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There has been a tremendous growth in the use of wireless communication in the past few decades. Mobile Ad hoc NETwork (MANET) is one of the most important one among various wireless communication mechanisms. In MANET, each node in a network performs as both a transmitter and a receiver. They rely on each other to store and forward packets. Its unique infrastructureless network and self-configuring capability makes it ideal for many mission critical applications, including military use and remote exploration. However, these characteristics also make MANET vulnerable to passive and active attacks due to its open medium, changing topology and lack of centralized monitoring. To address the new security challenges, Intrusion Detection System (IDS) is required to detect the malicious attackers before they can accomplish any significant damages to the network. Many existing IDSs for MANETs are based upon Watchdog mechanism. In this paper, we propose a new IDS called Enhanced Adaptive ACKnowledgement (EAACK) that solves four significant problems of Watchdog mechanism, which are ambiguous collisions, receiver collisions, limited transmission power and false misbehavior report. We use Network Simulator 2 to simulate the proposed mechanism and compare the results with existing mechanisms.

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Nowadays, wireless sensor networks are deployed in a wide range of applications such as military. To enable sinks to avoid physical attacks from adversaries, most of WSNs adopt sink-location privacy mechanisms. By utilizing these mechanisms, an adversary cannot analyze packet traffic and perform hop-byhop trace-back, and thus deduce the location of a sink. In this paper, we propose an attack approach to track anonymous sinks. It utilizes a Pseudo-Noise (PN) code to mark a data flow in an invisible manner. An adversary is able to interfere with a source node's traffic by embedding a secure signal into the node's traffic. The signal is carried along with the traffic from the source node to the sink. Therefore, the attacker can recognize the location of a sink node by tracking the invisible secure signal. Through our simulation experiments, we conclude that the proposed attack approach is able to track an anonymous sink without additional traffic overhead.

No abstract