Spyware Detection and Prevention using Deep Learning AI for user applications
Mahesh V1, Sumithra Devi K A2
1Mahesh V, JAIN (Deemed-to- be-University), Dayananda Sagar Academy of Technology and Management,Bengaluru-560069, (Karnataka), India.
2Dr. Sumithra Devi K A, Dayananda Sagar Academy of Technology and Management,Bengaluru-560069, (Karnataka), India.
Manuscript received on 24 January 2019 | Revised Manuscript received on 30 March 2019 | Manuscript published on 30 January 2019 | PP: 345-349 | Volume-7 Issue-6, March 2019 | Retrieval Number: E1991017519©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: A user application (Smartphone or personal computer’s) play’s an essential role in our daily life. As usage of smartphones and PC’s keeps on increases, every day in one life, each and everyone uses to do every task in their daily life using smartphone or PCs to access, develop, store data’s. By using this everyone access the data over the internet, the user’s sensitive data’s were shared during the payment process, private messages online, and using their personal data to access the resource to study etc. There is the possibility of occurring attacks to this user sensitive data’s. Weakness on the construction of user application will allow the hacker or attacker to steal user information. Spyware is one type of attack that steel user sensitive information without user knowledge. The proposal states that the method and technique used to detect and prevent the user application from malicious attack using deep learning AI (Artificial intelligence).
Keywords: AI (Artificial intelligence), Internet, Malicious code, Malware, Spyware, user Application.
Scope of the Article: Vision-based applications