Digital Forensics Using Supervised Ml
Rajyashree.R1, Nimisha Praveen2, Dheeraj.J3, Sudharshan.R4
1Ms. R. Rajyashree, Assistant Professor, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India
2Ms. Nimisha Praveen, Student, BTECH., Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India
3Mr. Dheeraj. J, Student, BTECH., Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India
4Mr. Sudharshan. R, Student, BTECH., Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India
Manuscript received on 18 June 2019 | Revised Manuscript received on 25 June 2019 | Manuscript published on 30 June 2019 | PP: 496-499 | Volume-8 Issue-5, June 2019 | Retrieval Number: E6997068519/19©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: Digital forensics is a branch of forensic science where it focused on recovery and investigation of artefacts found on the digital devices. Its ability to totally reduce or even eliminate sample risk – This is the biggest advantage of forensic science over the external auditors. The forensic science helps in gathering of evidence of physical investigations, so care must be exercised in digital forensic collection to ensure that the data being collected for analysis must be as pure and undisturbed as possible. Digital forensics using supervised ml, uses network forensics and forensic data analysis. In network forensic when the data passed over the network like (LAN WAN MAN), data packets may be lost during the transmission, the lost data packet can be traced by the linear regression algorithm.In data forensics it helps to check the integrity of the data with the existing data by the support vector machine algorithm.These two algorithms of machine learning will help us to find the best trends and predict were the missing packets have gone and the data provided is valid or not
Keywords: Digital Forensics, Data Collection, Data Forensics, Evidence, Integrity, Linear Regression, Network Forensics, Support Vector Machine, Transmission.
Scope of the Article: WAN