Related papers: AI-Driven Cyber Threat Intelligence Automation
Understanding the modus operandi of adversaries aids organizations in employing efficient defensive strategies and sharing intelligence in the community. This knowledge is often present in unstructured natural language text within threat…
There is no denying that the use of Information Technology (IT) is undergoing exponential growth in today's world. This digital transformation has also given rise to a multitude of security challenges, notably in the realm of cybercrime. In…
The cybersecurity threat landscape has lately become overly complex. Threat actors leverage weaknesses in the network and endpoint security in a very coordinated manner to perpetuate sophisticated attacks that could bring down the entire…
Over the last decade, Artificial Intelligence (AI) has become increasingly popular, especially with the use of chatbots such as ChatGPT, Gemini, and DALL-E. With this rise, large language models (LLMs) and Generative AI (GenAI) have also…
This review comprehensively examines the integration of artificial intelligence (AI) in enhancing the dynamic security assessments of modern power systems. It highlights the pivotal role of AI in facilitating scenario generation, incident…
By 2028 most cybersecurity actions will be autonomous, with humans teleoperating. We present the first classification of autonomy levels in cybersecurity and introduce Cybersecurity AI (CAI), an open-source framework that democratizes…
Despite the high volume of open-source Cyber Threat Intelligence (CTI), our understanding of long-term threat actor-victim dynamics remains fragmented due to inconsistent reporting standards and the lack of structured datasets containing…
As our cities and communities become smarter, the systems that keep us safe, such as traffic control centers, emergency response networks, and public transportation, also become more complex. With this complexity comes a greater risk of…
In Industry 4.0, Cyber-Physical Systems (CPS) generate vast data sets that can be leveraged by Artificial Intelligence (AI) for applications including predictive maintenance and production planning. However, despite the demonstrated…
Security provisioning has become the most important design consideration for large-scale Internet of Things (IoT) systems due to their critical roles to support diverse vertical applications by connecting heterogenous devices, machines and…
The complexity of modern computing environments and the growing sophistication of cyber threats necessitate a more robust, adaptive, and automated approach to security enforcement. In this paper, we present a framework leveraging large…
Traditional static cybersecurity models often struggle with scalability, real-time detection, and contextual responsiveness in the current digital product ecosystems which include cloud services, application programming interfaces (APIs),…
Cyber threat intelligence is the provision of evidence-based knowledge about existing or emerging threats. Benefits from threat intelligence include increased situational awareness, efficiency in security operations, and improved…
Log-based cyber threat hunting has emerged as an important solution to counter sophisticated cyber attacks. However, existing approaches require non-trivial efforts of manual query construction and have overlooked the rich external…
CTI-REALM (Cyber Threat Real World Evaluation and LLM Benchmarking) is a benchmark designed to evaluate AI agents' ability to interpret cyber threat intelligence (CTI) and develop detection rules. The benchmark provides a realistic…
The traditional production paradigm of large batch production does not offer flexibility towards satisfying the requirements of individual customers. A new generation of smart factories is expected to support new multi-variety and…
The workshop will focus on the application of AI to problems in cyber security. Cyber systems generate large volumes of data, utilizing this effectively is beyond human capabilities. Additionally, adversaries continue to develop new…
The accelerating advancements in Artificial Intelligence (AI) and Machine Learning (ML), highlighted by the development of cutting-edge Generative Pre-trained Transformer (GPT) models by organizations such as OpenAI, Meta, and Anthropic,…
Intrusion Detection Systems (IDS) are a proven approach to secure networks. However, in a privately used network, it is difficult for users without cybersecurity expertise to understand IDS alerts, and to respond in time with adequate…
The new generation of cyber threats leverages advanced AI-aided methods, which make them capable to launch multi-stage, dynamic, and effective attacks. Current cyber-defense systems encounter various challenges to defend against such new…