LGTBIDS: Layer-wise Graph Theory Based Intrusion Detection System in Beyond 5G

The advancement in wireless communication technologies is becoming more demanding and pervasive. One of the fundamental parameters that limit the efficiency of the network are the security challenges. The communication network is vulnerable to security attacks such as spoofing attacks and signal strength attacks. Intrusion detection signifies a central approach to ensuring the security of the communication network. In this paper, an Intrusion Detection System based on the framework of graph theory is proposed. A Layerwise Graph Theory-Based Intrusion Detection System (LGTBIDS) algorithm is designed to detect the attacked node. The algorithm performs the layer-wise analysis to extract the vulnerable nodes and ultimately the attacked node(s). For each layer, every node is scanned for the possibility of susceptible node(s). The strategy of the IDS is based on the analysis of energy efficiency and secrecy rate. The nodes with the energy efficiency and secrecy rate beyond the range of upper and lower thresholds are detected as the nodes under attack. Further, detected node(s) are transmitted with a random sequence of bits followed by the process of re-authentication. The obtained results validate the better performance, low time computations, and low complexity. Finally, the proposed approach is compared with the conventional solution of intrusion detection.Comment: in IEEE Transactions on Network and Service Management, 202

Intrusion detection based on k-coverage in mobile sensor networks with empowered intruders

Intrusion detection is one of the important applications of Wireless Sensor Networks (WSNs). Prior research indicated that the barrier coverage method combined with Mobile Sensor Networks (MSNs) can enhance the effectiveness of intrusion detection by mitigating coverage holes commonly appeared in stationary WSNs. However, the trajectories of moving sensors and moving intruders have not been investigated thoroughly, where the impact between two adjacent moving sensors and between a moving sensor and a moving intruder are still underdetermined. In order to address these open problems, in this paper, we firstly discuss the virtual potential field between sensors as well as between sensors and intruders. We then propose to formulate the mobility pattern of sensor node using elastic collision model and that of intruder using point charge model. The point charge model describes an hitherto-unexplored mobility pattern of empowered-intruders, which are capable of acting upon the virtual repulsive forces from sensors in order to hide them away from being detected. With the aid of the two models developed, analytical expressions and simulation results demonstrate that our proposed design achieves a higher k -barrier coverage probability in intrusion detection when compared to that of the conventional designs. It is also worth mentioning that these improvements are achieved with shorter average displacement distance and under the much more challenging MSNs settings.</p