Publications

📝 Saha, B., Rani, N., & Shukla, S. K. (2024). MAD: A Meta-Learning Approach to Detect Advanced Persistent Threats using Provenance Data in Industrial IoT. Accepted at Workshop on AI for Cyber Threat Intelligence (WAITI) 2024 co-located with the Annual Computer Security Applications Conference (ACSAC24). [Paper]

📝 Rani, N., Saha, B., Maurya, V., & Shukla, S. K. (2024). Chasing the Shadows: TTPs in Action to Attribute Advanced Persistent Threats. arXiv preprint arXiv:2409.16400. [Paper]

📝 Rani, N., Saha, B., & Shukla, S. K. (2024). A Comprehensive Survey of Advanced Persistent Threat Attribution: Taxonomy, Methods, Challenges and Open Research Problems. arXiv preprint arXiv:2403.03267. [Paper]

📝 Rani, N., Saha, B., Maurya, V., & Shukla, S. K. (2024). Genesis of Cyber Threats: Towards Malware-based Advanced Persistent Threat (APT) Attribution. Accepted in IEEE TPS 2024. [Paper] [Code & Dataset]

📝 Rani, N., Saha, B., Maurya, V., & Shukla, S. K. (2024). TTPXHunter: Actionable Threat Intelligence Extraction as TTPs from Finished Cyber Threat Reports. Digital Threats: Research and Practice. [Q1]   [Paper] [Code & Dataset]

📝 Saha, B., Rani, N., & Shukla, S. K. (2023, August). MalXCap: A Method for Malware Capability Extraction. In International Conference on Information Security Practice and Experience (pp. 230-249). Singapore: Springer Nature Singapore. [Core: B Ranked] [Paper]

📝 Rani, N., Saha, B., Maurya, V., & Shukla, S. K. (2023). TTPHunter: automated extraction of actionable intelligence as TTPs from narrative threat reports. In Proceedings of the 2023 Australasian Computer Science Week (pp. 126-134). [Core: Australasian B Ranked] [Paper] [Code & Dataset]