Related papers: Honeypot Protocol
Since honeypots first appeared as an advanced network security concept they suffer from poor deployment and maintenance strategies. State-of-the-Art deployment is a manual process in which the honeypot needs to be configured and maintained…
Human oversight of AI is promoted as a safeguard against risks such as inaccurate outputs, system malfunctions, or violations of fundamental rights, and is mandated in regulation like the European AI Act. Yet debates on human oversight have…
To evaluate the safety and usefulness of deployment protocols for untrusted AIs, AI Control uses a red-teaming exercise played between a protocol designer and an adversary. This paper introduces AI-Control Games, a formal decision-making…
We introduce scheming honeypot evaluations, a framework for testing whether models will pursue instrumental goals if given the opportunity. Our scheming honeypot evaluations take the form of coding tasks in Google's alignment research…
The field of AI Control seeks to develop robust control protocols, deployment safeguards for untrusted AI which may be intentionally subversive. However, existing protocols that rely on weaker monitors to detect unsafe behavior often fail…
In the field of natural language processing, the prevalent approach involves fine-tuning pretrained language models (PLMs) using local samples. Recent research has exposed the susceptibility of PLMs to backdoor attacks, wherein the…
Intrusion research frequently collects data on attack techniques currently employed and their potential symptoms. This includes deploying honeypots, logging events from existing devices, employing a red team for a sample attack campaign, or…
We study the performance of perception-based control systems in the presence of attacks, and provide methods for modeling and analysis of their resiliency to stealthy attacks on both physical and perception-based sensing. Specifically, we…
Honeypots, as a strategic cyber-deception mechanism designed to emulate authentic interactions and bait unauthorized entities, often struggle with balancing flexibility, interaction depth, and deception. They typically fail to adapt to…
A honeypot is a type of security facility deliberately created to be probed, attacked and compromised. It is often used for protecting production systems by detecting and deflecting unauthorized accesses. It is also useful for investigating…
Honeypots play a crucial role in implementing various cyber deception techniques as they possess the capability to divert attackers away from valuable assets. Careful strategic placement of honeypots in networks should consider not only…
Network honeypots are often used by information security teams to measure the threat landscape in order to secure their networks. With the advancement of honeypot development, today's medium-interaction honeypots provide a way for security…
In this paper, HTTP status codes are used as custom metrics within the HPA as the experimental scenario. By integrating the Random Forest classification algorithm from machine learning, attacks are assessed and predicted, dynamically…
Automated control monitors could play an important role in overseeing highly capable AI agents that we do not fully trust. Prior work has explored control monitoring in simplified settings, but scaling monitoring to real-world deployments…
Existing approaches to monitoring AI agents rely on supervised evaluation: human-written rules or LLM-based judges that check for known failure modes. However, novel misbehaviors may fall outside predefined categories entirely and LLM-based…
As autonomous AI agents are increasingly deployed in high-stakes environments, ensuring their safety and alignment with human values is becoming a practical deployment concern. Current benchmarks for AI agents primarily evaluate refusal of…
Activation monitoring, which probes a model's internal states using lightweight classifiers, is an emerging tool for AI safety. However, its worst-case robustness under a misalignment threat model--where a model might learn to actively…
In this age of digitalization, Internet services face more attacks than ever. An attacker's objective is to exploit systems and use them for malicious purposes. Such efforts are rising as vulnerable systems can be discovered and compromised…
The proliferation of the Internet of Things (IoT) has raised concerns about the security of connected devices. There is a need to develop suitable and cost-efficient methods to identify vulnerabilities in IoT devices in order to address…
We introduce HonestCyberEval, a new benchmark for assessing AI models' capabilities and risks in automated software exploitation, focusing on their ability to detect and exploit vulnerabilities in real-world software systems. Our evaluation…