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cybersecurity

1,407 papers

#cybersecurity Preprint Open access Nov 2026

Digital Security Under Compound Threats: Surveillance, Threat Reasoning, and Habituation Among North Korean Defectors in China

North Korean defectors residing in China face persistent uncertainty regarding digital security and privacy. Through semi-structured interviews with 19 defectors, we examine how individuals understand digital threats and adapt their security behaviors. We identify three interrelated conditions: transnational surveillan...

Yibo Meng, Bingyi Liu, Lionel Z. Wang et al. · 0 citations

LITMUS: Benchmarking Behavioral Jailbreaks of LLM Agents in Real OS Environments

LLM-agents In-OS Testing for Measuring Unsafe Subversion is presented, a benchmark addressing both gaps via a semantic-physical dual verification mechanism and OS-level state rollback and providing the first standardized platform for reproducible, physically grounded behavioral safety evaluation of LLM agents in real O...

Chiyu Zhang, Lu Zhou, Xiao-Gang Xu et al. · 7 citations · ⚡2
#artificial intelligence Preprint Open access Nov 2026

DUP: Detection-guided Unlearning for Backdoor Purification in Language Models

As backdoor attacks become more stealthy and robust, they reveal critical weaknesses in current defense strategies: detection methods often rely on coarse-grained feature statistics, and purification methods typically require full retraining or additional clean models. To address these challenges, we propose DUP (Detec...

Man Hu, Yahui Ding, Yatao Yang et al. · 0 citations
#artificial intelligence Preprint Open access Nov 2026

Reconciling Privacy with Provenance for Language Model Watermarks

Watermarking has great potential for regulating the use of language models (LMs), but its deployment has been marred by controversy, as many users argue that fine-grained tracking of LM usage violates their privacy. This tension reduces the effectiveness of watermarks, as users engage in evasion strategies such as para...

Elise L. Han, Tatsunori Hashimoto · 0 citations
#machine learning Preprint Open access Nov 2026

AI-Native Task-Oriented Semantic Communications over a Relay: Benefits and Vulnerabilities

Semantic communication (SemCom) using a relay node is considered, where the relay assists in conveying task-relevant information from a source to a destination, with meaning defined by classification labels. A joint end-to-end design of the source encoder, relay transformation, and destination decoders is developed to...

Yalin E. Sagduyu, Tugba Erpek, Aylin Yener · 0 citations
#machine learning Preprint Open access Nov 2026

KeHoSu: Keyed Homoglyph Substitution for Authenticated Text Provenance over Copy-Paste Channels

Nowadays, large language models produce text at scale, and much of it is redistributed across platforms. A moderator who finds a suspicious comment, post or article may want to know which platform generated it and for which account. In this paper we study attribution over the channel through which such text actually tr...

Andrei Alexandru Dr\u{a}ghici, Sediola Ruko, Briland Hitaj et al. · 0 citations
#artificial intelligence Review Aug 2026

AI Slop and Hallucinations in Vulnerability Assessment: A Survey on Reasoning Failures and Trustworthy Mitigation

A taxonomy of AI slop grounded in a structured literature review is formalized and a roadmap for securing emerging AI-driven triage systems is provided, shifting evaluation from linguistic fluency to mathematical verifiability.

Junchen Ding, Jialiang Dong, Yi Zhu et al. · 0 citations

Persona-Model Collapse in Emergent Misalignment

Fine-tuning large language models on narrow data with harmful content produces broadly misaligned behavior on unrelated prompts, a phenomenon known as emergent misalignment. We propose that emergent misalignment involves persona-model collapse: a deterioration of the internal representations that encode and distinguish...

D. B. Costa, Renato Vicente · 3 citations
#artificial intelligence Preprint Open access Nov 2026

Analysis of LLM Vulnerability to GPU Soft Errors: An Instruction-Level Fault Injection Study

Large language models (LLMs) are highly compute- and memory-intensive, posing significant demands on high-performance GPUs. At the same time, advances in GPU technology driven by shrinking transistor sizes and lower operating voltages have made these devices increasingly susceptible to soft errors, particularly in radi...

Duo Chai, Zizhen Liu, Shuhuai Wang et al. · 0 citations
#artificial intelligence Preprint Nov 2026

FedReason: Large Language Models as Weight-Space Meta-Aggregators for Heterogeneous Federated Learning

FedReason was the strongest server-side rule on CIFAR-100 but did not beat SCAFFOLD, which changes client training, and was the strongest server-side rule on CIFAR-100 but did not beat SCAFFOLD, which changes client training.

Ali Mohammadi Ruzbahani, Abbas Yazdinejad, Hadis Karimipour · 0 citations
#artificial intelligence Preprint Nov 2026

Beyond Instruction Override: Benchmarking Indirect Prompt Injection with Task-Tampering Attacks

A benchmark that makes this boundary explicit: in each of 90 validated cases across three tool-use environments, the user request specifies the source that resolves the targeted decision, and every attack tampers with a decision required by the benign task rather than replacing that task.

Rong-Ting Zhang, Martín Bertrán, Sandeep Avula et al. · 0 citations
#artificial intelligence Preprint Nov 2026

Signed but Not Safe: Requirement Integrity in Multi-Agent LLM Handoffs

A preregistered study with synthetic, exactly scorable tasks comparing free-text, structured JSON and signed requirement-manifest handoffs: the orchestrator extracts each requirement as a verbatim quote plus a checkable predicate, code signs the manifest with HMAC-SHA256, and deterministic code verifies the merger's de...

Xiao-Bo Chen, Gen-Liang Zhu, Zi-Yu Wang et al. · 0 citations

From tech blogs

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Microsoft Research Blog Nov 3, 2026

Learn the rules: The hacker mindset

Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules. The post Learn the rules: The hacker mindset appeared first on Microsoft Research.

GPT-Lab Oct 30, 2026

Black October? The Week AI Changed the Cybersecurity Conversation

Critical flaws, compromised release channels and agentic AI threats landed within days of each other in mid-October 2026. Why “Black October” may say more about how well we now find weaknesses than about the attacks themselves. The post Black October? The Week AI Changed the Cybersecurity Conversation appeared first on GPT-Lab.

Google DeepMind Blog Jul 17, 2026

Introducing Gemini 3.5 Flash Cyber

Google introduces Gemini 3.5 Flash Cyber, a lightweight cybersecurity model to find and patch vulnerabilities.

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