A Lightweight Anomaly Detection System for Black Hole Attack

Mobile ad hoc networks (MANETs) are now key in today’s new world. They critically needed many situations when it is crucial to form a network on the fly while not having luxury of time or resources configure devices, build infrastructure, even have human interventions. Ad applications. For instance, they can be used battlefields, education, rescue missions, and other Such characterized by high mobility, low power, storage, processing. infrastructure-less; this means that don’t use infrastructure equipment for communication. These rely instead each routing MANETs hopping mechanism where node finds another within its communication range as hop delivering message through so on. In standard networks, there dedicated specific functions such routers, servers, firewalls, etc., every performs multiple functions. example, function performed nodes. Hence, more vulnerable attacks than networks. The main goal paper propose solution detecting black hole using anomaly detection based support vector machine (SVM). This system aims at analyzing traffic identifying anomalies checking behaviors. case attacks, attacking nodes some behavioral characteristics different from normal effectively detected our lightweight system. To experiment with effectiveness solution, an OMNET++ simulator generate under attack. then classified into malicious non-malicious which identified. results proposed showed very accuracy attacks.