cyberintel.kalymoon.com · 4579 articles · updated every 4 hours · grows forever
arXiv:2606.25627v1 Announce Type: cross Abstract: Distributed intelligent systems increasingly need to train across data silos without centralizing raw data. Federated learning keeps data local but ca…
arXiv:2606.25589v1 Announce Type: cross Abstract: As graph neural networks (GNNs) become standard tools for critical tasks in circuit design and analysis, their security and privacy risks require care…
arXiv:2606.25487v1 Announce Type: cross Abstract: Almost every paper on LLM jailbreaks and prompt injection reports an attack-success rate (ASR), and that number is assigned not by people but by an au…
arXiv:2606.25422v1 Announce Type: cross Abstract: Persistent memory is a recently proposed memory paradigm that delivers many system-wide benefits, including improved runtime efficiency and the abilit…
arXiv:2606.25097v1 Announce Type: cross Abstract: Speculative decoding accelerates inference by letting a draft model propose tokens for a target model to verify, raising a concrete safety question: a…
arXiv:2606.25004v1 Announce Type: cross Abstract: In machine learning, model certification has been identified as an important method for gaining assurance about a model's trustworthiness and quality.…
arXiv:2606.26028v1 Announce Type: new Abstract: As autonomous AI agents increasingly transact across organizational boundaries, a fundamental trust challenge emerges: how can an agent assess whether a…
arXiv:2606.26021v1 Announce Type: new Abstract: Tabular foundation models are commonly assumed to present limited privacy concerns as they are often pre-trained on large collections of synthetic data.…
arXiv:2606.25998v1 Announce Type: new Abstract: Biometric authentication systems are increasingly deployed in security-critical applications, yet existing physiological and behavioral biometrics suffe…
arXiv:2606.25950v1 Announce Type: new Abstract: In our increasingly interconnected world, good IT security practices are necessary to prevent vulnerabilities and data breaches. Providing security cont…
arXiv:2606.25926v1 Announce Type: new Abstract: From a user's perspective, perhaps the most significant difference between traditional banking services and widely used blockchain-based financial syste…
arXiv:2606.25858v1 Announce Type: new Abstract: Federated learning is vulnerable to backdoor attacks in which malicious clients inject poisoned updates while preserving benign-task performance. In thi…
arXiv:2606.25750v1 Announce Type: new Abstract: Safety evaluation of large language models (LLMs) is commonly performed by querying models with unsafe or jailbreak prompts and judging whether their ou…
arXiv:2606.25734v1 Announce Type: new Abstract: Visual aimbots have emerged as a serious cheating threat in first-person shooter (FPS) games, as they evade existing anti-cheat defenses by operating on…
arXiv:2606.25721v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) systems are vulnerable to corpus poisoning attacks that manipulate model outputs through malicious retrieved docume…
arXiv:2606.25645v1 Announce Type: new Abstract: In recent years, the posting of fake news including disinformation and misinformation on social networking services (SNS) has become a social problem. T…
arXiv:2606.25622v1 Announce Type: new Abstract: The NIS-2 Directive mandates robust Risk Management from thousands of small and medium enterprises. To ensure compliance, companies rely on established …
arXiv:2606.25608v1 Announce Type: new Abstract: This paper presents a novel approach to perform semi-automated BSI IT-Grundschutz certification using a MultiLarge Language Model system (MLS) with Hybr…
arXiv:2606.25561v1 Announce Type: new Abstract: Manual formal analysis of cryptographic schemes is labor-intensive and requires substantial expertise. While model-checking tools (e.g., Scyther and Tam…
arXiv:2606.25533v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has emerged as a dominant paradigm for enhancing large language models with external knowledge. By coupling retriev…
arXiv:2606.25356v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used for automated vulnerability detection, but it remains unclear how program structure and semantics sho…
arXiv:2606.25349v1 Announce Type: new Abstract: In secure two-party Transformer inference, linear layers are typically evaluated using Fully Homomorphic Encryption (FHE) through plaintext-ciphertext o…
arXiv:2606.25332v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown promise for automated penetration testing, yet existing end-to-end black-box evaluations are highly susceptible …
arXiv:2606.25248v1 Announce Type: new Abstract: Group signatures are privacy preserving signature schemes in which a group member can anonymously sign messages on behalf of the group, while providing …