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About me

I am ParulGahelot pursuing M.Tech (Specialized cybrsecurity) at center for advanced studies. I have done B.Tech in S.R. institute of management and technology,lucknow and diploma in government polytechnic,Unnao.

Interested area

  • Network security, malware analysis in android smart phones, cyber security.


Analysis of deep packet inspection in advance method of managing and examine packet traffic. Network forensics is use in two ways first related to security second related to law enforcement. Analysis and monitoring computer network traffic for the purpose of legal evidence or intrusion detection.

Bio: I am ARVIND GOUTAM. I belong to LUCKNOW. I have completed bachelor degree in COMPUTER SCIENCE from MAHARANA INSTITUTE OF PROFESSIONAL STUDIES with 60.34%. I did my schooling 12th and 10th from U.P board from my hometown. My final year project is on “ONLINE JOB CONSULTANCY” which is developed on ASP.Net as frontend. 


 Project- Vulnerability Assessment and Penetration Testing.

 My Role and work-

1- Web application development cycle.

2- Practice various webapp based attacks.

3- Security aspect in development cycle.

Abstract-In my internship, I'm working on Vulnerability Assessment and Penetration Testing (Web Application). It is about finding vulnerabilities (flaws) in web application and providing secure code which removes these security flaws. I will be working on various attack vectors like SQL Injection, Cross-Site Request Forgery, Cross-Site Scripting etc and their mitigation techniques. The focus of this training is security aspect in development cycle.

I am Shikha & I am pursuing M .Tech Computer science with specialization in Cyber Security from Centre For Advance Studies (DR. APJ Abdul Kalam Technical University) Lucknow. I begged my B .Tech in computer science from I.I.M.T Engineering College Meerut (GautamBuddh Technical University Lucknow).

My areas of interest are malware analysis, security monitoring tool, cloud security.

Abstract - Despite the significant improvement of security defense mechanisms and their continuous evolution, malware are still spreading and keeping to succeed in pursuing their malicious goals. These advanced malwares may be encrypted, compressed or other-wise obfuscated to evade traditional detection techniques. Static analysis is preferred on the other techniques because it is safe to infect the productive systems and Portable Executable (PE) can be a comprehensive view in analyzing malware. Hence in this work I will use the information inside the PE files to detect advanced malware in huge volume of data.

Bio:Currently, I am doing M. Tech in Cyber Security from Computer Science and Engineering department, Dr. A.P.J. Abdul Kalam Technical University. I have done B.Tech. in Computer Science and Engineering from Uttar Pradesh Technical university, Vira College of Engineering Bijnor (2009-2013). I am working in area of cyber security and also have great interest in Web Vulnerability Assessment and Penetration Testing (WVAPT).

Area of Interest- Network and Information Security, Cryptography.

Project- Deep Packet Inspection (DPI) in Network.

Abstract- Computer networks become larger day by day and connected to the internet is the subject of cyber-attacks. Economic cost of cyber-attack is commercial loss arising from theft of corporate and financial information, reputational damage, and legal consequence of cyber breach. Many forensic tools and strong security measure contribute together to detect those attacks and re-establishing the network. Hence increasing security of the network is much more important. Various Forensic tools are used to capture, filter and inspect packets. In this work, I will use these tools for deep packet Inspection and analysis the malicious traffic on the network.

Bio: I am pursuing M.Tech in Computer Science (with specialization Cyber Security) at the Centre for Advanced Studies, Dr. A.P.J. Abdul Kalam Technical University, Lucknow and I have done B.Tech degree in Computer Science Engineering from Shri Ram MurtiSmarak College of Engineering & Technology at Bareilly.

Area of Interest:  Cyber Security, Malware Analysis & Web VAPT

Title: Detection of loopholes in web application

Vulnerability Assessment and Penetration Testing (VAPT) techniques help them to go looking out security loopholes. These security loopholes could also be utilized by attackers to launch attacks on technical assets. It divides into 3- phases like Web Application Development Cycle, Web Application Security Testing and Web based attacks, Security aspect in Development Cycle. According to the news of OWASP for web applications vulnerability like Broken Authentication & Session Management, Cross-site Scripting (XSS), Insecure Direct Object References. In my work I am doing detection of some loopholes in web application.

Bio: I am an undergraduate Computer Science Engineering student from Gandhi Engineering College, Odisha. By day am a full-time student and at night am an Ethical Hacker and a Cyber Security Researcher. Till yet worked and acknowledged by more than 100+ companies, most of counted from Silicon Valley.

Area of Interest: VAPT (Vulnerability Assessment and Penetration Testing ). Basically, at C3I center am testing the security vulnerabilities of the SCADA systems.

Abstract: Detection of a malware when a new binary is downloaded, to distinguish it from ‘benign-ware’ is an important part of computer security.  There exist various techniques proposed by researchers using both static and dynamic analyses to detect malware. But day by day, malware authors have improved its evasion capability using non-persistence, obfuscation techniques, and use of  volatile payloads that operate only in memory.  With obfuscation techniques, malware authors make the reverse engineering of binary tougher. So now malware analysis is not limited to static and dynamic analysis. By memory forensics techniques we can get a comprehensive view of the actions of an executable. We have used an interval-based approach to take the memory dumps and then selected one memory dump for further analysis. In this work we have extracted various features from memory dump such registry bindings, suspicious DLLs, hidden processes, orphan threads, code injection, injected DLLs, file system etc., and automated the classification of malware vs. benign-ware. For evaluation purposes we used 1730 malware and 1571 benign files. We achieved 99.09% accuracy with 0.43% false positive rate using XG-Boost
classification method.

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