[1] Anomalous Host Identification in High-Cardinality Network Streams using ML-Enabled Reverse-Sketching, IEEE International Conference on Electrical, Computer and Energy Technologies (ICECET), Sydney, Australia (2024). doi: TBA
[2] Deepfake Image Detection using Vision Transformer Models, IEEE International Black Sea Conference on Communications and Networking, Tbilisi, Georgia (2024).
[3] A Review of IoT Firmware Vulnerabilities and Auditing Techniques, Sensors 24(2), MDPI.
[1] Training Manual: Using HAK5 Pineapple for Wireless Auditing, Ethical Hacking and Penetration Testing - Lab Manuals, CIMACS (2023).
[2] SAFE: a Standardized Automotive Forensic Engine for Law Enforcement Agencies, Communications in Computer and Information Science (CCIS), ICCET, Springer, Al-Ain, UAE (2023).
[3] Evaluating Learning Algorithms for Keystroke Based User Authentication, IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom), Istanbul, Turkey (2023).
[4] Securing Bio-FET Interfaces in IoBNT Systems using Deep Learning Techniques, 17th IEEE International Conference on Open Source Systems and Technologies (ICOSST), Lahore, PK (2023). doi: TBA
[5] Hybrid Deep Learning Techniques for Securing Bioluminescent Interfaces in Internet of Bio Nano Things, Sensors 23(21), MDPI.
[1] An automated context-aware IoT vulnerability assessment rule-set generator, Computer Communications, 133 - 152, Elsevier (2022).
[1] Perspectives on Auditing and Regulatory Compliance in Blockchain Transactions. Trust Models for Next-Generation Blockchain Ecosystems, Springer Nature Switzerland AG (2021).
A Systematic Review of Bio-Cyber Interface Technologies and Security Issues for Internet of Bio-Nano Things, 9:93529 - 93566, IEEE Access (2021).
[3] Identifying and Mitigating Phishing Attack Threats in IoT Use Cases Using a Threat Modelling Approach. Sensors 2021, 21, 4816.
[4] Anomaly Detection in Encrypted Internet Traffic using Hybrid Deep Learning. Security and Communication Networks 2021, 21.
[5] Using a Machine Learning Model for Malicious URL Type Detection. The 21st International Conference on Next Generation Wired/Wireless Networks and Systems 2021, St. Petersburg, Russia.
[6] Information Security Risk Assessment. Encyclopedia 2021, 1, 602-617.
[1] Identification of significant risks in pediatric acute lymphoblastic leukemia (ALL) through machine learning (ML) approach. Medical & Biological Engineering & Computing (2020).
[2] Towards Dynamic Hash-Based Key Establishment in Mobile Wireless Sensor Networking Nodes, IEEE INMIC 2020, Pakistan.
[1] Using Burstiness for Network Applications Classification,"Journal of Computer Networks and Communications Volume 2019, Article ID 5758437, 10 pages.
[2] On Nature-Inspired Dynamic Route Planning: Hammerhead Shark Optimization Algorithm. 15th International Conference on Emerging Technologies 2019 (ICET’19), Peshawar, Pakistan, 12/2019
[3] On MOS-Enabled Differentiated VoIP Provisioning in Campus Software Defined Networking. 15th International Conference on Emerging Technologies 2019 (ICET’19), Peshawar, Pakistan, 12/2019
[4] Securing Internet of Bio-Nano Things: ML-Enabled Parameter Profiling of Bio-Cyber Interfaces. 22nd IEEE International Multi Topic Conference 2019, Islamabad, Pakistan, 11/2019
[5] Securing Software Defined Networks: On Feasibility of Network Behaviour Profiling. International Conference On Latest trends in Electrical Engineering & Computing Technologies, Karachi, Pakistan, 11/2019
[6] Forensic of Things: Revisiting Digital Forensic Investigations in Internet of Things. 4th International Conference on Emerging Trends in Engineering, Sciences & Technology, Karachi, Pakistan, 12/2019
[7] Exploring Blockchain-Secured Data Validation in Smart Meter Readings. 22nd IEEE International Multi Topic Conference 2019, Islamabad, Pakistan, 11/2019
[8] A Novel Features Set for Internet Traffic Classification using Burstiness, Proceedings of the 5th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP, 397-404, 2019, Prague, Czech Republic.
[1] Securing wireless software defined networks: Appraising threats, defenses and research challenges, 2018 International Conference on Advancements in Computational Sciences (ICACS), Lahore, Pakistan, 2018, pp. 1-6.
[2] A Taxonomy of Ransomware Threats and Mitigation Techniques, 2018 International Conference on Computing, Mathematics and Engineering Technologies (iCOMET), Sukkur, Pakistan, 2018, pp. 1-6.
[3] Internet of Profiling - Traffic, Users and Applications,"The 12th International IEEE Conference on Communications (COMM2018), Bucharest, Romania, 2018, pp. 27-32.
[4] IoT-Enabled Smart City Waste Management using Machine Learning Analytics, The 2nd International Conference on Energy Conservation and Efficiency (IEEE ICECE 2018), Lahore, Pakistan, 2018, pp. 1-6.
[1] State-of-the-art and recent research advances in software defined networking. Wireless Communications and Mobile Computing, Volume 2017 (2017), Article ID 7191647, 35 pages. John Wiley & Sons 2017.
[2] Social engineering: Revisiting end-user awareness and susceptibility to classic attack vectors, 2017 13th International Conference on Emerging Technologies (ICET), Islamabad, 2017, pp. 1-6.
[3] Towards dynamic network policy composition and conflict resolution in software defined networking," 2017 International Conference on Information and Communication Technologies (ICICT), Karachi, Pakistan, 2017, pp. 34-39.
[4] Multi-feature Enterprise Traffic Characterization in OpenFlow-based Software Defined Networks, 2017 International Conference on Frontiers of Information Technology (FIT), Islamabad, 2017, pp. 23-28.
[5] Network Application Detection Using Traffic Burstiness, World Congress on Internet Security, Cambridge, United Kingdom, 11-14 December 2017.
[1] On Internet Traffic Classification: A Two-Phased Machine Learning Approach. Journal of Computer Networks and Communications, vol. 2016, Article ID 2048302, 21 pages, 2016. Hindawi Publishing.
[2] User-Centric Network Provisioning in Software Defined Data Center Environment, 2016 IEEE 41st Conference on Local Computer Networks (LCN), Dubai, 2016, pp. 289-297.
[3]OpenFlow-enabled user traffic profiling in campus software defined networks, 2016 IEEE 12th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), New York, NY, 2016, pp. 1-8.
[4] User-centric traffic optimization in residential software defined networks," 2016 23rd International Conference on Telecommunications (ICT), Thessaloniki, 2016, pp. 1-6.
[5] Traffic Profiling: Evaluating Stability in Multi-device User Environments, 2016 30th International Conference on Advanced Information Networking and Applications Workshops (WAINA), Crans-Montana, 2016, pp. 731-736.