Wireless sensor networks (WSNs) as an emerging technology face numerous challenges. Sensor nodes are usually resources constrained,also, they are vulnerable to physical attacks or node compromises. Autonomic Computing is a steadily emerging and promising research field. In the domain of simplifying interoperability, it aims to diminish the management complexity in several industries and systems. Self-protection in WSNshasn't been deeply studied before, because ofthe high rate of fails. The major concern in WSN is to maximize the network's Lifetime.In this paper,a framework that embeds autonomic capabilities into WSN systems is proposed. The proposed framework provides self-protection features in cases of unauthorized, inadvertent and intentional change in security parameters.
The increased deployment of ubiquitous wireless sensor (WSN) networks has exponentially increased the complexity to detect wireless sensor network attacks and protect against them. Wormhole and hello flood attacks can destabilize or disable wireless sensor networks. In a typical wormhole attack, the attacker receives packets at one point in the network, forwards them through a wired or wireless link with less latency than the network links, and relays them to another point in the network. Hello flood attack is an important attack on the network layer, in which an adversary, which is not a legal node in the network, can flood hello request to any legitimate node using high transmission power and break the security of WSNs. This paper describes detection algorithms for wireless sensor networks, which detects wormholes and hello flood attacks based on the packet flow rate to base station node in the network. Simulation results show that the algorithms have low false toleration and false detection rates and small time to detect attacks.
Keywords:Wireless sensor network, packet flow, cluster topology, wormhole attack, hello flood attack.
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