Faculty Mr. Rijvan Beg

Mr. Rijvan Beg

Department of Computer Science and Engineering

Contact Details

rijvan.b@srmap.edu.in

Office Location

Education

2025
Ph.D. (CSE)
MANIT (NIT-Bhopal)
India
2012
LNCT Bhopal
MANIT (NIT-Bhopal)
India
2008
B.E (IT)
LNCT Bhopal
India

Experience

  • 2024-2025 - National Forensic Sciences University Bhopal Campus, Bhopal,
  • 2023-2024 - SAGE University, Bhopal
  • 2022-2023 - Maulana Azad National Institute of Technology (NIT-Bhopal), Bhopal
  • 2018-2019 - Lakshmi Narain College of Technology, Bhopal
  • 2011-2018 - TIT Group of Institutions, Bhopal
  • 2010-2011 - Bansal Institutes of Science & Technology, Bhopal

Research Interest

  • My primary research interest lies in the field of Evidence-Based Malware Analysis, which bridges digital forensics, cybersecurity, and data-driven threat intelligence.
  • My research interests lie at the intersection of Cybersecurity, Cyber Forensics. Malware Forensics, and Artificial Intelligence, with a focus on developing intelligent systems for threat detection, malware analysis, and secure communication.
  • I am particularly interested in leveraging deep learning, autoencoders, and forensic neural networks for cross-domain malware localization, and cyber risk assessment.
  • My current work explores quantum computing anomalies in cybersecurity, intelligent systems for IoT device protection, and gesture-based assistive technologies.
  • I am also engaged in interdisciplinary innovations that merge cybersecurity with emerging technologies like conversational AI and quantum computing.

Awards

  • GATE (Graduate Aptitude Test in Engineering)- 2008
  • Percentile- 95.5
  • All India Rank- 225
  • GATE Score - 425

Memberships

  • Member CSTA (Computer science Teachers Association)
  • IOP Publisher (Engineering Research Express)
  • IEEE ISDC Conferences
  • IOS Publisher (Intelligent Data Analysis)
  • Sciendo (Control and Cybernetics)

Publications

  • Design of an Iterative Method for Malware Detection Using Autoencoders and Hybrid Machine Learning Models

    Mr. Rijvan Beg, Rijvan Beg

    Source Title: IEEE Access, Quartile: Q1

    View abstract ⏷

    In the evolving cyber threat landscape, one of the most visible and pernicious challenges is
  • ACMFNN: A Novel design of an augmented convolutional model for intelligent cross-domain malware localization via forensic neural networks

    Mr. Rijvan Beg, Rijvan Beg

    Source Title: IEEE Access, Quartile: Q1

    View abstract ⏷

    The detection and localization of malwares using spatial and temporal data patterns require the

Patents

  • Simultaneous production of bio-oil, biochar and syngas from marine macroalgae waste: waste to wealth in blue economy approach

    Mr. Rijvan Beg

    Status: On-going

  • A System of Intelligent Attachment to Control Wheelchair by Motions Based on Human Gesture Movements and Methods Thereof

    Mr. Rijvan Beg

    Patent Application No: 2.02E+11, Date Filed: 30/03/2021, Date Published: 09/04/2021, Status: Granted

  • System and Method for Achieving Cybersecurity of Internet of Things (IoT) Devices using Embedded Recognition Token

    Mr. Rijvan Beg

    Patent Application No: 2.02E+11, Date Filed: 10/01/2022, Date Published: 25/02/2022, Status: Published

Projects

Scholars

Interests

  • Cyber Forensics
  • Cyber Security
  • Ethical Hacking
  • Malware Analysis

Thought Leaderships

There are no Thought Leaderships associated with this faculty.

Top Achievements

Research Area

No research areas found for this faculty.

Education
2008
B.E (IT)
LNCT Bhopal
India
2012
LNCT Bhopal
MANIT (NIT-Bhopal)
India
2025
Ph.D. (CSE)
MANIT (NIT-Bhopal)
India
Experience
  • 2024-2025 - National Forensic Sciences University Bhopal Campus, Bhopal,
  • 2023-2024 - SAGE University, Bhopal
  • 2022-2023 - Maulana Azad National Institute of Technology (NIT-Bhopal), Bhopal
  • 2018-2019 - Lakshmi Narain College of Technology, Bhopal
  • 2011-2018 - TIT Group of Institutions, Bhopal
  • 2010-2011 - Bansal Institutes of Science & Technology, Bhopal
Research Interests
  • My primary research interest lies in the field of Evidence-Based Malware Analysis, which bridges digital forensics, cybersecurity, and data-driven threat intelligence.
  • My research interests lie at the intersection of Cybersecurity, Cyber Forensics. Malware Forensics, and Artificial Intelligence, with a focus on developing intelligent systems for threat detection, malware analysis, and secure communication.
  • I am particularly interested in leveraging deep learning, autoencoders, and forensic neural networks for cross-domain malware localization, and cyber risk assessment.
  • My current work explores quantum computing anomalies in cybersecurity, intelligent systems for IoT device protection, and gesture-based assistive technologies.
  • I am also engaged in interdisciplinary innovations that merge cybersecurity with emerging technologies like conversational AI and quantum computing.
Awards & Fellowships
  • GATE (Graduate Aptitude Test in Engineering)- 2008
  • Percentile- 95.5
  • All India Rank- 225
  • GATE Score - 425
Memberships
  • Member CSTA (Computer science Teachers Association)
  • IOP Publisher (Engineering Research Express)
  • IEEE ISDC Conferences
  • IOS Publisher (Intelligent Data Analysis)
  • Sciendo (Control and Cybernetics)
Publications
  • Design of an Iterative Method for Malware Detection Using Autoencoders and Hybrid Machine Learning Models

    Mr. Rijvan Beg, Rijvan Beg

    Source Title: IEEE Access, Quartile: Q1

    View abstract ⏷

    In the evolving cyber threat landscape, one of the most visible and pernicious challenges is
  • ACMFNN: A Novel design of an augmented convolutional model for intelligent cross-domain malware localization via forensic neural networks

    Mr. Rijvan Beg, Rijvan Beg

    Source Title: IEEE Access, Quartile: Q1

    View abstract ⏷

    The detection and localization of malwares using spatial and temporal data patterns require the
Contact Details

rijvan.b@srmap.edu.in

Scholars
Interests

  • Cyber Forensics
  • Cyber Security
  • Ethical Hacking
  • Malware Analysis

Education
2008
B.E (IT)
LNCT Bhopal
India
2012
LNCT Bhopal
MANIT (NIT-Bhopal)
India
2025
Ph.D. (CSE)
MANIT (NIT-Bhopal)
India
Experience
  • 2024-2025 - National Forensic Sciences University Bhopal Campus, Bhopal,
  • 2023-2024 - SAGE University, Bhopal
  • 2022-2023 - Maulana Azad National Institute of Technology (NIT-Bhopal), Bhopal
  • 2018-2019 - Lakshmi Narain College of Technology, Bhopal
  • 2011-2018 - TIT Group of Institutions, Bhopal
  • 2010-2011 - Bansal Institutes of Science & Technology, Bhopal
Research Interests
  • My primary research interest lies in the field of Evidence-Based Malware Analysis, which bridges digital forensics, cybersecurity, and data-driven threat intelligence.
  • My research interests lie at the intersection of Cybersecurity, Cyber Forensics. Malware Forensics, and Artificial Intelligence, with a focus on developing intelligent systems for threat detection, malware analysis, and secure communication.
  • I am particularly interested in leveraging deep learning, autoencoders, and forensic neural networks for cross-domain malware localization, and cyber risk assessment.
  • My current work explores quantum computing anomalies in cybersecurity, intelligent systems for IoT device protection, and gesture-based assistive technologies.
  • I am also engaged in interdisciplinary innovations that merge cybersecurity with emerging technologies like conversational AI and quantum computing.
Awards & Fellowships
  • GATE (Graduate Aptitude Test in Engineering)- 2008
  • Percentile- 95.5
  • All India Rank- 225
  • GATE Score - 425
Memberships
  • Member CSTA (Computer science Teachers Association)
  • IOP Publisher (Engineering Research Express)
  • IEEE ISDC Conferences
  • IOS Publisher (Intelligent Data Analysis)
  • Sciendo (Control and Cybernetics)
Publications
  • Design of an Iterative Method for Malware Detection Using Autoencoders and Hybrid Machine Learning Models

    Mr. Rijvan Beg, Rijvan Beg

    Source Title: IEEE Access, Quartile: Q1

    View abstract ⏷

    In the evolving cyber threat landscape, one of the most visible and pernicious challenges is
  • ACMFNN: A Novel design of an augmented convolutional model for intelligent cross-domain malware localization via forensic neural networks

    Mr. Rijvan Beg, Rijvan Beg

    Source Title: IEEE Access, Quartile: Q1

    View abstract ⏷

    The detection and localization of malwares using spatial and temporal data patterns require the
Contact Details

rijvan.b@srmap.edu.in

Scholars