Dr. Raman Singh


Assistant Professor


Intrusion Detection System, Cloud Data Security, Cyber Physical System, Autonomous Driving, Machine Learning



Contact No.



Dr. Raman Singh is working as Assistant Professor with Computer Science and Engineering Department, Thapar Institute of Engineering & Technology Patiala. He has completed Ph.D. (CSE) from Institute of Engineering and Technology, Panjab University Chandigarh in February 2016. He has completed Master of Engineering (IT) from UIET, Panjab University Chandigarh in May 2010. He has published 14 research papers in international journals and conferences. He has won Best Publication of The Year - 2016 award from UIET Panjab University. He has 6 years of teaching and research experience. He has served Information Technology industry for two years as a technology solution consultant. He is a Microsoft Certified Technology Specialist (MCTS) and Microsoft Technet Certified Technology Expert. His area of interest includes Intrusion Detection, Network Security, Cyber Security, Autonomous Driving and Machine Learning.

Research Projects:

Project Title: An Efficient Software Defined Network (SDN) - based Framework for Big Data Processing in Cloud Data Center

From: 15/08/2017 To 15/08/2019

Summary: In recent years, there has been an exponential increase in the Internet-enabled devices which are used for cooperative data sharing and information processing by the end users from different network locations. These devices may generate a lot of data which varies with respect to the volume, velocity, variety, varcity, and value. There may be different sources of data from which the data with respect to these attributes can be generated and processed using different data mining techniques. The sources of big data generation may be transportation systems, healthcare domain, or from social websites. To process such as large collection of database repository is one of the biggest challenges in this type of environment. Moreover, the data generated from these Internet-enabled devices need to be accessed from any location in a distributed manner. In this direction, cloud computing can be one of the solutions as it provides seamless connection to various smart objects, such as smart phones, PDAs, smart vehicles, or smart home appliances which may be distributed geographically. Cloud computing can be viewed as a distributed database repository from which various smart devices can access data as per their needs. This complex large-scale computing technology need to store, process and analyze large amounts of datasets as many organizations are adopting it. In this project, SDN-based framework would be designed to process the large datasets generated from various sources in the cloud environment in an efficient manner.

Project Title: Authentico: Aadhar based Authentication

From: 15/05/2017 To 15/05/2018

Summary: Authentico on the whole will be Aadhaar based person identity authentication system with instant verification. This project aims to make who of the authentication process easy, reliable and fast. It will make easier for the person who has to provide an identity without even carrying his proof; just their fingerprints could also help them get their identity verified. It will also help the person who has to check the identity and verify them as it will be easier, automatic and fast. With the means of this we aim to achieve the goal of truth, legitimate use, and the main agenda of our government to eliminate falsie works.

Membership of Professional Institutions, Associations, Societies:

  1. Graduate Professional Member of IEEE.

Publications and other Research Outputs


  1. Raman Singh, Harish Kumar, R.K. Singla, K.R. Ramkumar, “Internet Attacks and Intrusion Detection System: Study and Review”, Online Information Review, Vol. 41, No. 2, (Indexed in SCIE and SCOPUS), ISSN: 1468-4527, Impact Factor: 1.152.
  2. K. R. Ramkumar and Raman Singh, “Key Management using Chebyshev Polynomials for Mobile Ad Hoc Networks”, China Communications (published by IEEE explorer by China Institute of Communications, Indexed in SCIE and SCOPUS). ISSN: 1673-5447, Impact Factor: 0.424. (Accepted).
  3. Raman Singh, Harish Kumar and R K Singla, “An Intrusion Detection System using Network traffic Profiling and Online Sequential Extreme Learning Machine”, Expert Systems with Applications (Elsevier Journal, Indexed in SCIE and SCOPUS). ISSN: 0957-4174, Impact Factor: 2.981, Source Normalized Impact per Paper (SNIP): 2.561. Volume 42, Issue 22, pages 8609–8624.
  4. Raman Singh, Harish Kumar and R K Singla, “A Reference Dataset for Network Traffic Activity based Intrusion Detection System”, International Journal of Computers Communications & Control (IJCCC), ISSN No. 1841-9836, Vol 10, No 3, pp 390-402. (Indexed in SCIE and Scopus) Journal Citation Report Impact Factor: 0.627.
  5. Raman Singh, Harish Kumar and R K Singla, “TOPSIS Based Multi-Criteria Decision Making of Feature Selection Techniques for Network Traffic Dataset”, International Journal of Engineering and Technology (IJET), ISSN No. 0975-4024, Vol 5 No 6 Dec 2013-Jan 2014, pp 4598-4604, (Indexed in Scopus), Source Normalized Impact per Paper: 0.581).

Book Chapters:

  1. Raman Singh, Harish Kumar and R.K. Singla," Analyzing statistical effect of sampling on network traffic dataset”, ICT and Critical Infrastructure: Proceedings of the 48th Annual Convention of Computer Society of India- Vol I, Advances in Intelligent Systems and Computing (Springer), ISBN No. 978-3-319-03106-4,Volume 248, 2014, pp 401-408, indexed in ISI Web of Science/Thomson Reuters, Scopus. Source Normalized Impact per Paper: 0.160)
  2. Raman Singh, Harish Kumar and R.K. Singla," Traffic Analysis of Campus Network for Classification of Broadcast Data", 47th Annual National Convention of Computer Society of India, International Conference on Intelligent Infrastructure, December 1-2, 2012, Science City, Kolkata. Proceeding published by MacGraw Hill Professional, ISBN No. 13-978-1-25-906170-7, pp 163-166.


  • Raman Singh, Harish Kumar and R.K. Singla, "Performance Analysis of an Intrusion Detection System using Panjab University Intrusion DataSet”, 2nd IEEE International Conference on Recent Advances in Engineering and Computational Sciences held on Dec 21-22, 2015 at UIET, Panjab University Chandigarh.
  • Raman Singh, Harish Kumar and R.K. Singla, "Synthetic Network Traffic Dataset Generation for behavioral Profiling”, 5th International Conference on Computers Communications and Control (ICCCC 2014), held on May 7-9, 2014 at Oradea, Romania
  • Raman Singh, Harish Kumar and R.K. Singla, "Analysis of Feature Selection Techniques for Network Traffic Dataset”, IEEE International Conference on Machine Intelligence Research and Advancement (ICMIRA), held on 21st -23rd Dec 2013 at Katra, ISSN No. 978-0-7695-5013-8, pp 42-46, indexed in ISI Web of Science/Thomson Reuters, Scopus.

Awards and Honours

Award Received:

  1. Received “Best Publication of the Year – 2015” and cash prize of Rs. 10000 from UIET Panjab University, Chandigarh on April 23, 2016.
  2. Received Teaching and Research Assistantship under World Bank sponsored “Technical Education Quality Improvement Program – Phase II”.
  3. Microsoft Certified Technology Specialist (MCTS)
  4. Received scholarship from Board of School Education Haryana in 1995,1998 and 2000.
  5. Received Merit certificate of 8th class.

Patent Filed:

  1. Electronic assistive device for classroom teaching (Patent No.: TEMP/E-1/30100/2016-DEL)
  2. Mobile phone with a mechanism to lock power button for preventing the unauthorized use (Patent No. TEMP/E-1/21226/2016-DEL).

Description of Research Interests:

Intrusion detection model is created to identify anomalies and possibility of attacks. Based on analysis of dataset by intrusion recognition model alert reports are generated. Machine learning approaches can be used to create intrusion detection model. The anomaly based approaches can be used to detect zero day attacks but these have high rate of false alarms. This technique also experience low accuracy rate. Hybrid approaches can be used to find known and unknown attacks but are quite complex and takes longer time to generate alerts. These issues are open research challenges in the field of anomaly based IDS. Anomaly detection techniques with high accuracy, low false alarms and less detection time are required.

Cyber-Physical Systems (CPS) is integrations of computation, networking, and physical processes. Technological advances in computing, communications, and control, have set the stage for a next generation of engineered systems, called cyber-physical systems (CPS). These systems can potentially be important in overcoming many challenges in energy, environment, transportation, and health care. Autonomous driving research can be used to solve traffic problem in Smart City. Machine Learning approaches along with CPS will helps in solving various issues of today’s city of congested traffic.