Urvashi

About

I served as an Assistant Professor in the Department of Computer Science and Engineering at NIT Jalandhar. I earned my Bachelor's degree in Computer Science and Engineering from Kurukshetra University, Haryana, India, in 2010. Following that, I pursued my Master's degree in Computer Science and Engineering at NIT Jaipur, Rajasthan, completing it in 2012. Subsequently, I obtained my Ph.D. in Computer Science and Engineering from NIT Jalandhar, Punjab, India, in 2019. My current research focuses on areas such as cyber security, information security, adversarial machine learning, explainable AI, and water quality assessment.

Employment

• Dr. B. R. Ambedkar National Institute of Technology Jalandhar Assistant Professor Grade I
  2022 - Present
• Dr. B. R. Ambedkar National Institute of Technology Jalandhar Assistant Professor Grade II
  2019 - 2022
• Thapar Institute of Engineering & Technology Lecturer
  2018 - 2019
• Lovely Professional University Assistant Professor
  2012 - 2015

Education

• Dr. B. R. Ambedkar National Institute of Technology Jalandhar PhD
  2015 - 2019
• Malaviya National Institute of Technology Jaipur MTech
  2010 - 2012
• Kurukshetra University BTech
  2006 - 2010

Projects & Funding

Projects & funding information is unavailable.

Publications (46)

• A hybrid explainable intrusion detection system for fair and trustworthy cybersecurity
  Computers and Electrical Engineering 2026 DOI: 10.1016/j.compeleceng.2026.111218
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• A Stacked Ensemble Framework for Android Malware Detection Using Semantic Permission Aggregation and Explainable <scp>AI</scp>
  SECURITY AND PRIVACY 2025 DOI: 10.1002/spy2.70110
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• Unified Quantitative Evaluation of System Severity: Leveraging Time to Compromise and Cost-Benefit Analysis for Enhanced vulnerability Risk Assessment
  Journal of Network and Systems Management 2025 DOI: 10.1007/s10922-025-09975-4
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• An Investigation for River Water Quality via Linear Regression Analysis of Variance
  Water Resources 2025 DOI: 10.1134/s0097807823602078
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• AFLF: a defensive framework to defeat multi-faceted adversarial attacks via attention feature fusion
  Evolving Systems 2025 DOI: 10.1007/S12530-024-09643-Z
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• Deadline-aware and energy efficient IoT task scheduling using fuzzy logic in fog computing
  Multimedia Tools and Applications 2025 DOI: 10.1007/S11042-024-19509-W
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• Towards Resilient Cyber Defense: Exploring the Synergy of Adversarial Robustness and Explainable AI in NIDS
  2025 DOI: 10.2991/978-94-6463-740-3_8
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• Quantitative Evaluation of Extensive Vulnerability Set Using Cost Benefit Analysis
  IEEE Transactions on Dependable and Secure Computing 2024 DOI: 10.1109/TDSC.2023.3253121
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• How to Defend and Secure Deep Learning Models Against Adversarial Attacks in Computer Vision: A Systematic Review
  New Generation Computing 2024 DOI: 10.1007/S00354-024-00283-0
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• A Reliable Approach for Generating Realistic Adversarial Attack via Trust Region-Based Optimization
  Arabian Journal for Science and Engineering 2024 DOI: 10.1007/S13369-024-09293-Y
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