Affiliations: [a]
Department of Information Technology, Annamalai University, Tamilnadu, India
| [b]
Department of Computer Science & Engineering, Panimalar Engineering College, Chennai, Tamilnadu, India
Correspondence:
[*]
Corresponding author. M.Mohan, Research Scholar, Department of Information Technology, Annamalai University, Tamil Nadu, India. E-mail: [email protected].
Abstract: Cloud computing is a new technology that provides services to customers anywhere, anytime, under varying conditions and managed by a third-party cloud provider. Even though cloud computing has progressed a lot, some attacks still happen. The recent anomalous and signature attacks use clever strategies such as low-rate attacks and attacking as an authenticated user. In this paper, a novel Attack Detection and Prevention (ADAPT) method is proposed to overcome this issue. The proposed system consists of three stages. An Intrusion Detection System is initially used to check whether there is an attack or not by comparing the IP address in the Blacklist IP Database. If an attack occurs, the IP address will be added to the Blacklist IP database and blocked. The second stage uses Bi-directional LSTM and Bi-directional GRU to check the anomalous and signature attack. In the third stage, classified output is sent to reinforcement learning, if any attack occurs the IP address is added to the blacklist IP database otherwise the packets are forwarded to the user. The proposed ADAPT technique achieves a higher accuracy range than existing techniques.
Keywords: Cloud computing, Bi-directional LSTM, Bi-directional GRU, IP address, and reinforcement learning
