Abstract

Active cyber defense mechanisms are necessary to perform automated, and even autonomous operations using intelligent agents that defend against modern/sophisticated AI-inspired cyber threats (e.g., ransomware, cryptojacking, deep-fakes). These intelligent agents need to rely on deep learning using mature knowledge and should have the ability to apply this knowledge in a situational and timely manner for a given AI-inspired cyber threat. In this paper, we describe a ‘domain-agnostic knowledge graph-as-a-service’ infrastructure that can support the ability to create/store domain-specific knowledge graphs for intelligent agent Apps to deploy active cyber defense solutions defending real-world applications impacted by AI-inspired cyber threats. Specifically, we present a reference architecture, describe graph infrastructure tools, and intuitive user interfaces required to construct and maintain large-scale …

Date

September 27, 2023

Authors

Prasad Calyam, Mayank Kejriwal, Praveen Rao, Jianlin Cheng, Weichao Wang, Linquan Bai, V Sriram Siddhardh Nadendla, Sanjay Madria, Sajal K Das, Rohit Chadha, Khaza Anuarul Hoque, Kannappan Palaniappan, Kiran Neupane, Roshan Lal Neupane, Sankeerth Gandhari, Mukesh Singhal, Lotfi Othmane, Meng Yu, Vijay Anand, Bharat Bhargava, Brett Robertson, Kerk Kee, Patrice Buzzanell, Natalie Bolton, Harsh Taneja

Conference

2023 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)

Pages

1-8

Publisher

IEEE