Robust and Efficient AI-Based Attack Recovery in Autonomous Drones

We introduce an autonomous attack recovery architecture to add common sense reasoning to plan a recovery action after an attack is detected. We outline use-cases of our architecture using drones, and then discuss how to implement this architecture efficiently and securely in edge devices...

On the Day They Experience: Awakening Self-Sovereign Experiential AI Agents

Drawing on Andrew Parker's "Light Switch" theory-which posits that the emergence of vision ignited a Cambrian explosion of life by driving the evolution of hard parts necessary for survival and fueling an evolutionary arms race between predators and prey-this essay speculates on an analogous...

D4+: Emergent Adversarial Driving Maneuvers with Approximate Functional Optimization

Intelligent mechanisms implemented in autonomous vehicles, such as proactive driving assist and collision alerts, reduce traffic accidents. However, verifying their correct functionality is difficult due to complex interactions with the environment. This problem is exacerbated in adversarial...

Neuromorphic Mimicry Attacks Exploiting Brain-Inspired Computing for Covert Cyber Intrusions

Neuromorphic computing, inspired by the human brain's neural architecture, is revolutionizing artificial intelligence and edge computing with its low-power, adaptive, and event-driven designs. However, these unique characteristics introduce novel cybersecurity risks. This paper proposes...

Coordinated Intelligence: The Next Frontier for Onchain AI Agents

Disciplined, well-trained, and well-equipped, AI agents are digital soldiers. They operate independently to carry out their orders, working…...

DeFeed: Secure Decentralized Cross-Contract Data Feed in Web 3.0 for Connected Autonomous Vehicles

Smart contracts have been a topic of interest in blockchain research and are a key enabling technology for Connected Autonomous Vehicles CAVs in the era of Web 3.0. These contracts enable trustless interactions without the need for intermediaries, as they operate based on predefined rules encoded...

Friday Squid Blogging: Pet Squid Simulation

From Hackaday.com, this is a neural network simulation of a pet squid. Autonomous Behavior: The squid moves autonomously, making decisions based on his current state hunger, sleepiness, etc.. Implements a vision cone for food detection, simulating realistic foraging behavior. Neural network can...

Unveiling the Black Box: a Multi-Layer Framework for Explaining Reinforcement Learning-Based Cyber Agents

Reinforcement Learning RL agents are increasingly used to simulate sophisticated cyberattacks, but their decision-making processes remain opaque, hindering trust, debugging, and defensive preparedness. In high-stakes cybersecurity contexts, explainability is essential for understanding how...

DMind Benchmark: toward a Holistic Assessment of LLM Capabilities across the Web3 Domain

Large Language Models LLMs have achieved impressive performance in diverse natural language processing tasks, but specialized domains such as Web3 present new challenges and require more tailored evaluation. Despite the significant user base and capital flows in Web3, encompassing smart contracts...

A Survey of Learning-Based Intrusion Detection Systems for In-Vehicle Network

Connected and Autonomous Vehicles CAVs enhance mobility but face cybersecurity threats, particularly through the insecure Controller Area Network CAN bus. Cyberattacks can have devastating consequences in connected vehicles, including the loss of control over critical systems, necessitating robus...

AutoPentest: Enhancing Vulnerability Management with Autonomous LLM Agents

A recent area of increasing research is the use of Large Language Models LLMs in penetration testing, which promises to reduce costs and thus allow for higher frequency. We conduct a review of related work, identifying best practices and common evaluation issues. We then present AutoPentest, an...

Security, Uninterrupted: Inside Qualys’ Zero-Touch Security Vision with Qualys Cloud Agent

New Feature: Remote Log Collection for Seamless Troubleshooting and Analysis In the modern enterprise, where resilience and scale are non-negotiable, the margin for error in cybersecurity has all but disappeared. Yet the tools available to security teams remain tethered to legacy...

Large Language Models Are Autonomous Cyber Defenders

Fast and effective incident response is essential to prevent adversarial cyberattacks. Autonomous Cyber Defense ACD aims to automate incident response through Artificial Intelligence AI agents that plan and execute actions. Most ACD approaches focus on single-agent scenarios and leverage...

Impact Analysis of Inference Time Attack of Perception Sensors on Autonomous Vehicles

As a safety-critical cyber-physical system, cybersecurity and related safety issues for Autonomous Vehicles AVs have been important research topics for a while. Among all the modules on AVs, perception is one of the most accessible attack surfaces, as drivers and AVs have no control over the...

Balancing Security and Liquidity: a Time-Weighted Snapshot Framework for DAO Governance Voting

As new project upgrading the blockchain industry, novel forms of attack challenges developers to rethink about the design of their innovations. In the growth stage of the development, Decentralized Autonomous Organizations DAO introduces different approaches in managing fund through voting in...

Risk Assessment and Threat Modeling for Safe Autonomous Driving Technology

This research paper delves into the field of autonomous vehicle technology, examining the vulnerabilities inherent in each component of these transformative vehicles. Autonomous vehicles AVs are revolutionizing transportation by seamlessly integrating advanced functionalities such as sensing,...

Securing Agentic AI: a Comprehensive Threat Model and Mitigation Framework for Generative AI Agents

As generative AI GenAI agents become more common in enterprise settings, they introduce security challenges that differ significantly from those posed by traditional systems. These agents are not just LLMs; they reason, remember, and act, often with minimal human oversight. This paper introduces ...

Firewall Regulatory Networks for Autonomous Cyber Defense

In this paper, we present the principles of designing new self-organising and autonomous management protocol to govern the dynamics of bio-inspired decentralized firewall architecture based on Biological Regularity Networks. The new architecture called Firewall Regulatory Networks FRN exhibits th...

Trustworthy Decentralized Autonomous Machines: a New Paradigm in Automation Economy

Decentralized Autonomous Machines DAMs represent a transformative paradigm in automation economy, integrating artificial intelligence AI, blockchain technology, and Internet of Things IoT devices to create self-governing economic agents participating in Decentralized Physical Infrastructure...

Quantum Computing Supported Adversarial Attack-Resilient Autonomous Vehicle Perception Module for Traffic Sign Classification

Deep learning DL-based image classification models are essential for autonomous vehicle AV perception modules since incorrect categorization might have severe repercussions. Adversarial attacks are widely studied cyberattacks that can lead DL models to predict inaccurate output, such as incorrect...