Today’s Internet of Things (IoT) application domains are widely distributed, which exposes them to several security risks and assaults, especially when data is being transferred between endpoints with constrained res...Today’s Internet of Things (IoT) application domains are widely distributed, which exposes them to several security risks and assaults, especially when data is being transferred between endpoints with constrained resources and the backbone network. Numerous researchers have put a lot of effort into addressing routing protocol security vulnerabilities, particularly regarding IoT RPL-based networks. Despite multiple studies on the security of IoT routing protocols, routing attacks remain a major focus of ongoing research in IoT contexts. This paper examines the different types of routing attacks, how they affect Internet of Things networks, and how to mitigate them. Then, it provides an overview of recently published work on routing threats, primarily focusing on countermeasures, highlighting noteworthy security contributions, and drawing conclusions. Consequently, it achieves the study’s main objectives by summarizing intriguing current research trends in IoT routing security, pointing out knowledge gaps in this field, and suggesting directions and recommendations for future research on IoT routing security.展开更多
The approach of traffic abnormality detection of network resource allocation attack did not have reliable signatures to depict abnormality and identify them. However, it is crucial for us to detect attacks accurately....The approach of traffic abnormality detection of network resource allocation attack did not have reliable signatures to depict abnormality and identify them. However, it is crucial for us to detect attacks accurately. The technique that we adopted is inspired by long range dependence ideas. We use the number of packet arrivals of a flow in fixed-length time intervals as the signal and attempt to extend traffic invariant “self-similarity”. We validate the effectiveness of the approach with simulation and trace analysis.展开更多
With the rapid integration of communication and information technology into substations,the risk of cyber attacks has significantly increased.Attackers may infiltrate substation networks,manipulate switches,and disrup...With the rapid integration of communication and information technology into substations,the risk of cyber attacks has significantly increased.Attackers may infiltrate substation networks,manipulate switches,and disrupt power lines,potentially causing severe damage to the power system.To minimize such risks,this paper proposes a three-layer defender-attacker-defender(DAD)model for optimally allocating limited defensive resources to substations.To model the uncertainty surrounding the knowledge of defender of potential attacks in realworld scenarios,we employ a fuzzy analytic hierarchy process combined with the decision-making trial and evaluation laboratory(FAHP-DEMATEL).This method accounts for the attack resource uncertainty by utilizing intelligence data on factors potentially influenced by attackers,which serves as an evaluation metric to simulate the likelihood of various attack scenarios.These uncertainty probabilities are then incorporated into the substation DAD model consisting three layers of agents:the decision-maker,the attacker,and the operator.The decision-maker devises a defense strategy before the attack,while the attacker aims to identify the strategy that causes the maximum load loss.Meanwhile,the operator seeks to minimize the load loss through optimal power flow scheduling.To solve the model,the original problem is transformed into a two-layer subproblem and a single-layer master problem,which are solved iteratively using a column-and-constraint generation algorithm.Case studies conducted on the IEEE RTS-96 system and the IEEE 118-node system demonstrate the effectiveness and practicality of the proposed model.Comparative experiments further highlight the advantages of the proposed model.展开更多
文摘Today’s Internet of Things (IoT) application domains are widely distributed, which exposes them to several security risks and assaults, especially when data is being transferred between endpoints with constrained resources and the backbone network. Numerous researchers have put a lot of effort into addressing routing protocol security vulnerabilities, particularly regarding IoT RPL-based networks. Despite multiple studies on the security of IoT routing protocols, routing attacks remain a major focus of ongoing research in IoT contexts. This paper examines the different types of routing attacks, how they affect Internet of Things networks, and how to mitigate them. Then, it provides an overview of recently published work on routing threats, primarily focusing on countermeasures, highlighting noteworthy security contributions, and drawing conclusions. Consequently, it achieves the study’s main objectives by summarizing intriguing current research trends in IoT routing security, pointing out knowledge gaps in this field, and suggesting directions and recommendations for future research on IoT routing security.
文摘The approach of traffic abnormality detection of network resource allocation attack did not have reliable signatures to depict abnormality and identify them. However, it is crucial for us to detect attacks accurately. The technique that we adopted is inspired by long range dependence ideas. We use the number of packet arrivals of a flow in fixed-length time intervals as the signal and attempt to extend traffic invariant “self-similarity”. We validate the effectiveness of the approach with simulation and trace analysis.
基金supported by National Natural Science Foundation of China(No.52377115)。
文摘With the rapid integration of communication and information technology into substations,the risk of cyber attacks has significantly increased.Attackers may infiltrate substation networks,manipulate switches,and disrupt power lines,potentially causing severe damage to the power system.To minimize such risks,this paper proposes a three-layer defender-attacker-defender(DAD)model for optimally allocating limited defensive resources to substations.To model the uncertainty surrounding the knowledge of defender of potential attacks in realworld scenarios,we employ a fuzzy analytic hierarchy process combined with the decision-making trial and evaluation laboratory(FAHP-DEMATEL).This method accounts for the attack resource uncertainty by utilizing intelligence data on factors potentially influenced by attackers,which serves as an evaluation metric to simulate the likelihood of various attack scenarios.These uncertainty probabilities are then incorporated into the substation DAD model consisting three layers of agents:the decision-maker,the attacker,and the operator.The decision-maker devises a defense strategy before the attack,while the attacker aims to identify the strategy that causes the maximum load loss.Meanwhile,the operator seeks to minimize the load loss through optimal power flow scheduling.To solve the model,the original problem is transformed into a two-layer subproblem and a single-layer master problem,which are solved iteratively using a column-and-constraint generation algorithm.Case studies conducted on the IEEE RTS-96 system and the IEEE 118-node system demonstrate the effectiveness and practicality of the proposed model.Comparative experiments further highlight the advantages of the proposed model.
