Forthcoming and Online First Articles

International Journal of Communication Networks and Distributed Systems

International Journal of Communication Networks and Distributed Systems (IJCNDS)

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International Journal of Communication Networks and Distributed Systems (24 papers in press)

Regular Issues

  • Research on the optimization of whitelisting technology for network firewall in industrial control system using genetic algorithm
    by Xiuhong Zhou, Wenbing Shi 
    Abstract: Industrial control systems improve the efficiency of industrial production management but also bring network risks. This paper briefly introduced the industrial control system and the industrial firewall adopting whitelist policy and proposed to optimise the whitelist of industrial firewall with the genetic algorithm-support vector machine (GA-SVM) algorithm to make it learn the rules independently. Finally, simulation experiments were performed using industrial control data collected from light-emitting diode (LED) lamp production enterprises to compare the GA-SVM algorithm with K-means and traditional SVM algorithms. The results demonstrated that the GA-SVM algorithm had better detection accuracy and shorter detection time for abnormal industrial control data; the industrial firewall adopting the GA-SVM-optimised whitelist had lower false blocking rate.
    Keywords: industrial firewall; industrial control system; whitelist; genetic algorithm.

  • Cluster-based multiple malicious node detection using honeypot AODV (H-AODV) in MANETs
    by Sampada H. K. Kubsad, Shobha K. R 
    Abstract: Security and scalability are two major research areas in the field of mobile ad-hoc networks (MANETs). The existing solutions for security and scalability are majorly used for static networks e.g., sensor networks. The focus of the present work is to detect and remove the multiple malicious black holes (MBH) and multiple malicious grey hole (MGH) nodes from the dynamic networks e.g., MANETs. The proposed solution increases network security. An efficient weight-based clustering technique is used to enhance the stability and load balancing of the network. Cluster head (CH) is selected based on the maximum weight factor. The weight of the node is based on three factors constancy factor (Cx) trust value (Ty) and link factor (Lz). Weightage values for the parameters can be prioritised and tested for consistency using analytic hierarchy process (AHP) algorithm. Each CH executes honey pot-AODV (H-AODV) to find the MBH and MGH nodes in its network.
    Keywords: mobile ad hoc networks; MANETs; honeypot-AODV; H-AODV; modified-AODV; M-AODV; clustering; malicious blackhole/grayhole attack; MBH/MGH.
    DOI: 10.1504/IJCNDS.2024.10053453
     
  • Effect of User Mobility under Rician Fading on Power Allocation for Non-Orthogonal Multiple Access (PA-NOMA) Strategy   Order a copy of this article
    by Sandeep Singh Rana, Gaurav Verma, O.P. Sahu 
    Abstract: Non-orthogonal multiple access (NOMA) has been envisaged as a promising technique to meet the demand for massive machine-type communication (mMTC) devices. However, designing a NOMA system required a proper comprehensive study of user mobility, user switching, and imperfect successive interference cancellation (Im-SIC). In this paper, the effect of user mobility and Rician fading channel on power allocation for non-orthogonal multiple access (PA-NOMA) strategy is thoroughly investigated. This paper also discusses the challenges faced during the power allocation to multiple NOMA users. Mobility of the users violates the basic channel gain conditions of the NOMA users, therefore, to maintain the fairness index of the individual cell edge users dynamic power allocation strategy is adopted. Simulation results show that user mobility and Im-SIC have a significant effect on the PA-NOMA strategy for multiple users in terms of sum-rate capacity, average bit error rate, and fairness index.
    Keywords: fairness index; PA-NOMA; imperfect SIC; Rician fading; user mobility; user switching.
    DOI: 10.1504/IJCNDS.2024.10053703
     
  • Developing Policy Hierarchies for an Effective Distributed Systems and Network Management. Case Study in a Videoconference Service.   Order a copy of this article
    by Sarandis Mitropoulos 
    Abstract: Large-scale distributed systems and network management depends on complex relationships which are strongly related to the manager roles which are depended by a set of management policies. Management policies express peer-to-peer or hierarchical management relationships which constitute the policy hierarchies. Policy hierarchies must satisfy at the highest management level, the business goals, while the complex relationships between policies must be analysed for avoiding conflicts, developing in parallel synergy, strategic convergence, and optimisation of policy usage. This paper proposes an integrated approach for constructing policy hierarchies. A generic policy refinement framework is presented as a crucial factor for a succeeded policy hierarchy construction. The policy hierarchy analysis functionality is defined, providing a respective software tool in Prolog. The high applicability of the proposed approach is depicted in a case study concerning the management of a videoconference service.
    Keywords: integrated distributed system and network management; management policy hierarchies; policy refinement and analysis; videoconference service provision.
    DOI: 10.1504/IJCNDS.2024.10054947
     
  • Detection and Mitigation of a Link Flooding based DDoS attacks on a Software Defined Network using Network Function Virtualization   Order a copy of this article
    by Shariq Murtuza, Krishna Asawa 
    Abstract: Software Defined Networks (SDN) are emerging as the first choice for network administrators due to their agility, modularity and dynamism. Network operators can change the network topology, routes and other parameters as per their current requirement. Like the traditional computer networks SDNs are also prone to various Denial of Service attacks(DDoS). Link flooding attacks are a class of DDoS attack that aims to choke crucial network connections and can fully detach the victim from the network. In this paper we have discussed two Link Flooding based Denial of Service attacks, namely Coremelt and Crossfire, in the context of SDN along with the possible mitigation. These attacks are aimed at disconnecting services from the network. We demonstrate the usage of Network Function Virtualization along with SDN features to mitigate these attacks by recreating replicas of the services under attack and connecting them to the network.
    Keywords: Software Defined Networks; Network Function Virtualization; Denial of Service Attacks; Virtual Network Functions.
    DOI: 10.1504/IJCNDS.2024.10055095
     
  • An Enhanced Priority based Multi-hop Clustering Algorithm for Vehicular Adhoc Networks   Order a copy of this article
    by RAKHI S, Shobha K. R 
    Abstract: The importance of intelligence transportation system is increasing as it improves road safety and efficacy by means of vehicular ad hoc networks (VANET). The nodes in VANET are intelligent machines that can communicate with each other. Due to high mobility and frequent network fragmentation, stability is always a challenge in VANET. Even though traditional clustering methods address this issue, they exhibit less stability in highly dynamic scenarios. To improve the stability of the clusters, a new multi-hop clustering method named enhanced priority-based multi-hop clustering algorithm (EPMCA) is proposed. The best neighbours are chosen using neighbour following method. Then, stable clusters are established based on the average velocity of the cluster and association lifetime between the nodes by the cluster head. The proposed algorithm shows significant improvement in average cluster head and cluster member duration, average cluster head changes and number of clusters for varying communication ranges compared to existing techniques.
    Keywords: vehicles; stability; cluster; priority; multi-hop; vehicular ad hoc networks; VANET; enhanced priority-based multi-hop clustering algorithm; EPMCA.
    DOI: 10.1504/IJCNDS.2024.10055893
     
  • Asymmetric Multi-period Deep Residual Network Face Age Estimation   Order a copy of this article
    by Yilihamu Yaermaimaiti, Yan Tian Xing, Tusongjiang Kari 
    Abstract: Aiming at the problem that it is difficult for face age estimation to find features that accurately characterise face age changes, this paper proposes an asymmetric multi-period deep residual network face age estimation model. First, use an asymmetric residual block to improve the feature extraction ability of the network model; secondly, build a multi-period residual structure to solve the optimisation problem caused by network deepening; then, use a shortcut connection that combines pooling and convolution to reduce The information loss of the shortcut layer; finally, the age estimation method combining multi-classification and sequential regression is used to reduce the prediction error. Experimental results on three public datasets showed that the error (MAE/RMSE) of this model is reduced to 2.42/3.44, 3.38/4.69 and 5.17/7.34, respectively, which proved the effectiveness of the proposed algorithm.
    Keywords: feature extraction; asymmetric convolution; shortcut connection; information loss; error.
    DOI: 10.1504/IJCNDS.2024.10056335
     
  • Applications of Bluetooth and Wifi-Direct for Local Communication and their Performance Evaluation   Order a copy of this article
    by YUGBHANU RAJWADE, Divi Arpit, K. Jairam Naik 
    Abstract: Wireless connectivity may not be available in congested locations (such as concerts or conference-halls) or may be interrupted by infrastructure outages caused by earthquakes and tsunamis. They are the great boon when it comes to device-to-device communication based on technologies like Wifi-Direct and Bluetooth. However, no existing research builds a fully functional communication system which is local in nature, nor does it consider how the user mobility can be supported. A fuzzy logic-based normalised quantitative decision (FNQD) approach was proposed by the recent researchers, but it is suffering with the distance coverage among the communicating devices. We put forward an intragroup communication solution for local setup without the interference of any external network support. We propose a Bluetooth and Wifi-Direct (Wifi_BL) system that improves the distance coverage obtained from the existing fuzzy logic-based normalised quantitative decisions. The proposed Wifi_BL system attains better distance coverage over the existing FNQD.
    Keywords: local communication; Bluetooth; Wifi-direct; distance coverage; fuzzy logic.
    DOI: 10.1504/IJCNDS.2024.10056567
     
  • STAGNN: A Spatial-Temporal Attention Graph Neural Network for Network Traffic Prediction   Order a copy of this article
    by Yonghua Luo, Qian Ning, Bingcai Chen, Xinzhi Zhou, Linyu Huang 
    Abstract: Accurate and real-time traffic prediction can reasonably allocate the resources of communication networks and effectively improve the communication quality of networks. However, the complex topology and highly dynamic nature of communication networks pose new challenges for traffic prediction. To be able to effectively obtain the temporal correlation and spatial dependency of network traffic and mask the redundant traffic features, we propose a spatial-temporal attention graph neural network (STAGNN). The STAGNN combines the graph attention network (GAT) and the time series model informer, where GAT is used to learn the complex spatial dependencies of network topology and informer is used to learn the dynamic temporal correlation of network traffic. Also in learning, we introduce the multi-headed attention mechanism enabling STAGNN to quickly select high-value network traffic information using limited attention resources. The experimental results demonstrate that STAGNN has better prediction performance compared with other existing methods.
    Keywords: network traffic prediction; attention mechanism; temporal correlation; spatial dependency.
    DOI: 10.1504/IJCNDS.2024.10056816
     
  • A Survey on Wireless Sensor Network (Applications and Architecture)   Order a copy of this article
    by Ranjan Kumar Mahapatra, Yajunath Kaliyath, N. S. V. SHET, Soumya Ranjan Mahapatro, Gnane Swarnadh Satapathi, SANKATA BHANJAN PRUSTY, B. Shivalal Patro 
    Abstract: Proliferation of wireless sensor network is due to the advancement in wireless networks, information technologies, miniaturisation of sensors as well as convergence of MEMS technology, wireless communication and digital electronics. These wireless networks interface the physical world to the computing (virtual) world. In recent years, due to the availability of smaller, cheaper and intelligent sensors in a large scale has motivated to deploy the sensors in various applications such as smart city, smart home, smart grid, automated vehicles, etc. Sensor plays an important role in internet of things. This survey reports current research activities, applications, characteristics, architecture and case study of WSNs. In addition to this open research issues/problems are discussed. The aim is to present a comprehensive study of the literature on the several aspect of wireless sensor network such as application and architecture.
    Keywords: wireless sensor network; WSN; architecture; protocol; localisation.
    DOI: 10.1504/IJCNDS.2024.10057102
     
  • Searchlight: A Novel Data Delivery Cost-aware Multi-mode Data Transmission Scheme With Best-fit Resource Allocation for 6G Underwater Sensor Networks Applications   Order a copy of this article
    by Mahfuzulhoq Chowdhury 
    Abstract: With the huge developments of underwater communication technologies, the UWSNs have played a significant role to realize profitable sea and water resource discovery/management applications. The existing UWSN works do not investigate data delivery cost-aware multi-mode data transmission by considering different communication links, forwarding nodes, networking devices, resource allocation, and routing. Another crucial challenge is selection of cluster-head and forwarding nodes. A majority of the works investigate only underwater sensors cluster head selection rather than both cluster head and forwarding nodes. This paper comes up with a data delivery cost-aware scheme with a best fit resource allocation for UWSNs. This paper provides an integrated network model by coordinating terrestrial, non-terrestrial, and underwater networks. This paper yields a numerical model that includes finish time, energy depletion cost, network survivability, throughput, and utility metrics. The results of the proposed scheme achieves at least 45% utility gain than the traditional schemes.
    Keywords: Underwater Sensor Networks; Best-fit Resource Allocation; Energy Utility; Cluster Head and Forwarding Node Selection; 6G; Throughput; Network Survivability.
    DOI: 10.1504/IJCNDS.2024.10057140
     
  • A Critical Review of Feature Selection Methods for Machine Learning in IoT Security   Order a copy of this article
    by Jing Li, Mohd Shahizan Othman, Chen Hewan, Lizawati Mi Yusuf 
    Abstract: In the internet of things (IoT) era, the security of connected devices and systems is critical. Machine learning models are commonly used for IoT attack detection, where feature selection (FS) plays an important role. However, FS for IoT security differs from traditional cybersecurity due to the uniqueness of IoT systems. This paper reviews FS methods for effective machine learning-based IoT attack detection. We identify five research questions and systematically review 1,272 studies, analysing 63 that meet inclusion criteria using the preferred reporting items for systematic review and meta-analysis (PRISMA) guidelines. We categorised the studies to address the research questions regarding FS methods, trends, practices, datasets and validation used. We also discussed FS limitations, challenges, and future research directions for IoT security. The review can serve as a reference for researchers and practitioners seeking to incorporate effective FS into machine learning-based IoT attack detection.
    Keywords: internet of things; IoT; feature selection; IoT dataset; attack detection; classification; IoT security; systematic literature review.
    DOI: 10.1504/IJCNDS.2024.10057332
     
  • A survey on security threats in cognitive radio networks based on cooperative spectrum sensing   Order a copy of this article
    by Flavien Donkeng Zemo, Sara BAKKALI 
    Abstract: Cognitive radio networks (CRNs) are a technological revolution that allows unlicensed users (SUs) to opportunistically use the freely licensed spectrum bands of a primary user (PU). To avoid interference with the PU, SUs need to do accurate spectrum sensing. Spectrum sensing (SS) by a single SU user can be inaccurate in deep fading and multi-path environments. Cooperative spectrum sensing (CSS) is a technology implemented in CRNs to improve the results of SS in deep fading environments. But only the success of CSS is threatened by new forms of attacks on the physical layer, the main ones being the spectrum sensing data falsification attack (SSDF) and the primary user emulation attack (PUEA). In our paper, we present the CSS in detail. Subsequently, a relevant study on SSDF and PUEA attacks is carried out, and depending on the approach exploited, different research works to defend the CSS against these attacks are presented.
    Keywords: cognitive radio networks; CRNs; cooperative spectrum sensing; CSS; spectrum sensing data falsification attack; SSDF; primary user emulation attack; PUEA.
    DOI: 10.1504/IJCNDS.2024.10057458
     
  • Secure Key Exchange Protocol using Graph and Trusted Third Party   Order a copy of this article
    by Maroti Deshmukh, Arjun Rawat 
    Abstract: The exchange of cryptographic keys poses a challenge due to the need for secure communication channels. This paper presents an algorithm that employs a random complete graph, a trusted third party, and a circuit to ensure secure key transmission. The trusted third party generates a graph and uses a circuit (a path from sender to receiver) to transmit the key alongside the message. This process enhances security by making key tracing difficult. The proposed scheme generates a common session key through a graph permutation, outperforming existing schemes in terms of key size. It accommodates varying key sizes, making it adaptable to different scenarios. Moreover, the approach minimises computation and communication overhead by utilising a limited number of steps, graph weights, permutations, and multiplications, while involving a trusted third party.
    Keywords: key exchange protocol; asymmetric key cryptography; complete graph; key distribution; trusted third party; TTP.
    DOI: 10.1504/IJCNDS.2024.10057678
     
  • A Network Packet Classification Engine For Real-Time Applications with Enhanced Performance   Order a copy of this article
    by Midde Adiseshaiah, Maruvada Sailaja 
    Abstract: With the advancements in digital communication systems, security is one of the essential components of real-time communication systems. Packet classification is one of the most important networking tasks that helps to prevent hacking and unintended effects on connected devices. The slow processing speed of the router and other devices connected to it is an issue with real-time packet classification implementation. In this study, a brand-new architecture for packet classification in routers is put forth. The suggested design is capable of operating at high frequencies, which can satisfy the real-time requirements for networking applications. The proposed design uses low-area components with enhanced speed capabilities for higher energy efficiency. The design is implemented in both application-specific integrated circuits (ASICs) and field programmable gate array (FPGA) logic devices to validate the output. FPGA families, including the Virtex-4, 5, and 7 families, are used for synthesising in Xilinx software.
    Keywords: routing; packet classification; field programmable gate array logic; data security.
    DOI: 10.1504/IJCNDS.2024.10057791
     
  • An Objective Comparison of two Prominent Virtual Actor Frameworks: Proto.Actor and Orleans   Order a copy of this article
    by Edward Sykes, Alec Di Vito 
    Abstract: Recently there has been a significant increase in developing distributed systems easily and rapidly. Driven by the demand of software communities, developers seek tools and frameworks that abstract away low-level details of the underlying distributed system and the need to understand complex details on how the system works. Researchers have explored serverless frameworks, distributed key value stores, distributed stream processing frameworks and distributed actor frameworks. Currently, stateful serverless applications and distributed actor models may be the answer to what developers need. In this paper, we present a review of stateful distributed computing frameworks, and the results of experiments that compare Orleans and Proto.Actor — two popular actor model frameworks — running on Kubernetes. We discovered that the Proto.Actor performs at least two times faster than Orleans, but is more complex to learn. We present the results of these tests, and provide a discussion of future research opportunities highlighting virtual actor model frameworks.
    Keywords: actor model; distributed computing; microbenchmark tests; serverless computing; virtual actor frameworks.
    DOI: 10.1504/IJCNDS.2024.10057792
     
  • OPTIMIZATION TECHNIQUES IN POLICY HIERARCHIES FOR MANAGING DISTRIBUTED SYSTEMS AND NETWORKS.   Order a copy of this article
    by Sarandis Mitropoulos 
    Abstract: Large-scale distributed system management is an emerging task for all modern networked organisations. In this direction, corporate management systems are usually organised into domains, which specify the borders for policy applicability. Due to the complexity of such a task, techniques must be developed for resolving conflicts and optimising the management structures and performance. In this paper, after brief providing an overview of the related topics on policy-based system management, we propose mechanisms for consistency and minimisation of policy sets, and finally for optimisation in management structures adopting parallel processing techniques.
    Keywords: distributed system management; management domain structures; management policy hierarchies; optimisation; parallel processing.
    DOI: 10.1504/IJCNDS.2024.10057839
     
  • Robustness of Complex Networks Considering Load and Cascading Failure under Edge-removal Attack   Order a copy of this article
    by Peng Geng, Zixin Ye, Huizhen Hao, Annan Yang, Yan Liu 
    Abstract: This article challenges the conventional wisdom that edges with larger degrees are more important in complex networks. Through simulation analysis on the BA scale-free and WS small-world networks, we investigate edge-removal attack strategies, taking into account edge load and cascading failure. Specific attacks include high load edge-removal attacks (HLEA) and low load edge-removal attacks (LLEA). Our results demonstrate that the importance of edges is closely tied to the load parameter δ . When 0 < δ < 1, attacking edges with smaller degrees leads to greater cascading failures, rendering low-degree edges more important under these conditions. Conversely, when δ > 1, high-degree edges are more critical due to their ability to cause greater cascading failure upon removal. When δ = 1, cascading failure becomes independent of the degree of the removed edge. These findings underscore the need for considering edge loads and specific network conditions when assessing the importance of edges in complex networks.
    Keywords: complex networks; edge load; cascading failure; edge-removal attack; high load edge-removal attacks; HLEA; low load edge-removal attacks; LLEA.
    DOI: 10.1504/IJCNDS.2024.10058708
     
  • Extended Diffie Hellman Protocol Based on Exponential and Multiplication Operation Over Modular Arithmetic   Order a copy of this article
    by Sandeep Chand Kumain, Maroti Deshmukh, Maheep Singh 
    Abstract: In this modern digital world, a huge volume of data is transmitted over the internet. This data transmission is done through the communication channel and the communication channel might be insecure. The unauthorised disclosure and tempering of data is a threat to the integrity of the message in network security, hence security is required during the data transmission between two or more parties. Diffie-Hellman is the first key exchange protocol proposed for this purpose. However, there are several attacks are possible in this scheme. In this research article, the authors of this study providing the solution for passive attack and increase the Diffie-Hellman algorithm’s security against potential passive attacks even the mod value is small. In this extended improved version of Diffie-Hellman, the final key does not rely directly on mod value which makes the passive attack more complex as compared to the original Diffie-Hellman.
    Keywords: key exchange protocol; key agreement protocol; passive attack; Diffie-Hellman; modular arithmetic; exponentiation operation.
    DOI: 10.1504/IJCNDS.2024.10058942
     
  • Metaheuristic enabled hot event detection and product recommendation in social media data streams   Order a copy of this article
    by Manu G. Thomas, S. Senthil 
    Abstract: In this study, a unique system that recognises hot events and reliably integrates them with product recommendation systems is modelled. The correlation between the detected hot event and the user interestingness identifies the respective product that influenced the discussion. This results in the hottest action recognition being carried out through pre-processing, extraction of features and weight, text data modelling and cluster dependent topic identification. The keywords are initially extracted from each tweet. The evaluation of the different feature space is then completed and submitted to determine the design of the text model. Finally, clustering dependent hot topic identification takes place, where the optimisation logic plays its major role. Two different clustering processes take place: micro and macro-based clustering, where the selection of optimal centroid is made by a new enhanced monarch butterfly optimisation with three-level butterfly adjusting operator (EMBO-3BAR).
    Keywords: hot topic detection; HTD; pre-processing; feature selection; user interestingness; optimisation; product recommendation.
    DOI: 10.1504/IJCNDS.2023.10054096
     
  • Software-defined network planes - a survey on attacks and countermeasure   Order a copy of this article
    by D. Sendil Vadivu, Narendran Rajagopalan 
    Abstract: A smartly managed framework that enables the network to be configured via software application is termed software-defined networks (SDN). SDN gracefully abstracts the network management regardless of the underlying technology. The fundamental drive of SDN is to move from distributed control architecture to centralised control architecture. Though SDN provides complex security policies that can be easily customised to safeguard the network, it suffers from a single point of failure and opens to many security challenges. In order to withstand this centralised architecture, it is crucial to study the security aspects of the SDN. This paper surveys the various security techniques of the SDN stack from the perspective of individual layers.
    Keywords: software-defined network; SDN; SDN planes; security; flow table; OpenFlow; attacks; countermeasure.
    DOI: 10.1504/IJCNDS.2023.10051589
     
  • A learning-based approach to improving multicast network performance   Order a copy of this article
    by Hazem H. Abdulmajeed, Hesham A. Hefny, Assem Alsawy 
    Abstract: A neural network approach is recommended by us in this research paper, to solve the problem of multicast routing subject to some quality of service (QoS) restrictions in communications and internet of things (IoT) networks, which is considered a complete nondeterministic polynomial (NP) problem. This approach was taken to identify a multicast tree that satisfies those restrictions, in particular cost, delay, and data loss rate. The exemplary (shortest) path is identified by the recommended routing algorithm considering the traffic conditions (the incoming traffic flow, routers occupancy, and link capacities). The experimental results showed a significant difference in obtaining the exemplary path that was executed by the recommended method using the Hopfield neural network (HNN) approach, besides the number of iterations. Furthermore, the execution time is less compared with the recommendations of heuristic algorithms, such as the ant colony optimisation algorithm (ACO) and genetic algorithms (GAs).
    Keywords: multicast routing; internet of things; IoT; neural network; quality of services; QoS; heuristic algorithms.
    DOI: 10.1504/IJCNDS.2023.10051590
     
  • Fuzzy logic-based delay efficient data collection technique for IoT environment   Order a copy of this article
    by Deepa Rani, Tanuj Wala, Rajeev Kumar, Naveen Chauhan 
    Abstract: The sensor nodes in WSNs are resource constraints and data collection is draining the sensor node's energy. Therefore, collecting data in a single hop by the mobile device helps in preserving the sensor node energy. This paper is introducing a fuzzy logic-based one hop data collection path (FLO-DCP) algorithm to find stop points from the set of intersecting points of the overlapped clusters and to reduce the data collection time by shorting the path length of the mobile device and increasing the lifetime of the network by preserving the sensor node's energy. The proposed method consists of three phases. First, fuzzy logic-based overlapped clusters are formed, thereafter the stop points and trajectory path for the mobile device is being computed, and last, the data collection process is done. Also, in comparison with NDCMC, CB, and ORLP-RP algorithms, simulation results show that the proposed algorithm has better performance.
    Keywords: internet of things; data collection; fuzzy C-mean; FCM; clustering; trajectory; one-hop transmission; mobile device.
    DOI: 10.1504/IJCNDS.2023.10051768
     
  • Atrial fibrillation medical image encryption algorithm based on deep learning and adaptive block   Order a copy of this article
    by Jiangjiang Li, Lijuan Feng, Xibin Guo 
    Abstract: In this paper, a deep learning and adaptive block-based chaotic encryption algorithm for atrial fibrillation medical image is proposed. Firstly, we use 2D Sine Logistic chaos system to generate two security sequences with good chaotic characteristics. Then the image is divided into fixed size image blocks, and the maximum pixel difference and variance of the image blocks are calculated. Finally, chaotic sequence 1 is used for ciphertext feedback encryption of smooth blocks, and chaotic sequence 2 is used for plaintext feedback encryption of complex blocks. So, the encrypted image is obtained. The RBF network is used to predict the chaotic sequence, and the predictive key stream is obtained. Experiment results show that the proposed algorithm has high encryption efficiency, and the encryption speed is about 1 time higher than that of the existing methods. The new algorithm is suitable for real-time encryption of medical images with large amount of data.
    Keywords: atrial fibrillation medical image encryption; 2D sine logistic chaos system; deep learning; adaptive block; RBF neural network.
    DOI: 10.1504/IJCNDS.2023.10052828