Detection of Mobile Keyloggers Using Deep Learning
Ch. Madhuri1, K. Rama Siritha2, S. Sai Ram3, G. Rama Koteswara Rao4
1Ch.Madhuri, Information Technology, VR Siddhartha Engineering College, Vijayawada, India.
2K. Rama Siritha, Information Technology, VR Siddhartha Engineering College, Vijayawada, India.
3S. Sai Ram, Information Technology, VR Siddhartha Engineering College, Vijayawada, India.
4Rama Koteswara, Rao Information Technology, VR Siddhartha Engineering College, Vijayawada, India.
Manuscript received on 29 May 2019 | Revised Manuscript received on 03 June 2019 | Manuscript published on 30 June 2019 | PP: 1751-1755 | Volume-8 Issue-8, June 2019 | Retrieval Number: H6845068819 /19©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: Keylogger is a tool which is used to record every keystroke made on the machine. It is used for gaining sensitive information without the knowledge of the owner by the attacker or any cybercriminal. By identifying the keyloggers we can prevent huge amount of data loss including sensitive information like personal details, credit card data, login credentials, passwords of any online banking and e-commerce websites, etc. The Keyloggers intrude our privacy by keeping track of the websites we visit, media files opened, passwords we type on the website. The deep learning algorithm gradient descent is used for detecting mobile keyloggers in the APK files.
Keywords: Keylogger, Deep Learning, Gradient Descent, APK files.
Scope of the Article: Deep Learning