Maninder Singh

Work place: Computer Science & Engineering Department Thapar University Patiala, INDIA



Research Interests: Computer systems and computational processes, Network Security, Data Structures and Algorithms


Dr. Maninder Singh is an Associate Professor at the Computer Science and Engineering Department, Thapar University, Patiala and also heads the Centre of Information and Technology Management (CITM). He received his Bachelor's Degree from Pune University, Master's Degree, with honours in Software Engineering from Thapar Institute of Engineering & Technology, and holds his Doctoral Degree with specialization in Network Security from Thapar University. His research interest includes Network Security, Grid Computing, Secure coding and is a strong torchbearer for Open Source Community. He has many research publications in reputed journals and conferences. He is on the Roll-of-honour @ EC-Council USA, being certified as Ethical Hacker (C|EH), Security Analyst (ECSA) and Licensed Penetration Tester (LPT).
Dr. Singh has successfully completed many consultancy projects (network auditing and penetration testing) for renowned national bank(s) and corporate and also architected Thapar University‚Äüs network presence. In 2003 his vision for developing an Open Source Based network security toolkit was published by a leading national newspaper. Linux For You magazine from India declared him a 'Tux Hero' in 2004. He is a Senior Member of IEEE, Senior Member of ACM and Life Member of Computer Society of India. He has been volunteering his services for Network Security community as a reviewer and project judge for IEEE design contests. Recently Dr. Singh was aired on “Centre Stage” @ Headlines Today, national channel.

Author Articles
Hybrid Real-time Zero-day Malware Analysis and Reporting System

By Ratinder Kaur Maninder Singh

DOI:, Pub. Date: 8 Apr. 2016

To understand completely the malicious intents of a zero-day malware there is really no automated way. There is no single best approach for malware analysis so it demands to combine existing static, dynamic and manual malware analysis techniques in a single unit. In this paper a hybrid real-time analysis and reporting system is presented. The proposed system integrates various malware analysis tools and utilities in a component-based architecture. The system automatically provides detail result about zero-day malware's behavior. The ultimate goal of this analysis and reporting is to gain a quick and brief understanding of the malicious activity performed by a zero-day malware while minimizing the time frame between the detection of zero-day attack and generation of a security solution. The results are paramount valuable for a malware analyst to perform zero-day malware detection and containment.

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CUDA based Rabin-Karp Pattern Matching for Deep Packet Inspection on a Multicore GPU

By Jyotsna Sharma Maninder Singh

DOI:, Pub. Date: 8 Sep. 2015

This paper presents a study of the improvement in efficiency of the Rabin-Karp pattern-matching algorithm based Deep Packet Inspection. NVIDIA GPU is programmed with the NVIDIA's general purpose parallel computing architecture, CUDA, that leverages the parallel compute engine in NVIDIA GPUs to solve many complex computational problems in a more efficient way than on a CPU. The proposed CUDA based implementation on a multicore GPU outperforms the Intel quadcore processor and runs upto 14 times faster by executing the algorithm in parallel to search for the pattern from the text. The speedup may not sound exorbitant but nonetheless is significant, keeping in view that the experiments have been conducted on real data and not synthetic data and, optimal performance even with the huge increase in traffic was the main expectation, not just an improvement in speed with few test cases.

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A Hybrid Real-time Zero-day Attack Detection and Analysis System

By Ratinder Kaur Maninder Singh

DOI:, Pub. Date: 8 Aug. 2015

A zero-day attack poses a serious threat to the Internet security as it exploits zero-day vulnerabilities in the computer systems. Attackers take advantage of the unknown nature of zero-day exploits and use them in conjunction with highly sophisticated and targeted attacks to achieve stealthiness with respect to standard intrusion detection techniques. Thus, it's difficult to defend against such attacks. Present research exhibits various issues and is not able to provide complete solution for the detection and analysis of zero-day attacks. This paper presents a novel hybrid system that integrates anomaly, behavior and signature based techniques for detecting and analyzing zero-day attacks in real-time. It has layered and modular design which helps to achieve high performance, flexibility and scalability. The system is implemented and evaluated against various standard metrics like True Positive Rate (TPR), False Positive Rate (FPR), F-Measure, Total Accuracy (ACC) and Receiver Operating Characteristic (ROC) curve. The result shows high detection rate with nearly zero false positives. Additionally, the proposed system is compared with Honeynet system.

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