Abstract
Delay in long network transmission is a major challenge for lossless connection, Delay Tolerant Networks (DTN) are designed to overcome the same. Due to the limited connectivity, DTN are exposed towards Blackhole and GrayHole attacks with intentionally dropping a segment of data under transmission towards the receiver node. In this paper, a Statistical-based Detection for GrayHole and BlackHole attackers(SbDGB) is addressed with an collision attack detection and individual attack detection under dual mode verification and justification technique. Simulation shows that, SbDGB can be appended over various dropping probabilities and various attackers rate per collision with higher accuracy of detection and alerting rate with lower false positive predictions.
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