An Intuitive Way to Unmask in-Browser Cryptojacking in Network Level using Support Vector Machine (SVM) in Machine Learning
Pruthvi Raj Kantamani1, Geetha Manoj Potru2, Yovan Felix A3
1Pruthvi Raj Kantamani, School of Computing, Sathyabama Institute of Science and Technology, Chennai (Tamil Nadu), India.
2Geetha Manoj Potru, School of Computing, Sathyabama Institute of Science and Technology, Chennai (Tamil Nadu), India.
3Yovan Felix A, School of Computing, Sathyabama Institute of Science and Technology, Chennai (Tamil Nadu), India.
Manuscript received on 19 July 2019 | Revised Manuscript received on 03 August 2019 | Manuscript Published on 10 August 2019 | PP: 562-566 | Volume-8 Issue-2S3 July 2019 | Retrieval Number: B11030782S319/2019©BEIESP | DOI: 10.35940/ijrte.B1103.0782S319
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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: Cryptocurrency mining is skyrocketed in the recent times. The hackers are turning their heads towards this type of attacks mainly through browser-based mining which makes them undetected. This leads to the increase in Electricity bills and heavy load on the computer processing. This can be avoided by disabling the java script in the device. The disabling Java Script leads to poor user experience of the websites as the websites in recent times are powered with Java Script frameworks. This paper discusses about a live network filtering tool which detects the illicit In-browser mining within the range of a network of devices.
Keywords: Cryptojacking, SVM, In-Browser Mining, Wireshark, Cryptocurrency, Illegal Cryptomining.
Scope of the Article: Machine Learning