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Publication Type : Conference Paper
Publisher : Proceedings of 2018 2nd International Conference on Advances in Electronics, Computers and Communications, ICAECC 2018
Source : Proceedings of 2018 2nd International Conference on Advances in Electronics, Computers and Communications, ICAECC 2018, Institute of Electrical and Electronics Engineers Inc. (2018)
ISBN : 9781538637852
Keywords : Application programming interfaces (API), Computer crime, GURLS, malware, Radial basis function networks, RBF kernels, Regularized Least Squares, Strings, Summary, Training and testing
Campus : Coimbatore
School : School of Engineering
Center : Computational Engineering and Networking
Department : Electronics and Communication
Year : 2018
Abstract : Ransomware is a malware, which upon execution scrambles the framework and it denies the client from accessing the data until the point when a payoff sum is not met from the victim. Recently, this kind of malware has shown a massive growth and had affected nearly 100 nations around the globe. In this paper we propose GURLS (Grand Unified Regularized Least Square) based approach to detect ransomware and classify it into different categories. The features used for training and testing are application programming interface (API) invocations and strings. This paper compares the performance of each of these features for classification and the effectiveness of RBF Kernel. The results obtained shows that using RBF kernel gives better accuracy. © 2018 IEEE.
Cite this Research Publication : N. Harikrishnan and Dr. Soman K. P., “Detecting Ransomware using GURLS”, in Proceedings of 2018 2nd International Conference on Advances in Electronics, Computers and Communications, ICAECC 2018, 2018.