Affiliations


  • Assistant Professor, Umeå University
  • Senior Member, ADSLab
  • Leading Cyber Analytics and Learning Group
  • Member, Umeå AI

    1. VSI-DDoS Detection on the Edge - A Combination Learner Approach - In WASP Security Cluster Meeting, Uppsala University, 2023.05.31, 2023, Uppsala.

    2. Building Turst in AI for Healthcare Applicatiions - In a workshop on AI in Medicine at Rajasthan University of health Sciences, 2023.04.29, 2023, Jaipur, India.

    3. Anomaly Detection on the Edge - A Deep Learning Approach - In the Department of Computer Science and Engineering, University of Calcutta, 2023.01.27, 2023, Kolkata, India.

    4. Argumentation-Based Adversarial Regression with Multiple Learners - In 34th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), Virtual Event, 2022.10.31, Oct 31 - Nov 2, 2022.

    5. Deep Learning-Based Cyberattacks Behaviour Analysis for Cloud Systems - In the International Faculty Development program on Data Analytics and Machine Learning, 2022.03.22, March 21-25, 2022, Mizoram University aand North-Eastern Hill University, India

    6. Federated Learning - Privacy, Scalability and Open Challenges - In an initiation meeting 2021.09.06, 2021, Harbin Institute of Technology, China

    7. Trustworthy Learning to Uncover Anomalies at Scale - In the ADS Lab, 2020.04.08, 2020, Umeå University, Sweden.

    8. Adversarial Impact on Anomaly Detection in Cloud Datacenters - In the 24th IEEE Pacific Rim International Symposium on Dependable Computing (PRDC), 2019.12.03, December 1-3, 2019, Kyoto, Japan.

    9. AI in Security : Does Data Matter? - In the Information Science Divison at NARA Institute of Science and Technology (NAIST), Japan on 2019.11.26 invited by the Coordinator of Colloquium Lectures, NAIST.

    10. Adversarial Learning-aware Anomaly Detection - In the Information Technology Center at The University of Tokyo, Hongo Campus, Japan on 2019.11.22 invited by the Information Technology Center.

    11. The Impact of AI on Security - In the Training Industrial Cyber Security Experts at IPA (Information-technology Promotion Agency), a public entity of Japan on 2019.11.22 invited by IPA authority.

    12. Information-theoretic Ensemble Learning for DDoS Detection with Adaptive Boosting - The 31st IEEE International Conference on Tools with Artificial Intelligence (ICTAI), 2019.11.05, November 4-6, 2019, Portland, Oregon, USA organized by BAI Foundation.

    13. Trustworthy Learning to Uncover Anomalies at Scale - In Department of Computing Science, Umeå University, 2019.06.12, Sweden.

    14. Why Anomaly Detection Matters for Critical Infrastructure Providers in Clouds? - In the Cyber Resilience Lab at Nara Institute of Science and Technology, Japan on 2019.04.19 organized by the Laboratory for Cyber Resilience.

    15. Multi-Scale Low-Rate DDoS Attack Detection Using the Generalized Total Variation Metric - In the 17th IEEE International Conference on Machine learning and Applications, Orlando, Florida, USA, 2018.12.20, December 17-20, 2018 organized by Association for Machine Learning and Applications (AMLA).

    16. Data-driven DDoS Detection based on Generalized Total Variation Metric - UMIT Seminar Series, Umeå University, Sweden, 2018.11.17 organized by UMIT, Umeå University.

    17. Monitoring Cloud Datacenters at Scale - Bharat Institute of Technology, Meerut, India, 2018.06.23 organized by Internet Governance and Research Initiatives, Cyber Peace Foundation, Delhi.

    18. Cyber Extortion : The Evolving DDoS Landscape - 12th Cloud Control Workshop, Lövånger, Sweden, 2018.03.19 organized by Umeå University and Lund University, Sweden.

    19. Applying Data Mining Techniques to Network Traffic Anomaly Detection - Department of Computing Science, Umeå University, Sweden, 2017.10.20 organized by Distributed Systems Group, Umeå University.

    20. Live Demonstration of Cyber Attacks in Enterprise Networks - National Workshop on Network Security, March 15-16, 2013, Tezpur, India, 2013.03.16, organized by Department of Computer Science and Engineering, Tezpur University.

    21. RODD: An Effective Reference-based Outlier Detection Technique for Large Datasets - 1st International Conference on Computer Science and Information Technology, Jan 2-4, 2011, Royal Orchid Central, Bangalore, India, 2011.01.03

    22. Anomaly-based Intrusion Detection using Incremental Approach - National Workshop on Network Security, June 9-10, 2010, 2010.06.09, organized by Department of Computer Science and Engineering, Tezpur University.