Affiliations: [a] Department of Computer Science and Engineering, Excel Engineering College, Namakkal, Tamilnadu, India
| [b] Department of Information Technology, Kongunadu College of and Engineering and Technology, Thollupatti, Tiruchirappali, Tamilnadu, India
| [c] Department of Computer Science and Engineering, Knowledge Institute of Technology, Salem, Tamilnadu, India
Correspondence:
[*]
Corresponding author. P. Vijayalakshmi, Associate Professor, Department of Computer Science and Engineering, Knowledge Institute of Technology, Salem, Tamilnadu, India. E-mail: viji.vietw@gmail.com.
Abstract: Recent technological advancements have enabled users to conduct more sophisticated business transactions via Wi-Fi enabled networks. Typically, a compromised access point (CAP) can handle all traffic between a user and an Internet server, thus becoming a serious security hazard. In addition, an attacker can easily control the entire network using the CAP remotely and compromise as many victims as possible to form a botnet. This paper presents a hybrid recommendation prediction model for forecasting CAP attacks based on network traffic in a private network. This model combines various prediction techniques likethe time-series model, the kNN model and cross association algorithm for attack prediction. This hybrid blacklisting recommendation system effectively improves the prediction rate significantly as well as the robustness against poisoning attacks.
Keywords: Access point, hybrid model, prediction model, recommendation system, security
