Biblio

As the configuration used for the Mobile Ad hoc Networks (MANET) does not have a fixed infrastructure as well, the mechanism varies for each MANET. The finding of the route in this mechanism also varies because it does not have any fixed path route for routing as well every node in this structure behaves like a base station. MANET has such freedom for its creation, so it also faces various types of attacks on it. Some of the attacks are a black hole, warm hole etc. The researchers have provided various methods to prevent warm hole attacks, as the warm hole attack is seen as difficult to prevent. So here a mechanism is proposed to detect and prevent the warm hole attack using the AODV protocol which is based on trust calculation. In our method, the multiple path selection is used for finding the best path for routing. The path is tested for the warm hole attack, as the node is detected the data packet sent in between the source and destination selects the path from the multi-paths available and the packet delivery is improved. The packet delivery ratio (PDR) is calculated for the proposed mechanism, and the results have improved the PDR by 71.25%, throughput by 74.09 kbps, and the E to E delay is decreased by 57.92ms for the network of 125 nodes.

Internet of Things (IoT) is an emerging paradigm in information technology (IT) that integrates advancements in sensing, computing and communication to offer enhanced services in everyday life. IoTs are vulnerable to sybil attacks wherein an adversary fabricates fictitious identities or steals the identities of legitimate nodes. In this paper, we model sybil attacks in IoT and evaluate its impact on performance. We also develop a defense mechanism based on behavioural profiling of nodes. We develop an enhanced AODV (EAODV) protocol by using the behaviour approach to obtain the optimal routes. In EAODV, the routes are selected based on the trust value and hop count. Sybil nodes are identified and discarded based on the feedback from neighbouring nodes. Evaluation of our protocol in ns-2 simulator demonstrates the effectiveness of our approach in identifying and detecting sybil nodes in IoT network.