Analysis of Cloud Log Files to Prevent Account Hijacking Attacks in Hybrid Cloud
Rahul Jain1, Sachin Goyal2, Ratish Agrawal3
1Rahul Jain, Department of Computer Science & Engineering, Radharaman Institute of Research and Technology, RGPV University, Bhopal (M.P), India.
2Sachin Goyal, Assistant Professor, Department of Information and Technology, University Institute of Technology, RGPV Bhopal (M.P), India.
3Ratish Agrawal, Assistant Professor, Department of Information and Technology, University Institute of Technology, RGPV Bhopal (M.P), India.
Manuscript received on 12 December 2018 | Revised Manuscript received on 23 December 2018 | Manuscript published on 30 December 2018 | PP: 37-40 | Volume-8 Issue-2, December 2018 | Retrieval Number: B2541128218/18©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Cloud services supplanting the other web services in exponential rate, year-over-year. Despite the rising prevalence in cloud services, lack of proficiency in the field of cloud security is now the largest cloud challenge. The proposed method is based on the data mining techniques applied on the recorded log entries in the access log file. Before, applying data mining coarse gained log entries has been converted into fine gained log entries to improve the result. Then, generates the rule set to identify the different attacks in cloud environment. Finally, the result analysis of the proposed method has been carried out on the standard dataset through calculating the confusion matrix. Then, calculated results have been compared with other techniques through the depiction of different curves such as ROC, Lift curve, etc. These curves clear the vision about best result. Result analysis, carried out in this work shows that Logistic Regression is giving the best result among other methods.
Keyword: Session Hijacking, Logistic Regression Decision Tree, Random Forest Roc Curve, Lift Curve
Scope of the Article: Regression and Prediction