Adaptive Asymmetric Cyber Defense
Traditional static defense mechanisms are no longer sufficient to protect critical infrastructure, sensitive data, and digital assets from sophisticated adversaries.
On AI cyber conflict
Traditional static defense mechanisms are no longer sufficient to protect critical infrastructure, sensitive data, and digital assets from sophisticated adversaries.
Recent incidents have highlighted the extensive impact of supply chain attacks, affecting not only traditional software systems but also AI-specific contexts.
While cybersecurity professionals are familiar with traditional threats like data breaches and DDoS attacks, federated learning presents unique dangers, such as model hijacking and neural network trojans.
Threats and Countermeasures in Artificial Intelligence Systems
Book Review - James Johnson's "The AI Commander" offers a compelling examination of AI's transformative impact on military strategy and global security.
Navigating the complexities of AI-driven cyber conflict requires a multifaceted approach that encompasses the development of international norms, the promotion of transparency and human oversight, and investments in AI safety research.
One of the most significant challenges posed by AI is the acceleration of escalation cycles, with AI-powered cyber weapons executing attacks at machine speed, significantly compressing the time between initial intrusion and full-scale escalation¹.
This article explores the intersection of AI, cyber wargaming, and cyber ranges, detailing their synergies, benefits, challenges, and future trends.
The tension between these two perspectives on AI - as a means of control and as a force to be controlled - is central to the narrative of Dune. The novel suggests that the key to navigating this dichotomy lies in maintaining a balance between technological progress and human agency...
Enter Adversary Influence, a cutting-edge approach to asymmetric cyber defense that harnesses the power of artificial intelligence (AI) with human oversight to proactively manipulate and mislead attackers, fundamentally altering the dynamics of cybersecurity.
This article explores the shift from traditional defense-in-depth strategies to a more proactive, AI-driven approach: deception-in-depth.
To address these challenges, researchers and practitioners are exploring innovative approaches like Asymmetric Cyber Defense and dual deception. These strategies aim to proactively mislead and manipulate attackers, effectively turning their own tactics against them (Fugate & Ferguson-Walter, 2019).