Pub Date : 2023-01-01DOI: 10.22247/ijcna/2023/218508
G. S. Kumar, G. Sahu, Mayank Mathur
– In today’s realm, Wireless Sensor Network (WSN) has been emerged as a prominent research topic due to the advances in the design of small and low cost sensors for an extensive sort of applications. A battery powers the sensor nodes that make up the WSNs. The restricted quantity of electricity available within WSN nodes is considered as one of the important research issues. Researchers have offered a variety of proposals from various angles to maximize the use of energy resources. Clustering nodes has shown to be one of the most effective ways for WSNs to save energy. The traditional Salp Swarm Algorithm (SSA) has a slow convergence rate and local optima stagnation, and thus produces disappointing results on higher-dimensional issues. Convergence inefficiency is caused by SSA's lack of exploration and exploitation. Improvements to the original population update method are made in this study, and a Modified Salp Swarm Algorithm (MSSA) is provided for achieving energy stability and sustaining network life time through effective cluster head selection throughout the clustering process. Furthermore, the performance of MSSA is validated and equated to other start-of-the art optimization algorithms under different WSN deployments. The suggested model outperforms competing algorithms in terms of sustained operation time, longevity of the network, and total energy consumption, as shown by the simulation results.
{"title":"Cluster Head Selection for Energy Balancing in Wireless Sensor Networks Using Modified Salp Swarm Optimization","authors":"G. S. Kumar, G. Sahu, Mayank Mathur","doi":"10.22247/ijcna/2023/218508","DOIUrl":"https://doi.org/10.22247/ijcna/2023/218508","url":null,"abstract":"– In today’s realm, Wireless Sensor Network (WSN) has been emerged as a prominent research topic due to the advances in the design of small and low cost sensors for an extensive sort of applications. A battery powers the sensor nodes that make up the WSNs. The restricted quantity of electricity available within WSN nodes is considered as one of the important research issues. Researchers have offered a variety of proposals from various angles to maximize the use of energy resources. Clustering nodes has shown to be one of the most effective ways for WSNs to save energy. The traditional Salp Swarm Algorithm (SSA) has a slow convergence rate and local optima stagnation, and thus produces disappointing results on higher-dimensional issues. Convergence inefficiency is caused by SSA's lack of exploration and exploitation. Improvements to the original population update method are made in this study, and a Modified Salp Swarm Algorithm (MSSA) is provided for achieving energy stability and sustaining network life time through effective cluster head selection throughout the clustering process. Furthermore, the performance of MSSA is validated and equated to other start-of-the art optimization algorithms under different WSN deployments. The suggested model outperforms competing algorithms in terms of sustained operation time, longevity of the network, and total energy consumption, as shown by the simulation results.","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42023817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.22247/ijcna/2023/218513
Divya K.S, Roopashree H.R, Yogeesh A.C
– Multiparty computation is essential in offering a better form of non-repudiation, which is not much explored in past research work. A review of existing non-repudiation-based approaches found various shortcomings that do not offer a good balance between robust security and algorithm efficiency. Therefore, the proposed study presents a novel yet simple multiparty computation framework to ensure a higher degree of non-repudiation considering a use-case of a highly distributed and large network, i.e., Internet-of-Things (IoT). The study implements a unique encryption mechanism that uses a transformation strategy to perform encoding while using split key management to retain maximal secrecy and multiparty authentication for enhanced security. The simulation outcome of the study showcases that the proposed scheme offers approximately a 48% reduction in computation overhead, 54% minimization in delay, and 58% faster processing in contrast to frequently reported non-repudiation schemes.
{"title":"Framework of Multiparty Computation for Higher Non-Repudiation in Internet-of-Things (IoT)","authors":"Divya K.S, Roopashree H.R, Yogeesh A.C","doi":"10.22247/ijcna/2023/218513","DOIUrl":"https://doi.org/10.22247/ijcna/2023/218513","url":null,"abstract":"– Multiparty computation is essential in offering a better form of non-repudiation, which is not much explored in past research work. A review of existing non-repudiation-based approaches found various shortcomings that do not offer a good balance between robust security and algorithm efficiency. Therefore, the proposed study presents a novel yet simple multiparty computation framework to ensure a higher degree of non-repudiation considering a use-case of a highly distributed and large network, i.e., Internet-of-Things (IoT). The study implements a unique encryption mechanism that uses a transformation strategy to perform encoding while using split key management to retain maximal secrecy and multiparty authentication for enhanced security. The simulation outcome of the study showcases that the proposed scheme offers approximately a 48% reduction in computation overhead, 54% minimization in delay, and 58% faster processing in contrast to frequently reported non-repudiation schemes.","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41833975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.22247/ijcna/2023/218512
N. Thrimoorthy, Somashekhara Reddy D, C. R., Soumya Unnikrishnan, Vanitha K
– Wireless Network is one of the Internet-of-Things (IoT) prototypes that come up with monitoring services, therefore, influencing the life of human beings. To ensure efficiency and robustness, Quality-of-Service (QoS) is of the predominant point at issue. Congestion in wireless networks will moreover minimize the anticipated QoS of the related applications. Motivated by this, a novel method called, Ornstein– Uhlenbeck Transition and Cache Obliviousness Neural Adaptive (OUT-CONA) to improve congestion control of wireless mesh networks is presented. Adaptive actor-critic deep reinforcement learning scheme on Ornstein–Uhlenbeck State Transition scheduling model to address handovers during data transmission for IoT-enabled Wireless Networks is first designed. Here, by employing the Ornstein–Uhlenbeck state transition scheduling model, both the advantages of the Gauss and Markov Processes are exploited, therefore reducing the energy consumption involved while performing the transition. Next, in the OUT-CONA method, LSTM is imposed for learning the current state representation. The LSTM with the current state representation achieves the objective of controlling congestion with cache obliviousness. The Cache Obliviousness-based Congestion method is utilized for congestion control with obliviousness caching using coherent shielding among organized as well as disorganized data. Furthermore, the performance of the OUT-CONA method is evaluated and compares the results with the performances of conventional techniques, adaptive aggregation as well as hybrid deep learning. The evaluation of the OUT-CONA congestion control method attains better network using lesser misclassification rate, consumption of energy, delay as well as higher goodput using conventional methods in Wireless Mesh Networks.
{"title":"Ornstein Uhlenbeck Cache Obliviousness Neural Congestion Control in Wireless Network for IOT Data Transmission","authors":"N. Thrimoorthy, Somashekhara Reddy D, C. R., Soumya Unnikrishnan, Vanitha K","doi":"10.22247/ijcna/2023/218512","DOIUrl":"https://doi.org/10.22247/ijcna/2023/218512","url":null,"abstract":"– Wireless Network is one of the Internet-of-Things (IoT) prototypes that come up with monitoring services, therefore, influencing the life of human beings. To ensure efficiency and robustness, Quality-of-Service (QoS) is of the predominant point at issue. Congestion in wireless networks will moreover minimize the anticipated QoS of the related applications. Motivated by this, a novel method called, Ornstein– Uhlenbeck Transition and Cache Obliviousness Neural Adaptive (OUT-CONA) to improve congestion control of wireless mesh networks is presented. Adaptive actor-critic deep reinforcement learning scheme on Ornstein–Uhlenbeck State Transition scheduling model to address handovers during data transmission for IoT-enabled Wireless Networks is first designed. Here, by employing the Ornstein–Uhlenbeck state transition scheduling model, both the advantages of the Gauss and Markov Processes are exploited, therefore reducing the energy consumption involved while performing the transition. Next, in the OUT-CONA method, LSTM is imposed for learning the current state representation. The LSTM with the current state representation achieves the objective of controlling congestion with cache obliviousness. The Cache Obliviousness-based Congestion method is utilized for congestion control with obliviousness caching using coherent shielding among organized as well as disorganized data. Furthermore, the performance of the OUT-CONA method is evaluated and compares the results with the performances of conventional techniques, adaptive aggregation as well as hybrid deep learning. The evaluation of the OUT-CONA congestion control method attains better network using lesser misclassification rate, consumption of energy, delay as well as higher goodput using conventional methods in Wireless Mesh Networks.","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46126228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.22247/ijcna/2023/218510
S. K. Jha, Anil Gupta, Niranjan Panigrahi
– Security attacks on time synchronization services prevent the Wireless Sensor Networks (WSNs) from operating consistently and possibly cause the system to go down entirely. One of the most vulnerable attack types where a node falsely assumes many identities is the Sybil attack. Despite receiving a lot of attention for their simplicity and distributed nature, consensus-based time synchronization (CTS) algorithms in WSN do not exhibit robust behavior when subjected to a Sybil attack. In this context, a message-level Sybil detection mechanism, the Sybil resilient consensus time synchronization protocol (SRCTS), is proposed using a graph-theoretic approach. A novel distributed mechanism based on connected component theory is proposed to detect and filter Sybil messages. The comparison has been shown with Robust and secure Time Synchronization Protocol (RTSP) and Node-identification-based secure time synchronization protocols (NiSTS) for detection and convergence speed. The Sybil message detection rate is improved by 6% as compared to SRCTS vs RTSP and by 14% as compared to SRCTS vs NiSTS. Simulation results exhibit that the SRCTS algorithm is 62% more effective as compared to NiSTS and 45% more efficient than RTSP in terms of convergence rate. An in-depth mathematical analysis is presented to prove the correctness of the algorithms, and the message complexity is proven to be O(n 2 ). The algorithm is validated through extensive simulation results.
{"title":"Resilient Consensus-Based Time Synchronization with Distributed Sybil Attack Detection Strategy for Wireless Sensor Networks: A Graph Theoretic Approach","authors":"S. K. Jha, Anil Gupta, Niranjan Panigrahi","doi":"10.22247/ijcna/2023/218510","DOIUrl":"https://doi.org/10.22247/ijcna/2023/218510","url":null,"abstract":"– Security attacks on time synchronization services prevent the Wireless Sensor Networks (WSNs) from operating consistently and possibly cause the system to go down entirely. One of the most vulnerable attack types where a node falsely assumes many identities is the Sybil attack. Despite receiving a lot of attention for their simplicity and distributed nature, consensus-based time synchronization (CTS) algorithms in WSN do not exhibit robust behavior when subjected to a Sybil attack. In this context, a message-level Sybil detection mechanism, the Sybil resilient consensus time synchronization protocol (SRCTS), is proposed using a graph-theoretic approach. A novel distributed mechanism based on connected component theory is proposed to detect and filter Sybil messages. The comparison has been shown with Robust and secure Time Synchronization Protocol (RTSP) and Node-identification-based secure time synchronization protocols (NiSTS) for detection and convergence speed. The Sybil message detection rate is improved by 6% as compared to SRCTS vs RTSP and by 14% as compared to SRCTS vs NiSTS. Simulation results exhibit that the SRCTS algorithm is 62% more effective as compared to NiSTS and 45% more efficient than RTSP in terms of convergence rate. An in-depth mathematical analysis is presented to prove the correctness of the algorithms, and the message complexity is proven to be O(n 2 ). The algorithm is validated through extensive simulation results.","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41635983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.22247/ijcna/2023/218514
P. Rutravigneshwaran, G. Anitha
– The Internet of Things (IoT) acts an imperative part in the Battlefield Network (BN) for group-based communication. The new technology is called Internet of Battlefield Things (IoBT) that delivers intelligence services on the battlefield to soldiers and commanders equipped with smart devices. Though it provides numerous benefits, it is also susceptible to many attacks, because of the open and remote deployment of Battlefield Things (BTs). It is more critical to provide security in such networks than in commercial IoT applications because they must contend with both IoT networks and tactical battlefield environments. Because of restricted resources, an attacker may compromise the BTs. The BT that has been seized by the adversary is called a malicious BT and it may launch several security attacks on the BN. To identify these malicious BTs, the IoBT network requires a reputation-based trust model. To address the black hole attack or malicious attack over Routing Protocol for Low Power and Lossy Networks (RPL) is a key objective of the proposed work. The proposed work is the combination of both machine learning algorithm and trust management and it is named as KmCtrust model. By removing malicious BTs from the network, only BTs participating in the mission are trusted, which improves mission performance in the IoBT network. The simulation analysis of KmCtrust model has witnessed the better results in terms of various performance
{"title":"Security Model to Mitigate Black Hole Attack on Internet of Battlefield Things (IoBT) Using Trust and K-Means Clustering Algorithm","authors":"P. Rutravigneshwaran, G. Anitha","doi":"10.22247/ijcna/2023/218514","DOIUrl":"https://doi.org/10.22247/ijcna/2023/218514","url":null,"abstract":"– The Internet of Things (IoT) acts an imperative part in the Battlefield Network (BN) for group-based communication. The new technology is called Internet of Battlefield Things (IoBT) that delivers intelligence services on the battlefield to soldiers and commanders equipped with smart devices. Though it provides numerous benefits, it is also susceptible to many attacks, because of the open and remote deployment of Battlefield Things (BTs). It is more critical to provide security in such networks than in commercial IoT applications because they must contend with both IoT networks and tactical battlefield environments. Because of restricted resources, an attacker may compromise the BTs. The BT that has been seized by the adversary is called a malicious BT and it may launch several security attacks on the BN. To identify these malicious BTs, the IoBT network requires a reputation-based trust model. To address the black hole attack or malicious attack over Routing Protocol for Low Power and Lossy Networks (RPL) is a key objective of the proposed work. The proposed work is the combination of both machine learning algorithm and trust management and it is named as KmCtrust model. By removing malicious BTs from the network, only BTs participating in the mission are trusted, which improves mission performance in the IoBT network. The simulation analysis of KmCtrust model has witnessed the better results in terms of various performance","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68278489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.22247/ijcna/2023/218515
G. S. Rapate, N. Naveen
– Resource management in the 5G network is one of the critical concerns which is increasingly seeking attention from the research community; however, a review of existing literature showcases very less usage of scheduling and more inclination towards sophisticated approaches of resource management which are practically infeasible to be executed over resource-constrained devices over Internet-of-Things (IoT). Therefore, the proposed scheme presents a unique framework for effective resource management in a 5G network using a unique scheduling approach. The system executes a novel routine management of time slots considering operational time and transition states of IoT nodes to balance the state of active and passive radio mode operation. The simulated outcome of the study shows that the proposed scheme offers approximately 35% of more residual energy, 47% of reduced energy dissipation, 25% of reduced delay, and 43% of faster processing speed in contrast to existing scheduling schemes in the IoT environment.
{"title":"Scheduling Framework for Resource Management in IoT Ecosystem Over 5G Network","authors":"G. S. Rapate, N. Naveen","doi":"10.22247/ijcna/2023/218515","DOIUrl":"https://doi.org/10.22247/ijcna/2023/218515","url":null,"abstract":"– Resource management in the 5G network is one of the critical concerns which is increasingly seeking attention from the research community; however, a review of existing literature showcases very less usage of scheduling and more inclination towards sophisticated approaches of resource management which are practically infeasible to be executed over resource-constrained devices over Internet-of-Things (IoT). Therefore, the proposed scheme presents a unique framework for effective resource management in a 5G network using a unique scheduling approach. The system executes a novel routine management of time slots considering operational time and transition states of IoT nodes to balance the state of active and passive radio mode operation. The simulated outcome of the study shows that the proposed scheme offers approximately 35% of more residual energy, 47% of reduced energy dissipation, 25% of reduced delay, and 43% of faster processing speed in contrast to existing scheduling schemes in the IoT environment.","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46475279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
– Wireless Sensor Networks (WSN) are under attack from insider packet drops. Each node will employ a trust mechanism to assess the trustworthiness of its neighbor nodes to send packets to only the trustworthy neighbors to distinguish packets dropped by inside intruders from network faults. The false alert arises when a normal node's trust value decreases and is removed from the routing paths using trust-aware routing algorithms. Optimizing the packet delivery ratio is a critical design consideration for WSNs. WSNs have long benefited from a secure zone-based routing mechanism already in place. A new routing criterion was developed for packet transfer in multi-hop communication. The routing metric was designed to protect against message manipulation, dropping, and flooding assaults. The method used an alternative way to route a packet while avoiding dangerous zones safely and efficiently in the routing process. Despite energy conservation and greater attack resilience, congestion in the WSN has increased, and the packet delivery ratio has been reduced. Each node has computing power that serves as a transceiver for the network. A packet-dropping node is hacked and forwards any or all the packets it receives. All or some boxes are packages modified by a hacked node that is intended to deliver them. In multi-hop sensor networks, packet dropping and alteration are two popular methods that an adversary can use to interrupt communication. The proposed model NDTRA-MAT is used to avoid packet loss with reduced false alarms. It is compared with the existing models, and the performance is calculated in terms of Malicious Node Detection Accuracy Levels
{"title":"NDTRA-MAT: A Novel Technique for Evaluating the Data Transfer Rate, Reducing the False Alarm Rate, and avoiding Packet Droppings Rate against Malicious Activity in Wireless Sensor Networks","authors":"Minakshi Sahu, Nilambar Sethi, Susant Kumar Das, Umashankar Ghugar","doi":"10.22247/ijcna/2023/218507","DOIUrl":"https://doi.org/10.22247/ijcna/2023/218507","url":null,"abstract":"– Wireless Sensor Networks (WSN) are under attack from insider packet drops. Each node will employ a trust mechanism to assess the trustworthiness of its neighbor nodes to send packets to only the trustworthy neighbors to distinguish packets dropped by inside intruders from network faults. The false alert arises when a normal node's trust value decreases and is removed from the routing paths using trust-aware routing algorithms. Optimizing the packet delivery ratio is a critical design consideration for WSNs. WSNs have long benefited from a secure zone-based routing mechanism already in place. A new routing criterion was developed for packet transfer in multi-hop communication. The routing metric was designed to protect against message manipulation, dropping, and flooding assaults. The method used an alternative way to route a packet while avoiding dangerous zones safely and efficiently in the routing process. Despite energy conservation and greater attack resilience, congestion in the WSN has increased, and the packet delivery ratio has been reduced. Each node has computing power that serves as a transceiver for the network. A packet-dropping node is hacked and forwards any or all the packets it receives. All or some boxes are packages modified by a hacked node that is intended to deliver them. In multi-hop sensor networks, packet dropping and alteration are two popular methods that an adversary can use to interrupt communication. The proposed model NDTRA-MAT is used to avoid packet loss with reduced false alarms. It is compared with the existing models, and the performance is calculated in terms of Malicious Node Detection Accuracy Levels","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41664421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.22247/ijcna/2023/218509
G. Shrivastava, Sachin Patel
– The storage of a vast quantity of data in the cloud, which is then delivered via the internet, enables Cloud Computing to make doing business easier by providing smooth access to the data and eliminating device compatibility limits. Data that is in transit, on the other hand, may be intercepted by a man-in-the-middle attack, a known plain text assault, a selected cypher text attack, a related key attack, or a pollution attack. Uploading data to a single cloud might, as a result, increase the likelihood that the secret data would be damaged. A distributed file system extensively used in huge data analysis for frameworks such as Hadoop is known as the Hadoop Distributed File System, more commonly referred to as HDFS. Because with HDFS, it is possible to manage enormous volumes of data while using standard hardware that is not very costly. On the other hand, HDFS has several security flaws that might be used for malicious purposes. This highlights how critical it is to implement stringent security measures to make it easier for users to share files inside Hadoop and to have a reliable system in place to validate the shared files' validity claims. The major focus of this article is to discuss our efforts to improve the security of HDFS by using an approach made possible by blockchain technology (hereafter referred to as BlockHDFS). To be more precise, the proposed BlockHDFS uses the Hyperledger Fabric platform, which was developed for business applications, to extract the most value possible from the data inside files to provide reliable data protection and traceability in HDFS. In the results section, the performance of AES is superior to that of other encryption algorithms because it ranges from 1.2 milliseconds to 1.9 milliseconds. In contrast, DES ranges from 1.3 milliseconds to 3.1 milliseconds, three milliseconds to 3.6 millimetres, RC2 milliseconds to 3.9 milliseconds, and RSA milliseconds to 1.4 milliseconds, with data sizes ranging from 910 kilos.
{"title":"Secure Storage and Data Sharing Scheme Using Private Blockchain-Based HDFS Data Storage for Cloud Computing","authors":"G. Shrivastava, Sachin Patel","doi":"10.22247/ijcna/2023/218509","DOIUrl":"https://doi.org/10.22247/ijcna/2023/218509","url":null,"abstract":"– The storage of a vast quantity of data in the cloud, which is then delivered via the internet, enables Cloud Computing to make doing business easier by providing smooth access to the data and eliminating device compatibility limits. Data that is in transit, on the other hand, may be intercepted by a man-in-the-middle attack, a known plain text assault, a selected cypher text attack, a related key attack, or a pollution attack. Uploading data to a single cloud might, as a result, increase the likelihood that the secret data would be damaged. A distributed file system extensively used in huge data analysis for frameworks such as Hadoop is known as the Hadoop Distributed File System, more commonly referred to as HDFS. Because with HDFS, it is possible to manage enormous volumes of data while using standard hardware that is not very costly. On the other hand, HDFS has several security flaws that might be used for malicious purposes. This highlights how critical it is to implement stringent security measures to make it easier for users to share files inside Hadoop and to have a reliable system in place to validate the shared files' validity claims. The major focus of this article is to discuss our efforts to improve the security of HDFS by using an approach made possible by blockchain technology (hereafter referred to as BlockHDFS). To be more precise, the proposed BlockHDFS uses the Hyperledger Fabric platform, which was developed for business applications, to extract the most value possible from the data inside files to provide reliable data protection and traceability in HDFS. In the results section, the performance of AES is superior to that of other encryption algorithms because it ranges from 1.2 milliseconds to 1.9 milliseconds. In contrast, DES ranges from 1.3 milliseconds to 3.1 milliseconds, three milliseconds to 3.6 millimetres, RC2 milliseconds to 3.9 milliseconds, and RSA milliseconds to 1.4 milliseconds, with data sizes ranging from 910 kilos.","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42147348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.22247/ijcna/2023/218511
Chinnu Mary, Gayathri K M, Reeja S R
– Wireless sensor networks (WSN) are utilized in various application domains concerning monitoring and smart application, in which highly sensitive information in healthcare and military applications is also employed using the WSN. The openness and unattended nature of the WSN make security as a challenging task. The information eavesdropping is employed by the network intruder from the source node; hence the location of the source node needs to be protected for the acquisition of information security. Thus, this research introduces a privacy preservation of the source location method using the hybrid optimization based secure routing. For this, Shuffled Shepherd-Coot (SS-Coot) optimization is proposed by hybridizing the foraging behavior of the Coot, a water bird, with the shepherd's behavior in herding the animal community. The incorporation of the herding behavior of the shepherd with Coot's foraging behavior helps to enhance the diversification phase to obtain the best solution by avoiding premature convergence. In the proposed source location privacy preservation, the network boundary radiuses are obtained optimally using the SS-Coot algorithm during the network initialization. Then, the routing through the various boundaries of the network with multi-hop helps to protect the location of the source by confusing the intruder's backtrace process. The analysis is performed based on Packet Delivery Ratio (PDR), throughput, energy consumption, and delivery latency and obtained the values of 1.02867, 1.02909, 0.30171, and 0.00165, respectively.
{"title":"Hybrid Optimization Enabled Routing Protocol for Enhancing Source Location Privacy in Wireless Sensor Networks","authors":"Chinnu Mary, Gayathri K M, Reeja S R","doi":"10.22247/ijcna/2023/218511","DOIUrl":"https://doi.org/10.22247/ijcna/2023/218511","url":null,"abstract":"– Wireless sensor networks (WSN) are utilized in various application domains concerning monitoring and smart application, in which highly sensitive information in healthcare and military applications is also employed using the WSN. The openness and unattended nature of the WSN make security as a challenging task. The information eavesdropping is employed by the network intruder from the source node; hence the location of the source node needs to be protected for the acquisition of information security. Thus, this research introduces a privacy preservation of the source location method using the hybrid optimization based secure routing. For this, Shuffled Shepherd-Coot (SS-Coot) optimization is proposed by hybridizing the foraging behavior of the Coot, a water bird, with the shepherd's behavior in herding the animal community. The incorporation of the herding behavior of the shepherd with Coot's foraging behavior helps to enhance the diversification phase to obtain the best solution by avoiding premature convergence. In the proposed source location privacy preservation, the network boundary radiuses are obtained optimally using the SS-Coot algorithm during the network initialization. Then, the routing through the various boundaries of the network with multi-hop helps to protect the location of the source by confusing the intruder's backtrace process. The analysis is performed based on Packet Delivery Ratio (PDR), throughput, energy consumption, and delivery latency and obtained the values of 1.02867, 1.02909, 0.30171, and 0.00165, respectively.","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41451303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.22247/ijcna/2023/218518
S. Kumaresh
– Intelligent Transportation System (ITS) with the internet of things (IoT) plays an integral role in smart city developments and enables substantial developments in modern human lifestyles. With the emergence of Fifth-Generation (5G) communication technologies, high-speed communications are enabled among multiple internet-connected devices. However, security, reliability, and scalability are significant factors that affect the communication performance of ITS. The conventional security models are mostly centralized and unsuitable for distributed low-powered IoT-enabled 5G ITS. The new-age distributed ledger technology blockchain can improve the security and reliability of ITS services. Therefore, this paper investigates a blockchain-based security mechanism, Blockchain-based Secure IoT Communication (BSIC), that protects the 5G-ITS from potential security threats. The BSIC utilizes a consortium blockchain model with Improved Proof of Reputation (IPoR) to achieve its objectives. It handles the resource limitation issues of IoT by integrating Vehicular Edge Computing (VEC) services. Further, the BSIC design includes two main components: reputation computation strategy and the IPoR mining process. The proposed model successfully builds a secure IoT communication system by integrating multi-criteria factors in subjective logic-based reputation estimation. It selects the miners by adjusting the consensus pool size according to network density and reputation and improves the consensus efficiency with minimum delay. Moreover, the experimental evaluations are carried out to analyze the efficiency of BSIC using performance metrics such as attack detection rate, consensus delay, and reputation estimation accuracy.
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