Nodes in a mobile computing system are vulnerable to clone attacks due to their mobility.In such attacks,an adversary accesses a few network nodes,generates replication,then inserts this replication into the network,p...Nodes in a mobile computing system are vulnerable to clone attacks due to their mobility.In such attacks,an adversary accesses a few network nodes,generates replication,then inserts this replication into the network,potentially resulting in numerous internal network attacks.Most existing techniques use a central base station,which introduces several difficulties into the system due to the network’s reliance on a single point,while other ways generate more overhead while jeopardising network lifetime.In this research,an intelligent double hashing-based clone node identification scheme was used,which reduces communication and memory costs while performing the clone detection procedure.The approach works in two stages:in the first,the network is deployed using an intelligent double hashing procedure to avoid any network collisions and then in the second,the clone node identification procedure searches for any clone node in the network.This first phase verifies the node prior to network deployment,and then,whenever a node wants to interact,it executes the second level of authentication.End-to-end delay,which is bound to increase owing to the injection of clone nodes,and packet loss,which is reduced by the double hashing technique,were used to evaluate the performance of the aforementioned approach.展开更多
Wireless Sensor Network(WSN)is a distributed sensor network composed a large number of nodes with low cost,low performance and self-management.The special structure of WSN brings both convenience and vulnerability.For...Wireless Sensor Network(WSN)is a distributed sensor network composed a large number of nodes with low cost,low performance and self-management.The special structure of WSN brings both convenience and vulnerability.For example,a malicious participant can launch attacks by capturing a physical device.Therefore,node authentication that can resist malicious attacks is very important to network security.Recently,blockchain technology has shown the potential to enhance the security of the Internet of Things(IoT).In this paper,we propose a Blockchain-empowered Authentication Scheme(BAS)for WSN.In our scheme,all nodes are managed by utilizing the identity information stored on the blockchain.Besides,the simulation experiment about worm detection is executed on BAS,and the security is evaluated from detection and infection rate.The experiment results indicate that the proposed scheme can effectively inhibit the spread and infection of worms in the network.展开更多
Internet of Things(IoT)network used for industrial management is vulnerable to different security threats due to its unstructured deployment,and dynamic communication behavior.In literature various mechanisms addresse...Internet of Things(IoT)network used for industrial management is vulnerable to different security threats due to its unstructured deployment,and dynamic communication behavior.In literature various mechanisms addressed the security issue of Industrial IoT networks,but proper maintenance of the performance reliability is among the common challenges.In this paper,we proposed an intelligent mutual authentication scheme leveraging authentication aware node(AAN)and base station(BS)to identify routing attacks in Industrial IoT networks.The AAN and BS uses the communication parameter such as a route request(RREQ),node-ID,received signal strength(RSS),and round-trip time(RTT)information to identify malicious devices and routes in the deployed network.The feasibility of the proposed model is validated in the simulation environment,where OMNeT++was used as a simulation tool.We compare the results of the proposed model with existing field-proven schemes in terms of routing attacks detection,communication cost,latency,computational cost,and throughput.The results show that our proposed scheme surpasses the previous schemes regarding these performance parameters with the attack detection rate of 97.7%.展开更多
文摘Nodes in a mobile computing system are vulnerable to clone attacks due to their mobility.In such attacks,an adversary accesses a few network nodes,generates replication,then inserts this replication into the network,potentially resulting in numerous internal network attacks.Most existing techniques use a central base station,which introduces several difficulties into the system due to the network’s reliance on a single point,while other ways generate more overhead while jeopardising network lifetime.In this research,an intelligent double hashing-based clone node identification scheme was used,which reduces communication and memory costs while performing the clone detection procedure.The approach works in two stages:in the first,the network is deployed using an intelligent double hashing procedure to avoid any network collisions and then in the second,the clone node identification procedure searches for any clone node in the network.This first phase verifies the node prior to network deployment,and then,whenever a node wants to interact,it executes the second level of authentication.End-to-end delay,which is bound to increase owing to the injection of clone nodes,and packet loss,which is reduced by the double hashing technique,were used to evaluate the performance of the aforementioned approach.
基金supported by the Natural Science Foundation under Grant No.61962009Major Scientific and Technological Special Project of Guizhou Province under Grant No.20183001Foundation of Guizhou Provincial Key Laboratory of Public Big Data under Grant No.2018BDKFJJ003,2018BDKFJJ005 and 2019BDKFJJ009.
文摘Wireless Sensor Network(WSN)is a distributed sensor network composed a large number of nodes with low cost,low performance and self-management.The special structure of WSN brings both convenience and vulnerability.For example,a malicious participant can launch attacks by capturing a physical device.Therefore,node authentication that can resist malicious attacks is very important to network security.Recently,blockchain technology has shown the potential to enhance the security of the Internet of Things(IoT).In this paper,we propose a Blockchain-empowered Authentication Scheme(BAS)for WSN.In our scheme,all nodes are managed by utilizing the identity information stored on the blockchain.Besides,the simulation experiment about worm detection is executed on BAS,and the security is evaluated from detection and infection rate.The experiment results indicate that the proposed scheme can effectively inhibit the spread and infection of worms in the network.
基金supported by the MSIT(Ministry of Science and ICT),Korea under the ITRC(Information Technology Research Center)support program(IITP-2020-2018-0-01426)supervised by IITP(Institute for Information and Communication Technology Planning&Evaluation)+1 种基金in part by the National Research Foundation(NRF)funded by the Korea government(MSIT)(No.2019R1F1A1059125).
文摘Internet of Things(IoT)network used for industrial management is vulnerable to different security threats due to its unstructured deployment,and dynamic communication behavior.In literature various mechanisms addressed the security issue of Industrial IoT networks,but proper maintenance of the performance reliability is among the common challenges.In this paper,we proposed an intelligent mutual authentication scheme leveraging authentication aware node(AAN)and base station(BS)to identify routing attacks in Industrial IoT networks.The AAN and BS uses the communication parameter such as a route request(RREQ),node-ID,received signal strength(RSS),and round-trip time(RTT)information to identify malicious devices and routes in the deployed network.The feasibility of the proposed model is validated in the simulation environment,where OMNeT++was used as a simulation tool.We compare the results of the proposed model with existing field-proven schemes in terms of routing attacks detection,communication cost,latency,computational cost,and throughput.The results show that our proposed scheme surpasses the previous schemes regarding these performance parameters with the attack detection rate of 97.7%.
