Cloud security based attack detection using transductive learning integrated with Hidden Markov Model
Hidden Markov Model (HMM); K-medoids clustering; Soft labels; Transductive deep learning; Zero-day attack security
In recent years, organizations and enterprises put huge attention on their network security. The attackers were able to influence vulnerabilities for the configuration of the network through the network. Zero-day (0-day) is defined as vulnerable software or application that is either defined by the vendor or not patched by any vendor of organization. When zero-day attack is identified within the network there is no proper mechanism when observed. To mitigate challenges related to the zero-day attack, this paper presented HMM_TDL, a deep learning model for detection and prevention of attack in the cloud platform. The presented model is carried out in three phases like at first, Hidden Markov Model (HMM) is incorporated for the detection of attacks. With the derived HMM model, hyper alerts are transmitted to the database for attack prevention. In the second stage, a transductive deep learning model with k-medoids clustering is adopted for attack identification. With k-medoids clustering, soft labels are assigned for attack and data and update to the database. In the last phase, with computed HMM_TDL database is updated with computed trust value for attack prevention within the cloud. 2022
Aoudni Y.; Donald C.; Farouk A.; Sahay K.B.; Babu D.V.; Tripathi V.; Dhabliya D.
Pattern Recognition Letters, Vol-157, pp. 16-26.
https://doi.org/10.1016/j.patrec.2022.02.012 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127188825&doi=10.1016%2fj.patrec.2022.02.012&partnerID=40&md5=df7f829b402ef0ee3127608978b9d91a
Aoudni Y., Computers and information technologies, Turaif Arts and Sciences College/ Northern Borders University, KSA; Donald C., Department of Computer Science, CHRIST (Deemed to Be University), Bangalore, India; Farouk A., Department of Computer Science, Faculty of Computers and Artificial Intelligence, South Valley University, Hurghada, Egypt; Sahay K.B., Department of Electrical Engineering, Madan Mohan Malaviya University of Technology, Uttar Pradesh, Gorakhpur, 273010, India; Babu D.V., Aarupadai Veedu Institute of Technology, Chennai, Vinayaka Mission's Research Foundation, Deemed to be University, Tamilnadu, Chennai, India; Tripathi V., Department of Computer Science & Engineering, Graphic Era Deemed to be University Dehradun, Uttarakhand, India; Dhabliya D., Department of Computer Engineering, Vishwakarma Institute of Information Technology, Pune, India