Bio
Lalit Kulkarni has completed his Bachelors in Computer Engineering from Govt. College, Nanded and Masters in Computing from Robert Gordon University, UK. He is doing his research in Security for Delay Tolerant Networks. He has published 16 research papers
Qualification
Ph.D. (Submitted)
M.S. (Computing)
B.E. (Computer Science & Engineering)
Area of Research
Network Security
Research Papers
Research Papers 1 : (2019) Lalit Kulkarni, Jagdish Bakal, Urmila Shrawankar, “Energy-Based Incentive Scheme for Secure Opportunistic Routing in Delay Tolerant Networks,” Springer Journal of Computing, ISSN: 1436-5057, 27 June 2019, pp 1–19 https://doi.org/10.1007/s00607-019-00735-2 (Springer SCI Indexed)
Research Papers 2 : (2019) Lalit Kulkarni, Jagdish Bakal, Urmila Shrawankar, “Distributed Misbehavior Detection System for Delay Tolerant Networks”; International Journal of Innovative Technology and Exploring Engineering ISSN: 2278-3075, Volume-8, Issue-9S3, July 2019 (Scopus)
Research Papers 3 : (2018) Pushkar Jagtap, Lalit Kulkarni, “Social-Energy based techniques in Delay Tolerant Network,” 2018 International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS), Institute of Engineering and Management, Kolkata, India February 23th-25th, 2018, Springer. vol 814. Pp. 531-538 ISBN 978-981-13-1501-5
Research Papers 4 : (2018) Pushkar Jagtap, Lalit Kulkarni, “SECBAR: Social Energy Credit-BAsed Router in Delay Tolerant Network,” 15th International Conference on Distributed Computing and Internet Technology, Bhubaneshwar, India Jan 10th – 13th, 2019, Springer.
Patents
- Title: Unknown Attack Detection using Evolution Identification on Streaming Network Data
Patent File No: 1221/MUM/2014
Published Date: 28/03/2014
Patent Authority: Government of India
- Title: System for Detecting Vacant Parking Space
Patent File No: 3102/MUM/2015
Published Date: 11/09/2015
Patent Authority: Government of India
Experience
Teaching experience: 17.5 Years
Industry experience: 1.5 Year
Subjects
Computer Network & Technology, Artificial Intelligence, Advanced Machine Learning