Cyber Threat Intelligence
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Schema-Agnostic Knowledge Graph Construction via Hybrid Ontology Discovery for Cyber Threat Intelligence
arXiv:2606.01208v1 Announce Type: new Abstract: Cyber threat intelligence (CTI) reports now serve as essential resources for capturing adversary tactics, techniques, and procedures observed in modern attack campaigns. While traditional CTI platforms reduce this intelligence to isolated indicators through fixed schemas such as STIX, ontology-based representations preserve the semantic relationships needed for structured threat analysis. However, existing approaches for ontology-aligned CTI...
CTIConnect: A Benchmark for Retrieval-Augmented LLMs over Heterogeneous Cyber Threat Intelligence
arXiv:2510.11974v2 Announce Type: replace Abstract: Cyber Threat Intelligence (CTI) is foundational to modern cybersecurity, enabling organizations to proactively defend against evolving threats. However, the sheer volume and heterogeneity of CTI data, spanning structured knowledge bases (CVE, CWE, CAPEC, MITRE ATT&CK) and unstructured threat reports, far exceed the capacity of manual analysis. The strong contextual understanding and reasoning of Large Language Models (LLMs) have driven...
TIBlender: Early-Warning Threat Intelligence from Cross-Platform Social Media Evidence
Announce Type: new Abstract: Cyber threat signals are fragmented across multiple social media platforms, yet no existing approach has fully automated their integration into actionable threat intelligence (TI) reports. We present TIBlender, a multi-agent system that monitors four platforms (X, Reddit, Telegram, and Discord) and produces structured TI reports via role-specialized LLM agents. These agents conduct multi-perspective investigations, tracing chains of evidence to uncover related...
Cognitive Threat Intelligence and Explainable Federated Security Analytics for distributed Infrastructure Systems
arXiv:2606.05701v1 Announce Type: new Abstract: The increasing adoption of distributed infrastructure systems, cloud computing, Internet of Things (IoT) technologies, and edge-based architectures has significantly expanded the cybersecurity attack surface and introduced increasingly sophisticated cyber threats. Conventional centralized intrusion detection approaches often face challenges related to scalability, data privacy, communication overhead, and limited transparency in artificial...
Hybrid CNN-LSTM Framework for Intelligent Cyber Attack Detection and Prevention in U.S. Critical Digital Infrastructure: A Comparative Machine Learning Evaluation on CSE-CIC-IDS2018
Announce Type: new Abstract: Digital infrastructure is growing at a rapid pace in the United States, and as a result, exposure to advanced cyber threats to critical sectors including healthcare, finance, transportation, energy and government systems is growing. The traditional cybersecurity approaches, including signature-based intrusion detection systems, have become less effective against today's cyber attacks, as they are unable to detect unknown and changing attacks in real time. To...
TinyML-Driven Cybersecurity for Autonomous Spacecraft: Latency-Accuracy Analysis for SPARTA RF and Cyber Threat Detection
Announce Type: new Abstract: Autonomous spacecraft require rapid, lightweight, and reliable onboard detection of cyber-RF threats. Using the SPARTA attack model, we analyze the latency-accuracy trade-offs of TinyML-compatible classical models -- Random Forest, Logistic Regression, SVM, and MLP -- for detecting uplink jamming, Fake-NR spoofing, payload manipulation, ground-segment compromise, and unauthorized command injection.
Blockchain Infrastructure for Intelligent Cyber--Physical--Social Systems:Post-Quantum Security, Interoperability, and Trustworthy Data Economies in the Era of Embodied AI
Announce Type: new Abstract: The deployment of embodied artificial intelligence via world-model-based robotics presents a transformative opportunity for blockchain infrastructure, establishing urgent demand for trustworthy data provenance, cross-organizational governance, and incentive-compatible sharing across decentralized ecosystems. Simultaneously, quantum computing advances recognized by the 2025 Nobel Prize in Physics and the Turing Award threaten the cryptographic primitives securing...
US shortens cyber fix window to three days as AI threats rise
US shortens cyber fix window to three days as AI threats rise WASHINGTON, June 10 : The U.S. cyber defense agency said on Wednesday that government officials now have three days to deal with the most serious categories of digital vulnerabilities in their networks, a compressed timeline that is due in part to hackers' use of artificial intelligence. The deadline, which was set in a new directive issued by the Cybersecurity and Infrastructure Security Agency, obligates civilian federal...
AutoSUT: The Environment Semantics Gap in Structured CTI for Adversary Emulation
Announce Type: new Abstract: Structured Cyber Threat Intelligence (CTI) is increasingly used for adversary emulation, detection evaluation, and cyber range design. However, these workflows still require a target System Under Test (SUT) whose environment is not fully described by public CTI. We measure how much of that environment can be derived from MITRE ATT&CK Structured Threat Information Expression (STIX) bundles.
Synthetic APTs: the Collapse of TTP-Based Attribution
Announce Type: new Abstract: Cyber Threat Intelligence CTI attribution relies on identifying the Tactics, Techniques, and Procedures TTPs that distinguish one threat actor from another. This approach presupposes that each adversary leaves a recognizable operational fingerprint. This work investigates whether AI driven adversary emulation challenges that presupposition.