TL;DR
A domain-adapted NER framework that combines a fine-tuned robustly optimised BERT pretraining approach encoder with a bidirectional long short-term memory layer to capture both long and short patterns in threat reports, demonstrating the framework’s value for real-world CTI analysis and automated cyber defense.
The results indicate that the hybrid RNN–BiLSTM architecture can be used to efficiently perform proactive vulnerability detection and is also applicable to enable real-time cybersecurity monitoring and the use of automatically possible counter efforts in contemporary software systems.
The rapid evolution of cyber-threats, including Advanced Persistent Threats (APTs) and dynamic malware strains, has made signature-based defense techniques obsolete. Proactive Cyber Threat Intelligence (CTI) and autonomous host-based detection have emerged as critical paradigms to circumvent modern threats before any s...
The dynamic nature of cyber threats—particularly minority-class and zero-day attacks—poses significant challenges to existing intrusion detection systems (IDS), which often lack adaptability, interpretability, and robustness. This paper presents X-THREAT, an adaptive and explainable deep learning framework designed to...
TTP-R1 is proposed, a two-stage framework that combines retrieval-augmented supervised fine-tuning (SFT) with reinforcement learning using verifiable rewards (RLVR) and applies Group Relative Policy Optimization with a decomposed reward that directly supervises the precision, recall, and output format of the predicted...
STINER, a taxonomy and expert-annotated corpus for extracting strategic intelligence from social media streams is introduced, and how social-media-driven extraction can surface early signals of the SafePay ransomware campaign prior to its retrospective characterization in vendor threat landscape reports is illustrated.
The rapid evolution of intelligent engineering networks, driven by interconnected systems, automation, and data-centric infrastructures, has significantly increased their exposure to sophisticated cyber threats that are often dynamic, adaptive, and difficult to detect using conventional security mechanisms. This resear...
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