A Hybrid Scheme for Malware Detection in Delay Tolerant Networks

Delay tolerant network (DTN) utilize the mobility of node and opportunistic contact among nodes for data communication. Due to limitation in resources such as buffer space and contact opportunity, DTNs are vulnerable to malware based attack. So the proposal introduces a novel malware detection technique in DTN. The proposed system deals with the several evidence matching and collection problems. The system also identifies the misbehaving nodes by collecting and validating their evidence using ECDSA. The signature and Behavioral analysis of every node along with the evidence collection helps to track the accurate malware in DTN. The proposed system uses a hybrid collaborative malware detection technique to improve the detection accuracy.