National Institute Of Technology,Kurukshetra

DEPARTMENT OF COMPUTER_ENGG

Faculty

Name : Ankit Kumar Jain
Designation : Assistant Professor
Qualification : PhD (NIT Kurukshetra)
Current Address :

Room number- 208, Computer Engineering Department, National Institute of Technology, Kurukshetra

 


Phone 1 (office) : 01744-233489
Phone 2 (office) :
Email : ankit.jain2407@gmail.com, ankitjain@nitkkr.ac.in

Area Of Intrest :

Cyber and Web Security, Mobile Security, Machine Learning, Security Issues in IoT, Online Social Networks Analysis

Call for Papers:  International Conference on Paradigms of Computing,Communication and Data Sciences (PCCDS-2020) at NIT Kurukshetra ( 1 May 2020 to 03 May 2020)

 

Experience :

  • Teaching- 8+ Years

Current Activities

1. Call for Papers:  International Conference on Paradigms of Computing,Communication and Data Sciences (PCCDS-2020) at NIT Kurukshetra ( 1 May 2020 to 03 May 2020)

2. Call for Book Chapters: Machine Learning Techniques for Pattern Recognition and Information Security

Previous Activities


1. Call for Participation: One Week STC On Pattern Recognition and CyberSecurity Applications (05.09.2019--09.09.2019)

2. Call for Papers:  Special Session on Pattern Recognition and Machine Learning: Innovations, Applications and Challenges

Other :

M.Tech Thesis Supervised:

  • Completed- 07
  • Ongoing- 04

Academics and Administrative Responsibilities:

  • Member of MTech(Computer Engineering) Syllabi & Scheme Revision committee.
  • Member of  MTech(Cyber Security) Syllabi design committee.
  • Deputy centre superintendent examination in may 2017.

Publications:

2019

  • A. K. Jain and B. B. Gupta, “A Machine Learning based Approach for Phishing Detection using Hyperlinks Information,” Journal of Ambient Intelligence & Humanized Computing, vol. 10, issue 5, 2019, Springer, https://doi.org/10.1007/s12652-018-0798-z (SCIE- Indexed)
  • R. Vishwakarma and A. K. Jain, " A survey of DDoS attacking techniques and defence mechanisms in the IoT network," Telecommunication Systems, https://doi.org/10.1007/s11235-019-00599-z, (SCIE- Indexed)
  • A. K. Jain, D. Goel, S. Agarwal, Y. Singh and G. Bajaj, " Predicting Spam Messages Using Back Propagation Neural Network, Wireless Personal Communications, DOI https://doi.org/10.1007/s11277-019-06734-y (SCIE- Indexed)
  • A. K. Jain and B. B. Gupta, “Feature based Approach for Detection of Smishing Messages in the Mobile Environment,” Journal of Information Technology Research (JITR), vol. 12, issue 2, 2019 (Scopus Indexed)
  • A. K. Jain, S.K. Yadav, and N. Choudhary, "A Novel Approach to Detect Spam and Smishing SMS using Machine Learning Techniques, International Journal of E-Services and Mobile Applications (IJESMA), (Accepted, In Press) (Scopus Indexed)

2018

  • A. K. Jain and B. B. Gupta, “Towards detection of phishing websites on client side using machine learning based approach,” Telecommunication System, vol. 68, issue 4, 2018, Springer https://doi.org/10.1007/s11235-017-0414-0 (SCIE- Indexed)
  • D. Goel and A. K. Jain, “Mobile phishing attacks and defence mechanisms: State of art and open research challenges, Computers & Security, Volume 73, 2018, pp 519-544, (SCIE- Indexed)
  • A. K. Jain and B. B. Gupta, “Two-level authentication approach to protect from phishing attacks in real time,” Journal of Ambient Intelligence & Humanized Computing, 2017, Springer, DOI 10.1007/s12652-017-0616-z (SCIE- Indexed)
  • A.K. Jain and B. B. Gupta, “Detection of Phishing attacks in financial and e-banking Websites Using Link and Visual Similarity Relation,” International Journal of Information and Computer Security (IJICS), vol. 10, issue 4, 2018, Inderscience, (Scopus Indexed)
  • A. K. Jain and B. B. Gupta, “ Rule-Based Framework for Detection of Smishing Messages in Mobile Environment,” Procedia Computer Science, Vol. 125, 2018, pp. 617-623, (Scopus Indexed)

2017

  • A. K. Jain and B. B. Gupta, “Phishing Detection: Analysis of Visual Similarity Based Approaches,” Security and Communication Networks, vol. 2017, Article ID 5421046, 20 pages, 2017, https://doi.org/10.1007/s12652-018-0798-z (SCIE- Indexed)
  • B. B. Gupta, A. Tewari, A. K. Jain, and D. P. Agrawal, “Fighting against phishing attacks: state of the art and future challenges,” Neural Computing and Applications, vol 28, no 12, pp. 3629-3654, 2017. (SCIE- Indexed)
  • Diksha Goel and Ankit Kumar Jain, “Smishing-Classifier: A Novel Framework for detection of Smishing Attack in Mobile Environment,” In proceedings of International Conference on Next Generation Computing Technologies, Dehradun, India, pp. 502-512, 2017   DOI: 10.1007/978-981-10-8660-1_38. (Scopus- Indexed)
  • Neelam Choudhary and Ankit Kumar Jain, “Towards Filtering of SMS Spam Messages Using Machine Learning Based Technique,” In proceedings of International Conference on Advanced Informatics for Computing Research, India, pp 18-30, 2017.
  • Neelam Choudhary and Ankit Kumar Jain, “Comparative Analysis of Mobile Phishing Detection and Prevention Approaches,” In proceedings of International Conference on Information and Communication Technology for Intelligent Systems, 25-26 March 2017, Ahmedabad, India, pp 349-356.

2016

  • A. K. Jain and B. B. Gupta, “A novel approach to protect against phishing attacks at client side using auto-updated white-list,” EURASIP Journal on Information Security, vol. 2016, article 9, 11 pages, 2016, Springer, https://doi.org/10.1186/s13635-016-0034-3 (Scopus Indexed)
  • A. Tewari, A. K. Jain, and B. B. Gupta, “Recent survey of various defense mechanisms against phishing attacks,” Journal of Information Privacy and Security, vol. 12, no. 1, pp. 3–13, 2016.
  • A. K. Jain and B. B. Gupta, “Comparative analysis of features based machine learning approaches for phishing detection,” in Proceedings of the 10th INDIACom, New Delhi, India, pp. 2125-2130, 2016.
  • K. K. Pandey, A. K. Jain and S. Mehrotra, "Performance analysis of cooperative communication in wireless sensor network," 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Jaipur, 2016, pp. 2021-2026