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Related papers: Kinetic and Cyber

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We analyze two open source deep reinforcement learning agents submitted to the CAGE Challenge 2 cyber defense challenge, where each competitor submitted an agent to defend a simulated network against each of several provided rules-based…

Cryptography and Security · Computer Science 2025-06-11 Jared Claypoole , Steven Cheung , Ashish Gehani , Vinod Yegneswaran , Ahmad Ridley

Computer Use Agents (CUAs), autonomous systems that interact with software interfaces via browsers or virtual machines, are rapidly being deployed in consumer and enterprise environments. These agents introduce novel attack surfaces and…

Cybernetic avatars (CAs) are key components of an avatar-symbiotic society, enabling individuals to overcome physical limitations through virtual agents and robotic assistants. While semi-autonomous CAs intermittently require human…

A real time portal (www.ganamoscybersecure.org) to enlighten people on how to protect their data in the web, the strategies adopted by cyber criminals to succeed in exploiting their victims as well as the mistakes made by people and…

Computers and Society · Computer Science 2019-10-25 Moses Adah Agana , Bassey Igbo Ele

Computer-Using Agents (CUAs) aim to autonomously operate computer systems to complete real-world tasks. However, existing agentic systems remain difficult to scale and lag behind human performance. A key limitation is the absence of…

The massive proliferation of social media data represents a transformative opportunity for conflict studies and for tracking the proliferation and use of weaponry, as conflicts are increasingly documented in these online spaces. At the same…

Computers and Society · Computer Science 2025-05-29 Afia Abedin , Abdul Bais , Cody Buntain , Laura Courchesne , Brian McQuinn , Matthew E. Taylor , Muhib Ullah

After more than two decades of discussion, the concept of cyberterrorism remains plagued by confusion. This article presents the result of an integrative review which maps the development of the term and situates the epistemic communities…

Computers and Society · Computer Science 2020-12-17 Vince J. Straub

Attention to the very physical aspects of information characterizes the current research in quantum computation, quantum cryptography and quantum communication. In most of the cases quantum description of the system provides advantages over…

Quantum Physics · Physics 2016-09-08 Edward W. Piotrowski , Jan Sladkowski

This chapter introduces the concept of Autonomous Intelligent Cyber-defense Agents (AICAs), and briefly explains the importance of this field and the motivation for its emergence. AICA is a software agent that resides on a system, and is…

Cryptography and Security · Computer Science 2023-04-26 Alexander Kott

Deep reinforcement learning (RL) is emerging as a viable strategy for automated cyber defense (ACD). The traditional RL approach represents networks as a list of computers in various states of safety or threat. Unfortunately, these models…

Machine Learning · Computer Science 2025-09-22 Isaiah J. King , Benjamin Bowman , H. Howie Huang

The last few years have seen an explosion of interest in autonomous cyber defence agents based on deep reinforcement learning. Such agents are typically trained in a cyber gym environment, also known as a cyber simulator, at least 32 of…

Machine Learning · Computer Science 2025-03-11 Elizabeth Bates , Chris Hicks , Vasilios Mavroudis

Concerns for the resilience of Cyber-Physical Systems (CPS)s in critical infrastructure are growing. CPS integrate sensing, computation, control, and networking into physical objects and mission-critical services, connecting traditional…

Cryptography and Security · Computer Science 2024-05-20 Mariana Segovia-Ferreira , Jose Rubio-Hernan , Ana Rosa Cavalli , Joaquin Garcia-Alfaro

Kinetic equations bridge the gap between a microscopic description and a macroscopic description of the physical reality. Due to the high dimensionality the construction of numerical methods represents a challenge and requires a careful…

Numerical Analysis · Mathematics 2013-12-02 Lorenzo Pareschi

Future warfare will occur in more complex, fast-paced, ill-structured, and demanding conditions that will stress current Command and Control (C2) systems. Without modernization, these C2 systems may fail to maintain overmatch against…

Modeling and simulation are widely used in cybersecurity research to assess cyber threats, evaluate defense mechanisms, and analyze vulnerabilities. However, the diversity of application areas, the variety of cyberattacks scenarios, and the…

Cryptography and Security · Computer Science 2025-08-11 Luca Serena , Gabriele D'Angelo , Stefano Ferretti , Moreno Marzolla

Behaviors of the synthetic characters in current military simulations are limited since they are generally generated by rule-based and reactive computational models with minimal intelligence. Such computational models cannot adapt to…

Artificial Intelligence · Computer Science 2021-01-07 Volkan Ustun , Rajay Kumar , Adam Reilly , Seyed Sajjadi , Andrew Miller

Hierarchical Reinforcement Learning has been previously shown to speed up the convergence rate of RL planning algorithms as well as mitigate feature-based model misspecification (Mankowitz et. al. 2016a,b, Bacon 2015). To do so, it utilizes…

Artificial Intelligence · Computer Science 2016-10-11 Daniel J. Mankowitz , Aviv Tamar , Shie Mannor

This review explores the academic and policy literature in the context of everyday cyber security in organisations. In so doing, it identifies four behavioural sets that influences how people practice cyber security. These are compliance…

Computers and Society · Computer Science 2020-04-27 Amy Ertan , Georgia Crossland , Claude Heath , David Denny , Rikke Jensen

This study examines the strategic role of cybersecurity based on survey data from 1,083 managers across Europe, the UK, and the United States. The findings indicate growing recognition of cybersecurity as a source of competitive advantage,…

Cryptography and Security · Computer Science 2025-05-21 Silvia Tedeschi , Giacomo Marzi , Marco Balzano , Gabriele Costa

Synthetic data has emerged as a cost-effective alternative to real data for training artificial neural networks (ANN). However, the disparity between synthetic and real data results in a domain gap. That gap leads to poor performance and…

Machine Learning · Computer Science 2025-09-03 Paul Wachter , Lukas Niehaus , Julius Schöning