An analytical Survey of Attack Scenario Parameters on the Techniques of Attack Mitigation in WSN

Wireless sensor networks (WSN) were cataloged as one of the most important emerging technologies of the last century and are considered the basis of the Internet of Things paradigm. However, an undeniable disadvantage of WSN is that the resources available for these types of networks, such as processing capacity, memory, and battery, are usually in short supply. This limitation in resources implements security mechanisms a difficult task. This work reviews 93 recent proposals in which different solutions were formulated for the different attacks in WSN in the network layer; in total, 139 references were considered. According to the literature, these attacks are mainly Sybil, wormhole, sinkhole, and selective forwarding. The main goal of this contribution is to present the evaluation metrics used in the state of the art to mitigate the Sybil, wormhole, sinkhole, and selective forwarding attacks and show the network topologies used in each of these proposals.

En-Route Message Authentication Scheme for Filtering False Data in WSNs

In wireless sensor networks, the adversary can easily control the compromised nodes to inject false data reports. En-route filtering is an effective mechanism to resist such attacks, where the forwarding nodes of the reports can identify and drop the false reports. However, the existing en-route filtering strategies are vulnerable to report disruption attacks and selective forwarding attacks, and the probabilities and efficiencies of en-route filtering false reports are low. To address these problems, a precheck mechanism performed by the CoS (Center-of-Stimulus) node is presented to resist report disruption attacks, a report forwarding strategy with balancing the residual energy of the nodes is designed to resist selective forwarding attacks, and an en-route message authentication scheme (EMAS) based on monitoring and reporting mechanism is proposed to resist false data injection attacks. The theoretical analysis and simulation results show that in most cases, EMAS provides a higher security level and higher en-route filtering probability and efficiency and is very efficient in energy saving.

Black Hole and Selective Forwarding Attack Detection and Prevention in IoT in Health Care Sector: Hybrid meta-heuristic-based shortest path routing

In the current health care scenario, security is the major concern in IoT-WSN with more devices or nodes. Attack or anomaly detection in the IoT infrastructure is increasing distress in the field of medical IoT. With the enormous usage of IoT infrastructure in every province, threats and attacks in these infrastructures are also mounting commensurately. This paper intends to develop a security mechanism to detect and prevent the black hole and selective forwarding attack from medical IoT-WSN. The proposed secure strategy is developed in five stages: First is selecting the cluster heads, second is generating k-routing paths, third is security against black hole attack, fourth is security against the selective forwarding attack, and the last is optimal shortest route path selection. Initially, a topology is developed for finding the cluster heads and discovering the best route. In the next phase, the black hole attacks are detected and prevented by the bait process. For detecting the selective forwarding attacks, the packet validation is done by checking the transmitted packet and the received packet. For promoting the packet security, Elliptic Curve Cryptography (ECC)-based hashing function is deployed. As the main contribution of this paper, optimal shortest route path is determined by the proposed hybrid algorithm with the integration of Deer Hunting Optimization Algorithm (DHOA), and DragonFly Algorithm (DA) termed Dragonfly-based DHOA (D-DHOA) by concerting the parameters like trust, distance, delay or latency and packet loss ratio in the objective model. Hence, the entire phases will be very active in detecting and preventing the two fundamental attacks like a black hole and selective forwarding from IoT-WSN in the health care sector.