Evidentiary assessment for protecting WSNs from internal attacks in real-time

Wireless sensor networks (WSNs) are becoming a vital role in our current modern life for detecting and collecting data about a natural or built environment, including human body. One of the reasons is due to WSNs have very attractive advantages. But one of the problems is internal attacks that have gained prominence and posed most challenging threats to all WSNs. In this paper, we extend our discussion at the conference of the AISC 2016 to an effective algorithm to make an evaluation for detecting internal attack by evidentiary assessment for protecting a WSN from the internal attacks with multi-criteria in real-time. This protecting is based on the combination of the multiple pieces of evidences collected from the nodes suffering from an internal attacker in a network. A decision made is carefully discussed based on the Dempster–Shafer Theory (DST). One of the advantages of this proposed method is that it is not just making a performance in real-time but also it is effective due to it does not need the knowledge about the normal or malicious node in advance with very high average accuracy that is close to 100%.