Detection of Insider Attacks by Using Trust Value in Decentralized Disruption-Tolerant Military Networks

Disruption-tolerant network (DTN) technologies are becoming successful solutions that allow nodes to communicate with each other in these extreme networking environments. Some of the most challenging issues in this scenario are the enforcement of authorization policies and the policies update for secure data retrieval. The concept of attribute-based encryption (ABE) is a promising approach that fulfills the requirements for secure data retrieval in DTNs. So, in the existing system cipher text-policy attributebased encryption (CP-ABE) is presented which provides a scalable way of encrypting data such that the encryptor defines the attribute set that the decryptor needs to possess in order to decrypt the cipher text. However, the problem of applying CP-ABE in decentralized DTNs introduces several security and privacy challenges with regard to the attribute revocation, key escrow, and coordination of attributes issued from different authorities. So, a secure data retrieval scheme is presented using CP-ABE for decentralized DTNs where multiple key authorities manage their attributes independently. But the drawback is updating attributes is not so efficient and high complexity. So, in the proposed system a new technique is introduced which is called Efficient Trust management system (ETMS) for reducing complexity and improving the security. Also, the geographical routing is used to find the location of the nodes. In this method, each node evaluates other nodes in the same subtask group while each subtask group leader (SGL) evaluates other SGLs and nodes in its subtask group. The peer-to-peer trust evaluation is periodically updated based on either direct observations or indirect observations. An experimental result shows that the proposed ETMS method achieves high efficiency and security and less complexity.