Abstract
DDoS has evolved as most common and devastating attack that has been confronted from previous years. Since hundreds and thousands of network replies, mostly RREP work together simultaneously to accomplish DDoS attack. Thus, no information system can tolerate and survive once they confront this ruthless attack and there are many existing intrusion detection systems to prevent and protect system as well as network from DDoS but still DDoS is still complex to detect and perplexing. In this research article, we have developed an IDS based on basics of latency and delays in neural networks. In order to form a multi-layer architecture, every node is kept on surveillance once the detectors are deployed in the network topology and the activities of every single node is tracked by their close hop nodes mutually to ensure their status of survival. Only after all of the information is collected in a table is forwarded for integrated analysis by their selected expert module. The nodes covered in first and second layer of firewall experience some suspected packets or streams as that of DDoS pattern and the core expert module that started right after the 2nd firewall will take some effective action and invoke the defense module to ensure the safety of the information system. And the nodes which didn't stood against defense module will be isolated first and rebooted later to ensure the normal functionality of the network. (C) 2017 The Authors. Published by IASE.