International Journal of Internet Technology and Secured Transactions (47 papers in press)
AN EVALUATION OF IDENTITY AND ACCESS MANAGEMENT SYSTEMS
by Yousef Sanjalawe, Mohammed Anbar, Qusay Alzubi
Abstract: Abstract: One of the most critical issues of all of networks types that integrate the both of wired and wireless technologies is the performance and applicability of the electronic authentication and identification techniques. These schemes involve various technologies of different levels of security. This research presents a comparative study of six IDAM available tools, based on the three characteristics (ease of use, usefulness, and users satisfaction), which build targets to be achieved in order to gain quality in software. The tools compared in this study are Log Mote, Oracle ID management, Tivoli Identity Manager, NetIQ-Novell, access sentinel, and Active directory. In order to enable users to access the available resources in a secure way, we propose a novel architecture of IDAM. The proposed architecture basically has several advantages like, autonomy, comprehensive and systematic, standardization, and scalability.
Keywords: Identity and access management; Identity management; IDAMs tools; Evaluation.
Cluster based optimal sink repositioning technique for WSNs using an improved glowworm swarm optimization and S* position search algorithm
by B. Santhosh Kumar, P. Trinatha Rao
Abstract: Wireless sensor network is a group of organized sensor nodes that are limited to their resources such as limited bandwidth, energy etc. The data gathered from sensor nodes will be forwarded to the sink node to take proper actions. In order to avoid the failures, the sink nodes should be positioned in the better place for the resource optimization. In this paper, first we will apply clustering for grouping the nodes that are adjacent to sink node. Clustering is done by an improved glowworm swarm optimization (IGSO) algorithm. The node which has the shortest path is selected for position. Hence, this approach is used to find the optimal position for all the sinks in order to optimize the lifetime of the network and move according with intelligent sink positioning.
Keywords: WSN; sink repositioning; network lifetime; sink nodes; clustering; IGSO.
Robust transcoding-resilient H.264 watermarking
by Grace C.-W. Ting, Bok Min Goi, Sze Wei Lee
Abstract: The H.264 standard is widely deployed for high-quality consumer video recording, storage and sharing applications such as Blu-ray DVD and streaming HD video on the internet including YouTube. In current times, since videos are easily shared live on social media and messaging mobile Apps, users need the ability to determine the ownership of these videos against being illegally distributed without proper acknowledgements to the owners, and to take actions against those who spread false videos that trigger viral fake news. Robust watermarking schemes are popularly applied techniques to solve these problems. These types of schemes are required to achieve robustness against modification attacks on the embedded watermark. In this paper, we present a robust watermarking scheme for these purposes. We demonstrate that it is able to withstand common modification attacks launched by malicious buyers aiming to modify the watermarks embedded by the owner, and that it is furthermore resilient to transcoding.
Keywords: Security; robust; transcoding resilience; watermarking; attacks; design; HD video.
Blockchain application in supply chain chemical substance reporting a Delphi study
by Sukhraj Takhar, Kapila Liyange
Abstract: Blockchains utilize digital ledger technology to enable data to be encrypted, recorded and traced in a more efficient manner than traditional paper-based systems. Smart contracts extend the capabilities of a blockchain by defining specific obligations. Chemical regulations impose the need on industry to record and report the use of hazardous chemicals within products. The process of collating supply chain chemical substance reporting information is a manually intensive and lengthy process as data needs to be requested, collated, checked, verified and rolled up to assess potential business continuity risks, as well as varying levels of reporting activity back to employees, consumers and chemical regulators. The primary research question answered by this paper relates to the potential use of a blockchain with a smart contract to enable the automated collation of supply chain chemical substance information for manufactured products. This paper presents the findings from a Delphi study, where the respondents reviewed proposed concepts and provide opinions. A proposed Supply Chain Chemical Substance Reporting (SCCSR) blockchain is presented based on the findings of the Delphi study. The SCCSR blockchain enables industry to implement greater efficiencies in collecting the required chemical substance information from a supply chain, which in turn will enable the required regulatory actions to be generated, as well as the investigation of alternative less hazardous substances which may be utilized by the supply chain.
Keywords: Supply chain chemical substance reporting; blockchain application; chemical regulations; business continuity risks; supply chain management; technology and innovation; Delphi method; automated data collection and validation; distributed ledger technology; digitalization.
A Survey on Emerging Issues in Interconnection Networks
by Mehrnaz Moudi, Mohamed Othman
Abstract: Nowadays, the interconnection network is considered as an important architectural choice for the future parallel system in many processors owing to the scalable nature of the interconnection network. The basic idea of interconnection is to reach efficient network communication and overcome scalability problems. Since an interconnection network plays a critical role in such computers, with millions of processors providing an efficient data transferring in the possible shortest time without congestion, designing various topologies for these networks is of high significance. This survey paper focuses on the issues emerged during the design of enhanced interconnected topologies to provide efficient inter-processor communication considering a maximum number of transferred packets in the shortest path.
Keywords: interconnection; topology; routing; switching; traffic; congestion; deadlock.
Secure SMS Transmission Based on Social Networks Messages
by Saman Shojae Chaeikar, Saeed Yazdanpanah
Abstract: Nowadays, short message communication has a wide range of applications in modern lives. Authentication, announcements, reports, and personal communications are the common instances of application of this widely used digital media. At transmission time, the message content spreads in the air without any intrinsic security countermeasure. As a result, the content of messages is interceptable without the need for complicated equipment. In modern methods, security has migrated from hardware to software, especially in smartphones. In this research, a method for securing short message communications is introduced which uses four distinguished cryptographic key generation factors to produce a couple of unique and dynamic encryption and decryption keys. The evaluation results show that the proposed method uses secure encryption and decryption keys, is resistant against a wide range of cryptographic and network attacks, outstandingly reduces the cost of establishing secure sessions, and highly satisfies the users with the delivered level of security and usability.
Keywords: SMS Security; Short Message Security; Secure Communications; Secure channel; GSM operator; Social network.
A cost-effective strategy for Splitting and Allocating Alerts Workloads during Forensic Investigations of very large IDS logs
by Joshua Nehinbe
Abstract: The scarcity of suitable models that investigators can adopt to effectively manage and allocate resources during an outbreak of intrusions is recently gaining momentum in digital forensics. This research proposes a cost-effective model which employs two measures of impurity (as a bilateral and comparative approach) to split and allocate alerts workloads to two or more investigators of huge intrusion logs. The premise is that the splitting and allocation of the alerts workloads among investigators should be carried out such that the organization will incur no marginal cost at long run. In addition to the effective cost management, the process must guarantee timely delivery of forensic results; particularly in the face of exponentially increase in the alerts workloads generated by Intrusion Detection Systems (IDSs) and where there have been obvious diminishing returns and declining in the efficiency of the investigative staffs. Thus, the proposed model uses a sample of intrusion datasets, C++ language, Clustering, Entropy, Gini-Index and Timestamp to successfully demonstrate and visually establish the profitable split-threshold within which costs were minimal or non-existent.
Keywords: Intrusion; intrusion detection system (IDS); detector; Gini Index; Entropy; networks forensics.
AN ENHANCEMENT OF ECC BASED SESSION INITIATION PROTOCOL
by Rahul Kumar, Mridul Kumar Gupta, Saru Kumari
Abstract: Session initiation protocol (SIP) is the most prominent signaling scheme for controlling, establishing, maintaining and terminating communications on the Internet. Many researchers are working to create strong protocols for secure communication using SIP. Tu et al. proposed an improved authentication protocol for session initiation protocol. They show that their scheme can resist a number of security attacks. However, we find that their protocol suffers from inefficient login phase, inefficient password update phase, impersonation attack and unable to keep the user anonymity. To make all these types of attacks ineffective, we present a very efficient scheme for SIP. Security investigation of the proposed scheme shows that our scheme can make all the shortcomings of Tu et al.s scheme as ineffective.
Keywords: session initiation protocol; elliptic curve cryptography; impersonation attack; inefficient login phase; user anonymity.
Establishing Security of Bitcoins Using Elliptic-curve Cryptography Based Protocol
by Dilbag Singh
Abstract: It is undeniable that the growth of the computer and network security is repeatedly increased since the past 40 years. In 1985-1986 encryption was applied as a primary technique for providing security. Network security technology includes authentication and authorization, data encryption, access control, security auditing. \r\nBitcoin is presently one of the most popular cryptocurrencies. The phenomenon of Bitcoin crypto-currencies is based on the public key cryptography and peer to peer network. In the Bitcoin, blockchain is used for storage of the transaction which is also called the public ledger. Digital Money or Bitcoin are used in a day to day activities, some of which are illicit and illegal. In this paper the main area is Security i.e. the main focus here is to protect Bitcoin systems from unauthorized access and from various threats using an appropriate scheme (Elliptic-curve cryptography (ECC)) protocol.\r\n
Keywords: Bitcoin; Blockchain; cryptography; Network Security; Cryptocurrency; Automated Validation of Internet Security Protocols and Applications; AVISPA; Elliptic-curve cryptography.
Implementation of Symbol Timing Recovery for Estimation of Clock Skew
by Muhammad Usman Hashmi, Muntazir Hussain, Fahad Bin Muslim, Kashif Inayat, Seong Oun Hwang
Abstract: Time synchronization in any distributed network can be achieved by using application layer protocols for time correction. Time synchronization method proposed in this article uses symbol timing recovery at the physical layer to correct application layer clock. This cross layer methodology diminishes the quantity of message trades needed by application layer for time synchronization thus resulting in energy saving. Precision of skew estimate can be increased by using multiple message exchanges. Examination of the cross layer strategy including the simulation results, the experimentation outcomes and mathematical analysis demonstrates that clock skew at physical layer is same as of application layer, which is actually the skew of hardware clock within the node.
Keywords: Time synchronization; Symbol timing recovery; Energy constrained distributed networks; Energy efficient clock skew estimation; Frequency offset estimation; Sensor networks; Bayesian estimation.
A Location-aware Routing Protocol with Adaptive Transmission Angle Management in Mobile Overlay Cognitive Ad-hoc Networks
by Hyukchun Oh, Kyusung Shim, Beongku An
Abstract: Mobile cognitive ad-hoc networks is considered as one of the promising networking solutions for future mobile networks since the licensed spectrum can share the licensed user and unlicensed user. In this paper, we propose a location-aware routing protocol, called LRP, to enhance the spectrum efficiency in mobile overlay cognitive ad-hoc network and provide a solution to reduce the control overhead by using the adaptive transmission angle management. The main contributions of this paper can be summarized as follows. First, we propose a location-aware routing protocol, called LRP, to improve the spectrum efficiency for mobile overlay cognitive ad-hoc networks. More specifically, the proposed routing protocol can establish a route by avoiding the coverage of primary users (PUs). Second, the proposed routing protocol select the next node that is the nearest node from the center line between a source node and a destination node. Thus, the proposed routing protocol can transmit the data packet stably. Third, we propose an adaptive transmission angle management that takes into account the previous session' route state in order to reduce the amount of control packet in the considered networks. From the numerical results, the proposed routing protocol and adaptive transmission angle management efficiently support the network performances such as the packet delivery ratio, control overhead, and delay by using OPNET.
Keywords: location-aware routing protocol; adaptive angle management; overlay cognitive radio; mobile ad-hoc networks.
Energy-efficient Load-balanced RPL routing protocol for Internet of Things (IoTs) Networks
by Ali Kadhum Idrees, Athraa Witwit
Abstract: RPL (IPv6 routing protocol for low power and lossy networks) is a standard routing protocol in the Internet of Things (IoT) networks. It used by nodes which are characterized by limited resources (like energy, memory, processing power, and bandwidth). In the standard RPL routing protocol, the energy consumption balancing during selecting the preferred parents is not considered that leads to depleting the battery power of some loaded nodes faster than the other nodes. Besides, the original RPL routing protocol has increased control packets that lead to high energy consumption inside the nodes and decrease the network lifetime. Therefore, to overcome these problems, this article proposed Energy-efficient load-balanced RPL (EL-RPL) routing protocol for IoTs networks. In this protocol, a parent selection algorithm is proposed. It selects the parent in parent list to be the next hop node in the direction of destination node in network based on an objective function that combine between the highest remaining energy and the total number of received packets by the parent. This can balance the load on the all parents in the parents' list. Besides, the proposed protocol improves the DODAG construction by preventing the DIO packets transmission to the nodes with the lower ranks. This will lead to save energy and hence enhance the network lifetime. Many experiments were performed using the OMNeT++ network simulator to evaluate the efficiency of EL-RPL routing protocol. In comparison with some existing protocol, the results ensure that the proposed EL-RPL protocol can efficiently save energy, decrease the control packets, and improve the lifetime of the IoTs networks.
Keywords: Internet of Things; RPL routing protocol; network lifetime optimization; energy load balancing; performance evaluation.
Utilizing AHP and PROMETHEE for evaluating the performance of online services
by Abeer Ghareeb, Nagy Darwish, Hesham Hefny
Abstract: Limited usage of online services by citizens is one of the main obstacles to the success of e-government projects. Most of the previous studies have focussed on identification of the main significant factors affecting adoption of online services by using statistical methods for hypotheses tests. However, there is a need to go a further step and propose methodologies to examine to what extent such identified adoption factors are practically achieved. This turns the adoption process of online services to be a multi-criteria decision making problem which make it more practical for handling. Therefore, this paper aims to propose a methodology to evaluate the performance of online services utilizing two of the most well-known and extensively used multi-criteria decision making methods. It uses the hierarchy structure of AHP while using ranking procedure of PROMETHEE. The proposed methodology has been applied to evaluate the performance of a sample of 24 services available on the Egyptian national portal. Each service has been analysed against nine acceptance criteria covering application and service aspects. It is found that 46% of the evaluated services tend to be performing quite reasonably.
Keywords: Multi-criteria analysis; E-government; online services; Citizen Requirements; PROMETHEE; AHP.
Energy Efficient Cross Layer Time Synchronization in Cognitive Radio Networks
by Syed Muhammad Usman Hashmi, Muntazir Hussain, Syed Muhammad Nashit Arshad, Kashif Inayat, Seong Oun Hwang
Abstract: Time synchronization is a vital concern for any Cognitive RadiornNetwork (CRN) to perform dynamic spectrum management. Each CognitivernRadio (CR) node has to be environment aware and self adaptive and must havernthe ability to switch between multiple modulation schemes and frequencies.rnAchieving same notion of time within these CR nodes is essential to fulfillrnthe requirements for simultaneous quiet periods for spectrum sensing. Current application layer time synchronization protocols require multiple timestamp exchanges to estimate skew between the clocks of CRN nodes. The proposed symbol timing recovery method already estimates the skew of hardware clock at the physical layer and use it for skew correction of application layer clock of each node. The heart of application layer clock is the hardware clock and hence application layer clock skew will be same as of physical layer and can be corrected from symbol timing recovery process. So one timestamp is enough to synchronize two CRN nodes. This conserves the energy utilized by application layer protocol and makes a CRN energy efficient and can achieve time synchronization in short span.
Keywords: time synchronization; cognitive radio; clock correction; symbolrntiming recovery.
Automated Analysis of Blood Vessel Permeability Using Deep Learning
by Yoojin Chung, Hyunwoo Kim
Abstract: The paper presented a deep learning-based approach that automatically detects changes in the blood vessel network permeability. In-vitro construction of perfusable blood vessel networks that mimic skin vasculature has been developed to test sensitivity to various chemical used in cosmetics industry. Because chemicals can affect the permeability of the vessels, it is important to characterize and quantify the changes to blood vessels accurately from time-lapse microscope images. Objective and quantitative comparisons are needed so that chemical safety can be compared with respect to composition and concentration. In this paper, we constructed an optimized model using CNN (Convolution Neural Network) to automatically detect changes such as permeability and shape in blood vessel network after exposing the vessels to chemicals. Fluorescently labeled dextran dye was filled outside the vessels while applying the chemicals from outside, through a membrane-like material that simulate the skin. Fluorescence time-lapse images were taken to measure the infiltration of fluorescent dye into the blood vessels as the vessel walls were damaged by the chemicals. The number of data was increased to use them as CNN data by applying diverse augmentation methods to 2,800 original images. To use images as CNN data, each image should be labeled as to whether there is any change in the blood vessel in the image and it not only takes much time for a human to put a label on each of the numerous images but also is impossible to carry out this work with consistency. In this paper, we also devised a method of automatically labeling images as to whether there is any change in the blood vessel to obtain learning data for CNN by pre-treating images using diverse image processing methods and separately establishing thresholds for different images. To verify the performance of the developed CNN, we used 4-fold cross validation and blood vessel changes were automatically detected with an accuracy of 92.07 % in the experiment.
Keywords: Blood Vessel Network; Automated Recognition; Microfluidic Culture Platform; CNN; Blood Vessel Permeability.
Intelligent Intrusion Detection System Using Log Cluster Decision Tree Detection Mitigation in Complex Event Processing
by Sandosh S, Govindasamy V, Akila V
Abstract: The world of technology largely engages on the networks that provide the vast amount of data for the user all around the world. The networks can be of different domains that includes education, market or even defense. Hence the network has to be secure against any attacks that lead to intrusion. For securing the networks, several intrusion detection systems (IDS) are developed, however the possibility of intrusion remains in the networks. In the current work, we propose the novel Intelligent IDS with Log Cluster Decision Tree Detection Mitigation (IIDS-LCDTDM) technique in Complex Event Processing environment, an extension of our previous work. The novel system comprises of three major algorithms as Attribute Greedy Stepwise Selection, two-mean-log cluster along with tree detection and mitigation algorithm. The gure6percent dataset is used to evaluate the proposed algorithm for various performance metrics using Java/J2EE software. From the evaluation result, the proposed system provided the accuracy of 99.987%, which was better than our previous model with 99.9463%.
Keywords: Intrusion Detection System; Complex Event Processing; IIDS-LCDTDM; Performance metrics.
Effective feature selection based on MANOVA
by Trong-Kha Nguyen, Vu Duc Ly, Seong Oun Hwang
Abstract: Effectiveness in classifying malware is a critical issue which can overheat a classifier or reduce performance in real-time malware detection systems. However, the effectiveness in feature selection stage was not studied so far. As effectiveness should be taken into account at the earliest possible stages, in this paper, we focus on the effectiveness of feature selection. Firstly, we perform an analysis on instruction levels which consists of most frequencies mnemonics. Secondly, we propose new methods to select effective features by MANOVA statistical tests. Furthermore, we use those selected features fed to a classifier. Our approach reduces significantly the number of features from 390 to 4, which explains 99.4% variation of the data. With the selected features, we classify malware samples and have achieved 96.2% of accuracy and 0.6% of false positive.
Keywords: malware classification; statistical analysis; security.
Bitcoin price prediction using ARIMA model
by M. Poongodi, V. Vijayakumar, Naveen Chilamkurti
Abstract: Bitcoin is a highly volatile cryptocurrency with rising popularity. It is a turning point in the way currency is seen. Now the currency, rather than being physical is becoming more and more digital. Due to high variance of solo mining, the number of users joining top most famous bitcoin mining pools is increasing due to the fact that users together under a bitcoin pool will have a higher chance of generating next block in the bitcoins blockchain by reducing the variance and earning the mining reward. In this research paper we are doing a survey on the technology lying underneath bitcoin's network and the various machine learning predictive algorithms. We collected the dataset on bitcoin blockchain from 28 April 2013 to 31 July 2017 which is publicly available on https://coinmarketcap.com and applied the ARIMA model for price prediction of bitcoin.
Keywords: ARIMA model; bitcoin; cryptocurrency; blockchain; mining; predictive analysis; regression model; neural network; support vector machine; SVM; Bayesian model.
Optimising group key management for frequent-membership-change environment in VANET
by Baasantsetseg Bold, Young-Hoon Park
Abstract: In this paper, we propose a tree-based optimal group key management algorithm using a batch rekeying technique, which changes a set of keys at a certain time interval. In batch rekeying, the server collects all the joining and leaving requests during the time interval, and generates rekeying messages. In the proposed algorithm, when a vehicle joins a group, it is located at a certain leaf node of the key-tree according to its leaving time. This reduces the size of the rekeying messages because the vehicles that leave during the same time interval are concentrated on the same parent node. With the proposed scheme, tree-based group key management can be employed to the VANET because it solves the communication overhead problem. Using simulations, we demonstrate that our scheme remarkably reduces the communication cost for updating the group key.
Keywords: vehicular ad hoc network; VANET; batch rekeying; key-tree; group key management.
A brief review of blockchain-based DNS systems
by Saif Al-Mashhadi, Selvakumar Manickam
Abstract: One of the crucial parts of the internet is the domain name system, which works as a phonebook of the internet. The protocol is designed to be fast, reliable, and not shielded with a security mechanism, DNSSEC which adds authentication later. However, threats utilising DNS such as DoS/DDoS are increasing daily. On the other hand, blockchain-based DNS is secure by design. By reviewing and comparing it with the current DNS and its ecosystem, it is concluded that blockchain currently has challenges that need to be addressed before it can be adapted as a replacement for the existing DNS.
Keywords: domain name system; DNS; blockchain; Namecoin; Ethereum Name Service; ENS.
Key-factors of the constrained management for the internet of underwater things
by Khamdamboy Urunov, Soo-Young Shin, Jung-Il Namgung, Soo-Hyun Park
Abstract: Indeed, we provide a comprehensive research of management system in the internet of underwater things (IoUT) specification. The main contributions act as lightweight management mechanism based on underwater acoustic network. Several compression algorithms and implementation steps are a solutions of the underwater – SNMP (u-SNMP) integrations to the embedded system via u-MIB.
Keywords: underwater-network management system; U-NMS; network management system; NMS; internet of underwater things; IoUT; underwater-management information base; u-MIB; underwater-simple network management protocol; u-SNMP; management information base; MIB; simple network management protocol; SNMP; lightweight mechanism; cognitive algorithm.
Wide band time optimal spectrum sensing
by Rama Murthy Garimella, Rhishi Pratap Singh, Naveen Chilamkurti
Abstract: Conventional methods for spectrum sensing do not consider historical traffic data. Equal amount of time is allocated to each channel of interest for sensing. In this research paper, we formulate the time optimization problem for spectrum sensing keeping historical traffic data into account. We have solved the problem for interesting constraints. For the solution of these constraints stochastic programming formulation has been done. The problem is also formulated as a quadratic/hybrid programming problem where the variance of discrete random variable constitutes a quadratic form associated with a laplacian like matrix. Using this result, time optimal spectrum sensing is formulated as a multi-linear objective function optimization problem.
Keywords: spectrum sensing; Pareto front; integer programming; source coding; stochastic optimisation.
ADFT: an adaptive, distributed, fault-tolerant routing algorithm for 3D mesh-based networks-on-chip
by Zahra Mogharrabi-Rad, Elham Yaghoubi
Abstract: Nowadays, three-dimensional network-on-chips (3D-NoCs) have been introduced as the most efficient communication architectures. In these architectures, it is likely to encounter some faults. Therefore, an important goal in designing such architectures is to make them more tolerable against faults. In this paper, an adaptive, distributed and fault-tolerant routing algorithm called ADFT is proposed for 3D mesh-based NoC that is able to tolerate permanent faults and does not require any additional circuit for fault-tolerant. In order to evaluate the performance of the ADFT, we compared it with LOFT in terms of latency and throughput. Simulation results show improvement of the proposed method.
Keywords: three-dimensional network-on-chip; 3D-NoC; routing algorithm; permanent fault; fault-tolerant.
Android application security: detecting Android malware and evaluating anti-malware software
by Sangeeta Rani, Kanwalvir Singh Dhindsa
Abstract: Mobile devices have become widespread computing technology, people prefer to use than desktop devices. These connected devices and their features like an exchange of data, video calling etc. have made our lives simple but, this has also increased data security concerns. At present, Google's Android is dominating the market share of mobile devices; as a result, it has become a big target for malware writers. Android users can download applications from official or third-party stores. Google implements various security policies to ensure secure distribution of applications but third-party application stores have less efficient or no such policies. This makes such markets more attractive for malware writers. This paper investigates Android application security by analysing 1,946 free most downloaded Android applications in the year 2016: 1,300 from Google Play Store and 646 from third-party Android applications. 100 samples from 33 different malware families (with variants) prominent in the Android market during January 2016 to April 2016 were also collected that acted as a template for malware detection. Further, based on detected malware samples, an evaluation-based study on ten anti-malware applications is performed to identify how well they protect users from malware.
Keywords: Android; malware; applications; permission; anti-malware software.
Efficient and secured information transfer for congestion avoidance and collision detection in vehicular ad hoc networks (V2V) methodology
by Jaya Subalakshmi Ramamoorthi, Arun Kumar Sangaiah
Abstract: Vehicular ad hoc networks (VANET) connects the vehicle and the infrastructure in solving various issues on the travel path. In this paper, a multi-hop routing protocol is established to transfer the information among vehicles when the infrastructure is out of range from the source and provides warning system on congestion level. This increases the efficiency and reduces the cost of establishing the infrastructure mechanism at various points. The timely reporting at the infrastructure for decision making is the key concern and it has been addressed in this proposed concept. In addition, a payload format is proposed with the essential parameters such as position status, speed, heading, vehicle identification number, date etc. This gives the complete information about the vehicle thereby updating the database for future reference. Simulations of route path, message transfer frequency and time frame distribution is done with NS-2.
Keywords: vehicle to vehicle; communication; multi-hop; payload; congestion; collision detection; NS-2.
New hybrid framework to detect phishing web pages, based on rules and variant selection of features
by Youness Mourtaji, Mohammed Bouhorma, Daniyal Alghazzawi
Abstract: Phishing phenomena are increasing day after day due to its simplicity to use; it is enough for hackers to clone legitimate website and send it by e-mail to victims to access it within the use of social engineering techniques to lure them and gain their confidence. Hackers use the lack of knowledge of regular users when surfing on the internet and understanding the role of uniform resource locator (URL) of a web page. This fact let hackers create malicious forms of URLs, like very long ones or containing some suspicious characters. Despite cloning web pages, hackers can inject malicious codes into this web page for nefarious uses, so detecting or preventing this kind of web pages is the objective of this paper. We present a new hybrid framework to identify phishing web pages based on different ways and methodologies for features extraction techniques using only the URL as the main entry and without having any visual experience before, also we use hybrid analysis to be complete and accurate.
Keywords: malicious web page; hybrid analysis; machine learning; network security intelligence.
Parallel visible light communication system using video camera and LED for communicating and indoor positioning
by Sadeq Moradzadeh, Gholamreza Abaeiani, Amir Hooshang Mazinan, Mojtaba Alizadeh
Abstract: Visible light communication (VLC) is a desirable indoor communication system to transfer data using visible light. In this paper, visible light communication system using LED and video camera is considered as a transmitter and receiver for communicating and positioning, respectively. A new method is proposed for indoor positioning by the help of statistics and image processing tools. Furthermore, the proposed method is utilised based on neural networks and in variant moments in order to find and follow new location of the transmitter. The effectiveness of the proposed method is evaluated and proved by conducting experiments.
Keywords: visible light communication; VLC; neural networks invariant moments; indoor positioning; LED.
Special Issue on: NISS2018 Mobile Networks and Information Systems Security
Assessing node mobility impact on routing performances in MANETs
by Younes Ben Chigra, Abderrahim Ghadi, Mohamed Bouhorma
Abstract: Mobile ad hoc network (MANET) plays a major role in enabling data communication in infrastructures-less areas. Network performance relies on the capacity of mobile nodes to process data packet and deliver it to the right destination at lower cost. Since nodes are free to move toward random destination, data delivery from a source to a destination might be disturbed due to frequent topology changes. Hence, mobility in mobile ad hoc network represents the main issue that should be addressed carefully while designing routing protocols. The purpose of this paper is to study the impact of node mobility on the performance of well-known routing protocols such as destination-sequenced distance vector (DSDV), dynamic source routing (DSR) and ad-hoc on demand distance vector (AODV). We assessed the efficiency of each protocol under high mobility environment using various values of speed and pause. Performance assessment is based on the conventional metrics such as latency, throughput, packet delivery ratio (PDR) and routing overhead. Moreover, we introduced two new metrics called path change factor (PCF) and route repair influence (RRI) for accuracy purpose. The study demonstrates that AODV has better performances in high mobility environment.
Keywords: mobile ad hoc networks; MANET; routing protocols; mobility; QoS; NS2; metrics.
A scatter search algorithm to configure service function chaining
by Adel Bouridah, Hacene Belhadef
Abstract: Network functions virtualisation (NFV) emerges to deal with the challenges of reducing both the capital expenses (CAPEX) and operational expenses (OPEX) of cloud providers. The NFV is done by implementing network functions and providing them as software commodities. Network services are provided by chaining a set of network functions together. The key problem will be how and where network functions should be placed in the network and how traffic is routed through them. This is the well-known service function chaining problem and it is known to be NP-hard so exhaustive search algorithms have no significant benefit in large-scale context. This paper proposes a scatter search-based solution to configure service function chain. The aim is to produce the optimal number and placement of the required virtual network functions with the dynamic traffic steering over them. This is done while respecting computing and network resources constraints.
Keywords: network function virtualisation; NFV; service function chaining; SFC; scatter search.
Enhancing multipath routing using an efficient multicriteria sorting technique
by Layla Aziz, Said Raghay, Hanane Aznaoui
Abstract: Saving energy in MANET represents a critical issue due to its material architecture. This paper aims to improve ad-hoc on-demand multipath distance vector routing (AOMDV) using multicriteria analysis method. In order to construct effective disjoints paths, our approach focuses on sorting the different available paths considering several important criteria. Our objective is improving the network performances and routing stability using an efficient multicriteria method called Electre Tri. The use of this technique enhances data reach ability and minimises the required delay during packets forwarding. The proposed approach is evaluated comparatively to well known routing protocols considering various metrics. Simulation results prove that our approach improves significantly the network lifetime and the transmission delay.
Keywords: AOMDV; MANET; multicriteria analysis; multipath routing; Electre Tri.
Towards an agent-based framework for urban traffic congestion management
by Sara Berrouk, Abdelaziz El Fazziki, Zakaria Boucetta
Abstract: This paper introduces an integrated solution to the road congestion problem by modelling the road network, using real-time traffic data and drivers' parameters to compute the proposed congestion index for each road segment and generating recommendations to avoid the most congested trajectories. The proposed framework combines the benefits of the multi-agent systems, traffic data from static sensors and big data tools in order to optimise the traffic flow in urban areas. The congestion indexes are used in the road network generation which is represented by a weighted graph. The edges' costs are computed based on the congestion indexes and the edge's properties and vary when new traffic records are retrieved. In this study, the Hadoop framework is used in the data gathering and analysis along with an improved version of Dijkstra for the least congested path finding which allows the proposed framework to reach a higher level of performance.
Keywords: big data; Dijkstra; Hadoop MapReduce; multi-agent systems; road network modelling; traffic congestion; route recommendations.
Special Issue on: Machine Learning Algorithms for the Era of Integrated Internet of Things and Mobile Edge Computing
An early prevention method for node failure in wireless sensor networks
by S. Siva Rama Krishnan, Arunkumar Thangavelu
Abstract: Wireless sensor networks are used to monitor physical or environmental conditions such as temperature and pressure as well as to study the quality of certain environmental and natural entities like air and water bodies by collecting data about the various components present in the air/water at a given spot and time. But the complete data generated by the nodes in each iteration is not always useful, as most of them give the redundant information or details which does not provide any essential information, just bulge up the amount of data being transmitted. Therefore, this paper aims to formulate an early prevention method (EPM) which not only gives a way to detect failed nodes, but also increases the overall efficiency of the network by reducing the overhead at the sink.
Keywords: node failure; data aggregation; node efficiency; node life span; network overhead; bucketing; recommendation routing; network accuracy; wireless sensor network.
Hybrid machine learning model for healthcare monitoring systems
by M.K. Nallakaruppan, U. Senthil Kumaran
Abstract: The human life is facing a daunting task to handle the physical ailments. The late diagnosis of many diseases leads to serious complications on the human health. The lack of medical awareness is the primary cause of the lack of diagnosis and treatment which allows the disease grows easily. The prescribe work provides a solution to physically challenged or elderly people through web-based remote health monitoring facilities. The system collects the data, classifies them, apply the machine learning algorithms to ensure the data integrity. The reports are then generated and supplied to doctors for further examination of the patient record for taking medical decisions. We form a hybrid cluster of machine learning algorithms to ensure the increased accuracy and reduced error rate on the patient data measurement.
Keywords: support vector machine; SVM; body area network; BAN; internet of things; IoT; global system for mobile communication; GSM; wireless sensor networks; WSN; general packet radio services; GPRS.
Performance evaluation of ICI self-cancellation schemes in fractional wavelet-based OFDM system
by R. Ayeswarya, N. Amutha Prabha
Abstract: The widely used multi carrier modulation technique in the current wireless scenario is orthogonal frequency division multiplexing (OFDM). It is severely affected by frequency offsets and leads to inter carrier interference (ICI). Fractional wavelet transforms (FrWT)-based OFDM model is proposed to mitigate the effect of ICI by its orthogonal fractional wavelets. The performance of FrWT involved OFDM model is comparatively analysed through various mapping schemes of ICI self-cancellation in order to mitigate frequency offsets. This system overcomes the drawback of ICI self-cancellation and shows improved bandwidth efficiency without any cyclic prefix. Simulation results are carried out for the proposed model and compared with exiting Fourier transform and wavelet transform-based OFDM system. The analysis is performed for a range of normalised frequency offsets values. The proposed model performance is tested with various mapping schemes against a frequency offset of 0.05. It is proved that FrWT-based OFDM with ICI self-cancellation gives reduced bit error rate (BER) of 10–5 at 8 dB signal to noise ratio (SNR). From various graphs, it states that weighted conjugated transformation results in effective mitigation of ICI with BER achievement of 10-4.4 at frequency offset of 0.1.
Keywords: bit error rate; BER; frequency offsets; fast Fourier transform; FFT; fractional wavelet transforms; FrWT; ICI self-cancellation; orthogonal frequency division multiplexing; OFDM.
Survey of methodologies for quantifying software reliability
by Ganesh Viswanathan, J. Prabhu
Abstract: An important problem that arises in the testing of software programs is that given piece of source code is reliable or not. Software reliability is an important segment of software quality. So software reliability must be quantified. Quantification refers to measurement. A number of software metrics and statistical reliability models have emerged during the past four decades but no model can solve the issue. In this paper, we conduct a survey on various software reliability metrics and models.
Keywords: software reliability; software reliability metrics; software reliability assessment; survey of software reliability quantification.
Prevention of rushing attack in MANET using threshold-based approach
by S. Sankara Narayanan, G. Murugaboopathi
Abstract: Mobile ad hoc networks are a collection of mobile nodes that works without the centralised infrastructure. Every mobile node not only acts as host, it also works as router to forward packets that are received from neighbour nodes. Mobile ad hoc networks are useful in military environments, automated battlefields, emergency, rescue operations, disaster recovery, educational, home and entertainment applications. Here data must be routed via intermediate nodes. Rushing attack is one of the network layer attacks in MANET. In this attack, when the attacker node receives the route request packet, it immediately forwards the route request packet to its neighbours without processing the packet. Threshold-based approach is used to detect rushing attack in MANET. Proposed method provides better packet delivery ratio and throughput in presence of rushing attacker. Simulation results show that our modified DSR protocol performs better compared to secure DSR algorithm.
Keywords: rushing attack; MANET; modified dynamic source routing; MDSR.
A queuing theory model for e-health cloud applications
by M. Sathish Kumar, M. Iyappa Raja
Abstract: A healthcare application plays a significant role in people's healthier life in recent times. Cloud computing is an ease technology that provides resources to users on demand. In high-performance computing, cloud has been outgrew technology for providing its services to e-health applications by pay-as-you-go model. Workload management for e-health applications in the cloud is one of the major areas to focus on to achieve availability in e-health cloud. To manage the workload, elasticity is the key characteristics where the workloads are scaled up and down on demand. This can be achieved by effectively allocating and de-allocating virtual machines (VM). Henceforth VM allocation and de-allocation are the major issues in e-health cloud. In this paper, a Markovian-based queueing model is presented to manage the elasticity of an e-health cloud. There are two conditions were analysed in which 'virtual machine is failed' and the 'virtual machine can be recovered' and 'cannot be recovered'. The proposed model helps to improve the virtual machine scaling without changing the type of machine.
Keywords: healthcare; e-health; cloud; queuing; Markov.
EC(DH)2: an effective secured data storage mechanism for cloud based IoT applications using elliptic curve and Diffie-Hellman
by Balasubramanian Prabhu Kavin, Sannasi Ganapathy
Abstract: In the rapid growth of cloud computing with internet of things (IoT) technology utilisation in this fast world, security is an essential issue in cloud data storage and access the encrypted data. In the past, several researchers have worked on data storage mechanisms and came up with different ideas to fulfil the cloud user's expectation. Even though, they have failed to provide the sufficient security on cloud. For providing better security over the cloud, we propose a new elliptic curve and Diffie-Hellman based data storage mechanism called EC(DH)2. Here, the standard Diffie-Hellman algorithm is used twice as DH2 and it is combined with the standard elliptic curve cryptographic algorithm for performing secured storage in cloud based IoT applications. The experiments have been conducted by using the various sizes of documents and files for evaluating the proposed EC(DH)2 algorithm and is proven that it provides better protection and increased key size.
Keywords: cloud computing; Diffie-Hellman; DH; security; elliptic curve cryptography; ECC; internet of things; IoT; data storage.
Automated intelligent public lighting system
by Sudha Senthilkumar, K. Brindha, Amlan Jena
Abstract: Intelligent street lighting refers to public street lighting that adapts to movement by pedestrians, cyclists and cars. This type of lighting is different from traditional, stationary illumination, or dimmable street lighting that dims at predetermined times. Intelligent street lighting, also referred to as adaptive street lighting, dims when no activity is detected, but brightens when movement is detected. Apart from that in this model of intelligent street lighting the lights will be configured to interact with each other to inform further lights to turn on or off when activity is detected near them. This ensures that people always walk in well-lit areas but area where activity is not detected remains dark thus saving energy. The lights will also be fitted with sensors to detect available sunlight initially and only come into action when required instead of predetermined times, it will also have access to a web API that provides average sunrise and sunset times in the region to save energy by reducing usage of the sensor itself.
Keywords: GSM model; sensor light; IoT; microcontroller.
Special Issue on: ICGHIT 2019 Green and Human Information Technology
QoS Assurance for PON-Based Fronthaul and Backhaul Systems of 5G Cloud Radio Access Networks
by Muhammad Waqar, Ajung Kim
Abstract: The envisioned fifth generation (5G) of cellular networks is expected to provide high bandwidths and strict quality of service (QoS) to billions of smart devices at affordable budgets. The newly proposed fronthaul and backhaul (FB) segments in the C-RANs (cloud-radio access networks) be leveraging solutions to satisfy the 5G demands, but the rigorous one-way delay and packet delay variations (PDVs) requirements of fronthaul networks that can only be satisfied through the high capacity optical links increase the cost and thus, fronthaul segment becomes a bottleneck in the C-RANs. Time division multiplexing (TDM) based passive optical networks (PONs) can be a promising candidate to carry the fronthaul traffic, but the TDM-PON systems have limitations to meet the fronthaul QoS requirements due to unavoidable delays at the switching nodes. Moreover, the unification of FB traffics over the same segment is vital for fully exploit the cost benefits of the C-RANs, but due to the poor performance of the PON systems for fronthaul traffic, the backhaul traffic could not be forwarded through the same fronthaul segments. Therefore, in this paper, we propose and implemented the strict priority and frame preemption based buffering schemes to transport the FB packet flows simultaneously at tolerable delays and PDVs. The simulation result verifies that the considered schemes significantly improved the performance of the PON systems to comply with the QoS requirements of the 5G fronthaul and backhaul traffics in the C-RANs.
Keywords: backhaul; buffering; C-RANs; frame preemption; fronthaul; strict priority; 5G networks.
Special Issue on: Effective Management of Internet of Things Breaches
Security and Detection Mechanism in IoT based Cloud Computing using Hybrid Approach
by Megha Vashishtha, Pradeep Chouksey, Dharmendra Singh Rajput, Somula Ramasubbareddy, Praveen Kumar Reddy M, Thippa Reddy G, Harshita Patel
Abstract: This paper presented a secure environment of IoT based cloud computing. This approach used and enhanced Rivest Cipher (RC6) method along with blowfish algorithm. The combination of RSA and RC4 is accepted for the generation of Key to get the superior security method, on image, Blowfish algorithm is applied. In this method, initially cloud provider registers the cloud user which authenticates the user, then text and image data can be uploaded in the existing four servers. The uploaded data can be viewed directly by the self-verified account without any constraint, but if those files are demanded by the other cloud users then data classification encryption standard have been applied. The textual data is practiced with the enhanced RC6 method with key processing method of RC4 and RSA algorithm. These keys are used for the data decryption from the further side. The TA gives the information of the mismatch in the last prefix of the combination of the user detail and the data. If it does not match then the data will be corrupted by the blocker algorithm and no useful information has been visualized and any type of contravention is traced at the admin side and the cloud user both. The whole parametric comparison implies that the performance of our framework is better in comparison to the traditional techniques.
Keywords: Cloud Computing; IOT; Rivest Cipher (RC6); RSA; RC4; Blowfish;.
An evolutionary-based technique to characterize anomaly in Internet of Things networks
by Alok Kumar Shukla, Sanjeev Pippal, Deepak Singh, Somula Ramasubbareddy
Abstract: Internet of Things (IoT) can connect devices embedded in various systems to the internet. Distributed denial-of-service (DDoS) attacks on the Internet of Things are position a serious threat to any networks. A distributed denial-of-service attack is a malicious attempt to interrupt normal traffic of a victim system, service or enterprises by formidable the victim or its nearby infrastructure with Internet traffic overflow. Towards defending DoS attacks the significant number of mechanisms in recent years have introduced for building intrusion detection system (IDS) such as evolutionary algorithm and artificial intelligence. Unfortunately, the modern well-known DDoS attack detection strategies have been failed to rationalize the objective as fast and early detection of DDoS attack. In order to understand different DDoS attacks activities, in this paper, Teaching Learning-based Optimization (TLBO) with learning algorithm is integrated to mitigate denial of service attacks. The approach is based on building an intrusion detection system to the requirements of the monitored environment, called TLBOIDS. Furthermore, TLBOIDS selects the most relevant features from original IDS dataset which can help to distinguish typical low-rate DDoS attacks with the use classifiers namely support vector machine, decision tree, na
Keywords: Evolutionary Algorithm; Intrusion Detection; Denial-of-Service; IoT.
Robust and Provable Secure Three-Factor Mutual Authentication Scheme using Smart Card
by Niranchana R, Amutha Prabakar Muniyandi
Abstract: The best solution to perform remote authentication verification is
offered by the authentication scheme that opts smart card. Such schemes
are developed by using the combination of password and biometric identity.
Biometric based authentication schemes provide the most prominent security,
when compared to the alternative schemes available for authentication. In this
paper, a provable secure three-factor authentication scheme that makes use of
smart card is been proposed. This authentication scheme is developed based
on fundamental assumption of Discreate Logarithm Problem and Modular
Exponentiation. The formal and informal security analysis for the proposed
scheme shows that the authentication scheme is more secure. The efficiency of
this scheme is calculated based the performance analysis for both computational
and communication cost. It shows that the proposed authentication scheme is
performing well, when compared to the related authentication schemes.
Keywords: Smart Card; Authentication; Modular exponentiation; Bio-metric
identification; formal security.
An Improved Security Approach for Attack Detection and Mitigation Over IoT Networks using HACABO & Merkle Signatures
by Phalguna Krishna ES, Arunkumar T
Abstract: IoT is an agglomeration of heterogeneous technologies and interconnected devices that are autonomous and self configurable .Its constrained resources characteristic has made it more vulnerable to harmful attacks and tend to data loss and resource exhaustion due to wireless architecture of IoT. Handling security attacks, more particularly DDoS attack is one of the key challenges in IoT environment. This paper focuses on detection and prevention mechanism of IoT attacks. For that, an attack detection mechanism with Hybrid Ant Colony African Buffalo Optimization and hash-based Merkle signature-prevention mechanism is proposed. The paper also introduces Economic DoS (E-DoS) shield mechanism using CloudWatch to prevent high rate DDoS attacks since the conventional approaches cannot prevent it. Also, the efficiency of the developed model is compared with recent works.
Keywords: IoT; Denial of Service; E-DoS; IoT Attacks; Attack detection; Attack Prevention; Merkle signature.
Digital application of analog-like time perception mechanism based on Analog on Digital (AoD) theory
by Ziran Fan, Takayuki Fujimoto
Abstract: This paper analyzes the human time perception mechanism regarding the use of analog clocks based on the design theory of Analog on Digital (AoD Theory). With the examination, the authors would propose the method to apply the design elements of analog clock into the digital devices such as smart watches and smartphones to the schedule management. The proposed application represents the reality of time passing that is originally provided by analog clocks. The interface design adopts the time representation of analog clocks into the schedule display so that it can intuitively indicates the lapse of time passing for each activity scheduled in a day. Moreover, we design the users operational experience close to that of analog tools by realizing the real feel of using clocks through the representation of the spring-driven system on digital style.
Keywords: interface design; time perception; smartphone; smart watch; information media; media design.
An Upgraded Model of Query Expansion Using Inverse- Term Frequency (ITF) With pertinent Response For Internet of Things
by Surbhi Sharma, Abhishek Kumar, Rashmi Agrawal
Abstract: The IOT plays an important role for recent internet access-based task to future internet and information retrieval is a field which is relate our study to the Structure, examination, association, accumulation, looking, and recovery of data. Data recovery has turned into a significant field of study and research under software engineering because of complex development of data accessible as full message, hypertext, authoritative content, catalog, numeric or bibliographic content. The research work is going on different parts of data recovery frameworks in order to improve its proficiency and unwavering quality. The target of this paper is to search the query development strategy utilizing reverse term recurrence to improve the proficiency and exactness of the data recovery framework and this accuracy in query processing leads to most recent trusted digitizing trend IOT. As the technique for assessment of query development, we will expel irrelevant, excess and uncertain words from the recovered report dependent on client query. In proposed work, we present another technique for Query Expansion (QE) which depends on inverse term recurrence with importance criticism. Getting the top regenerated records use as in importance criticism for extra QE terms and developing applicant terms. Procedure of scoring strategy appoints score to one of a kind terms and applying Inverse term frequency (ITF) to deliver the rank reduce of terms. These terms will channel through semantic activity and reweighting produce refreshed (extended) question which will again send to look through apparatus.
Keywords: Inverse-term frequency; Query Expansion; Precision; KLD-mean; Semantic similarity; term-pooling; IOT.
Special Issue on: Internet Technologies and Business Systems Cases from the Gulf Cooperation Council
Factors Influencing Bitcoin Investment Intention: The case of Oman
by Abdelghani Echchabi, Mohammed Mispah Said Omar, Abdullah Mohammed Ayedh
Abstract: The current study examines the factors that might increase the investment in Bitcoin among Muslim communities. Oman is selected as a setting for this study due to the rapid progress in the Islamic finance and investment areas that the country has witnessed though ventured in this field relatively late compared to other countries. The study used a survey questionnaire to collect data for a sample of 200 respondents. Subsequently, the collected data was analysed using Structural Equation Modelling (SEM) as well as basic descriptive statistics and one sample t-test. The findings revealed that the respondents perceive themselves to have sufficient awareness and knowledge of the Bitcoin concept and benefits, as well as the techniques used to manage a Bitcoin account. In addition, the findings revealed that factors such as perceived ease of use, compatibility, awareness and facilitating conditions have a significant impact on Omani communities intention to invest in Bitcoin.
Keywords: Systems and Technology; Cryptocurrency; Bitcoin; Oman; SEM; Internet; Security.