International Journal of Internet Technology and Secured Transactions (24 papers in press)
Providing a model based on Poisson distribution for malware propagation assessment in Peer-to-Peer networks
by Shadi Haghi, Mahdi MollaMotalebi
Abstract: The use of peer-to-peer networks has increased dramatically in recent years in applications infrastructure such as file sharing, gaming, instant messaging and content distribution. These networks suffered from the problem of large-scale incompatibilities, which was organized by the super peer to overcome this problem. This structure has a two-layer architecture in which some nodes with more resources (higher bandwidth, higher processing power) are considered as super peers. Each super peer has a number of regular nodes (or regular members). On the other hand, it has attracted the attention of malware makers, especially worms, because they can easily be replicated and propagated in such a way. So far, several models have been presented to assess the behaviour of worm propagation in peer-to-peer network, but there has not been any effective review of how the worm propagates in super-peer networks. Hence, providing an effective model for expressing the propagation of a worm to identify its dangers and providing new solutions for detecting and confronting it in super peers networks is necessary. This paper presents a framework for modelling the connectivity of the super-peer network and then examines the behaviour of active worm propagation based on epidemic models on this framework. The results of the simulation of worm propagation behaviour in super-peer networks in comparison with the way they propagate in peer-to-peer network indicate that the worm propagate more rapidly in super-peer networks. Also, the results of the implementation indicate that the model presented in this study has achieved a significant improvement in reducing the rate of propagation of worms compared to previous work.
Keywords: Super-peer network; flat peer-to-peer network; Malware; Active worm; Modelling worm propagation behaviour.
A hybrid blockchain proposal to improve Valued Added Tax (VAT) recovery
by Christophe GAIE, Markus Mueck
Abstract: In the present article, we propose a novel hybrid blockchain approach to improve VAT recovery, meeting privacy requirements as introduced by the European General Data Protection Regulation. Indeed, the existing blockchain systems rely on distributed decision making using different cryptocurrencies whose transparency is a real improvement to prevent tax fraud: if each node of the system which keeps an informatic track of every transaction, it will not be possible to hide cash transactions. However ensuring the transparency and security of transactions requires a tremendous amount of energy. Therefore, the idea proposed in this paper is to introduce an authority with a limited action in order to take advantage of the decentralized advantages of cryptocurrencies while reducing their energy consumption.
Keywords: Data Analytics; Fraud Detection; Tax Recovery; Telecommunications; Blockchain; Privacy Protection.
Efficient way in sharing of IoT data and uses of Blockchain in Auditing the storage data
by Ackley Joseph Lyimo, Kakelli Anil Kumar
Abstract: Today the need for technology in various aspects of life has risen abruptly, hence leading to the expansion of the Internet of Things (IoT), but when it comes to IoT data, there is a myriad of issues regarding controlling and auditing it. A lack of measures taken for security can also make IoT vulnerable to a number of threats. To better maintain and minimize these threats, using Blockchain can play a significant role by auditing and recording all actions that occur while collecting the data and storing the same in the cloud. Due to the nature of consensus methods in a Blockchain system, we introduced the uses of the Interplanetary File System wherein the data collected will be stored in them and a hash value will be retrieved which will be sent to the Blockchain and recorded. In this paper we introduced better Blockchain-based design for IoT which can show the distributed control of how IoT data is collected, recorded for auditing and stored. Through this system we succeeded in achieving secure sharing of IoT data and proper utilization of cloud storage resources.
Keywords: Blockchain; Internet of Things (IoT); Interplanetary File systems (IPFS).
Detecting Botnet Using Traffic Behavior Analysis and extraction of effective flow features
by Sanaz Feizi, Hamidreza Ghaffari
Abstract: Botnets is one of the most serious attacks that cause irreversible damage to systems and networks, and it is important to detect and prevent botnets as attacks using them are constantly occurring. In the paper, the botnet detection method proposed so far was analyzed, and based on the analysis, botnet detection method and effective flow features extraction method were proposed. The proposed method in this paper is able to detect and identify them not only during the attack phase, also in the C&C phase of botnet life cycle before they can attack the system or network. The proposed model is based on traffic behavior analysis to detect botnet-related command and control traffic designed by using classification through selecting effective network flow-based features, which has the advantage that it can also detect encrypted traffic. Accordingly, it is thought that the paper will be an important help for various studies in the method of detecting botnets.
Keywords: Botnet Detection; Network Flow; Traffic Behavior Analysis; Random Forest; Intrusion Detection.
An IoT-based two-factor divide and conquer task scheduler and deep resource allocator for cloud computing
by Sripriya Arun, Sundara Rajan
Abstract: The epidemic developing rate of the networking technologies has resulted in an impressive sizeable scope of the associated computing framework. Internet-of-things (IoT) is considered a substitute for acquiring high performance by the improved potentialities in task scheduling, resource allocations and information exchanges. However, the current IoT is experiencing the gridlock of the task scheduling and resource allocation due to the higher level of dependency while scheduling and convoluted service contributing frameworks. With task scheduling and resource allocation considered with salient characteristics of cloud computing (CC) environment, this paper proposes a method called two-factor task scheduler and deep
resource allocator (TFTS-DRA) based on IoT. In this method, each task is processed before its actual allocation to the cloud resources by cost and time-based divide and conquer task scheduling model. The resources are allocated using deep resource allocation model, which considers the auto encoder (AE) and fully connected neural network (FCNN) with energy consumption and transmission delay of cloud resources as constraints. Simulation results show that the proposed TFTS-DRA method performs in an extensive manner with higher throughput rate. The numerical results shows that
proposed deep resource allocator algorithm in an IoT-CC environment, both the bandwidth utilisation and energy consumption can be improved.
Keywords: internet of things; IoT; cloud computing; two factors; task scheduler; deep resource allocator; auto encoder; fully connected neural network.
Expanded test frequency band and improved field uniformity in a reverberation chamber for networked system by dual-band quadratic residue diffusers
by Eugene Rhee
Abstract: This paper shows electromagnetic field characteristics in an electromagnetic reverberation chamber that can be used as a test facility for measuring electromagnetic interference and radiated immunity of networked systems. In the reverberation chamber, there is a dual-band diffuser for two different frequency bands and the dual-band diffuser is designed by the combination of different single-band Schroeder-type quadratic residue diffuser (QRD). Finite-difference time-domain (FDTD) numerical analysis method is used to analyse the distribution of electromagnetic fields inside the reverberation chamber. Compared with existing single-band diffuser, this dual-band diffuser in the reverberation chamber not only expands the test frequency band but also improves the performance of the reverberation chamber such as electromagnetic field uniformity, polarisation characteristics, power efficiency and tolerance of the reverberation chamber. Which means that the reverberation chamber with this dual-band diffuser is a more efficient test facility than the reverberation chamber with existing units.
Keywords: reverberation chamber; diffuser; field uniformity; frequency band; electromagnetic compatibility; electromagnetic interference.
Explicit traffic shaping scheme in content centric networking
by Jihoon Lee, Eugene Rhee
Abstract: Content centric networking (CCN) is considered as the prominent future internet architecture. CCN packets are routed based on content name itself, not on IP address and has two kinds of packets such as interest and data. CCN has a security model to secure content pieces, not to secure a transmission session. However, CCN has not widely taken the side effect to the occurrence of network congestion. So, this paper proposes the traffic control scheme in CCN environment to reduce high communication overhead, long content retrieval time, and high resource consumption. The proposed traffic shaping scheme for data packets tries to delay the transmission of data packets during network congestion.
Keywords: content centric networking; CCN; traffic control; traffic shaping.
Centralised and distributed authentication scheme in internet of things: review and outlook
by Upendra Verma, Diwakar Bhardwaj
Abstract: Internet of things (IoT) is the promising technology in which devices equipped with processors, actuators and sensors communicate with each other to serve a meaningful objective. Security is the essential requirements and authentication plays a vital role in IoT system. This paper is a comprehensive attempt to provide state of art survey of available centralised and distributed authentication scheme till 2020. The comparison has been carried out in terms of various factors network model, type of architecture, application domain and IoT layers. Based on the finding, it can be observed that IoT architecture and how the authentication is performed criterion can play an important role for deciding the authentication scheme. This paper provides summary of wide range of authentication schemes with the help of showing their strengths and limitations. The paper introduced a conceptualisation process of authentication for IoT, which constitutes a footstep for researchers working under different application domain.
Keywords: conceptualisation process; centralised authentication scheme; distributed authentication scheme; IoT architecture; network model; type of architecture.
Robust baggage detection and classification based on local tri-directional pattern
by Shahbano, Muhammad Abdullah, Kashif Inayat
Abstract: In recent decades, the automatic video surveillance system has gained significant importance in computer vision community. The crucial objective of surveillance is monitoring and security in public places. In the traditional local binary pattern, the feature description is somehow inaccurate, and the feature size is large enough. Therefore, to overcome these shortcomings, our research proposed a detection algorithm for a human with or without carrying baggage. The local tri-directional pattern descriptor is exhibited to extract features of different human body parts including head, trunk, and limbs. Then with the help of support vector machine (SVM), extracted features are trained and evaluated. Experimental results on INRIA and MSMT17 V1 datasets show that LtriDP outperforms several state-of-the-art feature descriptors and validate its effectiveness.
Keywords: carrying baggage detection and classification; local tri-directional pattern; support vector machine; SVM; boosting machine; video surveillance.
Energy efficient cross layer time synchronisation in cognitive radio networks
by S.M. Usman Hashmi, Muntazir Hussain, S.M. Nashit Arshad, Kashif Inayat, Seong Oun Hwang
Abstract: Time synchronisation is a vital concern for any cognitive radio network (CRN) to perform dynamic spectrum management. Each cognitive radio (CR) node has to be environment-aware and self-adaptive and must have the ability to switch between multiple modulation schemes and frequencies. Achieving same notion of time within these CR nodes is essential to fulfil the requirements for simultaneous quiet periods for spectrum sensing. Current application layer time synchronisation 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 uses 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 synchronise two CRN nodes. This conserves the energy utilised by application layer protocol and makes a CRN energy efficient and can achieve time synchronisation in short span.
Keywords: time synchronisation; cognitive radio; clock correction; symbol timing recovery.
Automated analysis of blood vessel permeability using deep learning
by Yoojin Chung, Hyunwoo Kim
Abstract: This paper presented a deep learning-based approach using CNN that automatically detects changes of permeability in the blood vessel network after exposing the vessels to chemicals. Because chemicals can affect the permeability of the vessels, it is important to characterise and quantify the changes to blood vessels accurately from time-lapse microscope images. We increased the number of data by applying diverse augmentation methods to 2,800 images. In this paper, we also devised a method of automatically labelling 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; convolution neural network; CNN; blood vessel permeability.
Intelligent intrusion detection system using log cluster decision tree detection mitigation in complex event processing
by S. Sandosh, V. Govindasamy, G. Akila
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 defence. 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, 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; performance metrics; IIDS-LCDTDM.
Discovering social bots on Twitter: a thematic review
by Rosario Gilmary, Akila Venkatesan, Govindasamy Vaiyapuri
Abstract: The onset of online social networks (OSN) like Twitter became a predominant platform for social expression and public relations. Twitter had 330 million monthly active users by the year 2019. With the gain in popularity, the ratio of virulent and automated accounts has also increased. It is estimated that 48 million of its functioning accounts are bots. Precisely, Twitter bots or Sybil accounts are kinds of automated web robot software that regulate activities like the tweet, retweet, like or follow via Twitter API. These bots misguide and delude genuine users by spreading spurious content. Hence, uncovering malicious bots from authentic users is obligatory to ensure a safe environment on Twitter. In this paper, the nature of Twitter bots and features of bot detection are discussed with their efficiency. Various bot detection approaches are classified based on the attributes and techniques used. Strong and weak aspects of distinct features and techniques are discussed. Key challenges and future research directions in detecting social bots are also presented. Special reference has been emphasised to contemporary emerging trends.
Keywords: social media; Twitter; OSN security; online social networks security; social bots; categorisation; suspicious behaviour detections; bot detection techniques.
A review on secrecy performance of cooperative relay network with diversity
by Khyati Chopra
Abstract: In the past few years, there has been a rapid increase in demand on transmitting data over the open wireless medium. Severe issues of information security and privacy thus arise, as the wireless transmissions may be intercepted by any unintended receiver in the network. There is a need to design the transmission system in an efficacious way, such that the available space and time can be used adequately. This becomes a challenging job as there are random variations in the channel quality due to deleterious effects of the multi-path fading. Hence, to improve the transmission reliability, coverage probability and throughput, relay aided communication draw in great attention from both academia and industry. Relays provide the advantage of cooperative diversity, where the directly transmitted signal and the relayed signal can be combined at the receiver using various diversity combining schemes to mitigate the fading effect. In this paper, we review the secrecy performance of dual-hop cooperative relay system with diversity reception and relay selection. The significance and secrecy effect of channel knowledge at the transmitter is also studied. We have corroborated that CSI knowledge at the transmitter can improve secrecy.
Keywords: decode-forward relay; secrecy outage probability; SOP; channel state information; CSI; cooperative communication; diversity combining.
QoS assurance for PON-based fronthaul and backhaul systems of 5G cloud radio access networks
by Muhammad Waqar, Ajung Kim
Abstract: The newly proposed fronthaul and backhaul (FB) segments in the cloud-radio access networks (C-RANs) could be leveraging solutions to satisfy the 5G demands, but the rigorous one-way delay and packet delay variations (PDVs) requirements of fronthaul networks are the bottleneck. 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 to fully exploit the cost benefits, but due to the poor performance of the PON systems for the 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 pre-emption-based buffering schemes to transport the FB packet flows simultaneously at tolerable delays and PDVs.
Keywords: backhaul; buffering; cloud-radio access networks; 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 and Merkle signatures
by E.S. Phalguna Krishna, Thangavelu Arunkumar
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 optimisation 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: internet of things; IoT; denial of service; DoS; 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 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 and it is a field which is relate our study to the structure, examination, association, accumulation, looking, and recovery of data. The objective of this paper is to search the query development strategy utilising reverse term recurrence to improve the proficiency and exactness of the data recovery framework and its accuracy in query processing, which leads to most recent trusted digitising 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 and they are used as an 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; ITF; query expansion; precision; KLD-mean; semantic similarity; term-pooling; internet of things; IoT.
An Architecture for Enabling IoT interoperability between cross-platforms
by Venkateswara Raju, Manjula R. Bharamagoudra
Abstract: The Internet of Things (IoT) continues to evolve and more and more IoT platforms provide access to things. However, IoTs ability lies in the development of cross-domain IoT ecosystems in these platforms, offering new, unexpected applications and value-added services. We have identified two key perspectives critical to the development of an IoT ecosystem: (i) Enable interoperability between platform development and cross- platform implementation of applications on Internet platforms; (ii) Market (or Trade Centre) to exchange and adapt IoT resources. Given these two important perspectives of an IoT ecosystem, this article introduces the BIG (Bridging the Interoperability Gap) IoT architecture as the basis for the creation of IoT ecosystems. Architecture responds to key needs that have been evaluated by industry and research associations as a key aspect of the BIG IoT project. We present a proof of the application of the concept in the context of a smart healthcare scenario. We adopted the generic RESTful Application Programming Interface (API) methodology to detect & interact the smart object platforms.
Keywords: Internet of Things( IoT); Interoperability; Architecture; Marketplace (or)Trade centre; Healthcare; Applications; Services.
Enhanced Adaptive Trust Management System for Socially related IoT
by Geetha Venkatesan, Avadhesh Kumar
Abstract: The Social IoT (SIoT) is a network involving heterogeneous entities like a human, devices referred to as things are connected with social relationship. Every individual thing has its own id, functional property, limited storage and capacity. Each one expects to establish trusted communication with other reliable entities in the IoT network, which paves the essential of Trust Management System (TMS). We propose an adaptive trust management design that performs trust assessment considering both QoS and Social parameter for deciding the trustiness of a node in the IoT network. The design uses direct assessment and indirect recommendation, which are aggregated using a dynamic weighted method. The decay factor for the past experiences and dynamic updating of the trust profiles enhances the system performances. The work is compared with static, distributed, social and single trust type of system in terms of resiliency and performance. The proposed work shows very efficient trust assessment and maximum performance.
Keywords: Internet of Things;Trust Management;Social parameter;QoS;Social IoT.
An Effective Cloud Based Smart Home Appliances Automation in IoT using PHMM Model
by M.R. Sundarakumar, S. Sankar, S.R.S. Reddy
Abstract: Internet of Technology (IoT) is an emerging and innovative approach to control the home appliances remotely. A trillion of devices are connected to the Internet that are controlled and monitored in real-world applications. The main goal is to provide the automation for home appliances using IoT. Wireless Sensor Networks (WSN) based home automation systems are very difficult to manage the devices using a centralized approach due to the mobility. To solve this issue, Wireless Home Automation System (WHAS) is proposed, which uses the Predictive Hidden Morkov Model (PHMM) to control the devices efficiently and conserves the energy utilization among the devices. The status of the devices are monitored continuously and selecting the device operation either in manual mode or automatic mode using the PHMM model. The proposed approach conserves more energy than traditional methods.
Keywords: Wireless Home Automation Systems (WHAS); Internet of Things (IoT); Web of Things (WoT).