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arXiv:2604.19438v1 Announce Type: new Abstract: Pre-trained machine learning models (PTMs) are commonly provided via Model Hubs (e.g., Hugging Face) in standard formats like Pickles to facilitate acce…
arXiv:2604.19422v1 Announce Type: new Abstract: With the growing use of eye tracking on VR and mobile platforms, gaze data is increasing. While scanpath comparison is important to gaze behavior analys…
arXiv:2604.19219v1 Announce Type: new Abstract: Federated Learning (FL) enables collaborative model training among multiple parties without centralizing raw data. There are two main paradigms in FL: H…
arXiv:2604.19118v1 Announce Type: new Abstract: Modern distributed systems generate massive volumes of log data that are critical for detecting anomalies and cyber threats. However, in real world sett…
arXiv:2604.19090v1 Announce Type: new Abstract: The rapid adoption of diffusion-based generative models has intensified concerns over the attribution and integrity of AI-generated content (AIGC). Exis…
arXiv:2604.19083v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable success in cross-modal understanding and generation, yet their deployment is threatene…
arXiv:2604.19053v1 Announce Type: new Abstract: We propose CHRONOS, a hardware-assisted framework that decouples the cryptographic setup required for private gradient aggregation from the active train…
arXiv:2604.19049v1 Announce Type: new Abstract: LLM-assisted defect discovery has a precision crisis: plausible-but-wrong reports overwhelm maintainers and degrade credibility for real findings. We pr…
arXiv:2604.19031v1 Announce Type: new Abstract: Software vulnerabilities are a primary threat to modern infrastructure. While static analysis and Graph Neural Networks have long served as the foundati…
arXiv:2604.19012v1 Announce Type: new Abstract: Deep learning for vulnerability detection has shown promising results on early benchmarks, but recent evaluations reveal catastrophic degradation: model…
arXiv:2604.18860v1 Announce Type: new Abstract: GUI agents that control desktop computers via screenshot-and-click loops introduce a new class of vulnerability: the observation-to-action gap (mean 6.5…
arXiv:2604.18819v1 Announce Type: new Abstract: The integration of Fog Computing with Flying Ad-Hoc Networks (FANETs) offers promising capabilities for decentralized, low-latency intelligence in UAV-b…
arXiv:2604.18718v1 Announce Type: new Abstract: Agentic security systems increasingly audit live targets with tool-using LLMs, but prior systems fix a single coordination topology, leaving unclear whe…
arXiv:2604.18717v1 Announce Type: new Abstract: Formal verification of masking in post-quantum cryptographic (PQC) hardware relies on SMT solvers over finite domains. Our prior work established struct…
arXiv:2604.18716v1 Announce Type: new Abstract: Today, machine learning is widely applied in sensitive, security-related, and financially lucrative applications. Model extraction attacks undermine cur…
arXiv:2604.18697v1 Announce Type: new Abstract: Indistinguishability properties such as differential privacy bounds or low empirically measured membership inference are widely treated as proxies to sh…
arXiv:2604.18663v1 Announce Type: new Abstract: Existing jamming attacks on Retrieval-Augmented Generation (RAG) systems typically induce explicit refusals or denial-of-service behaviors, which are co…
arXiv:2604.18660v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used in education, yet their default helpfulness often conflicts with pedagogical principles. Prior work e…
arXiv:2604.18658v1 Announce Type: new Abstract: Existing AI agent safety benchmarks focus on generic criminal harm (cybercrime, harassment, weapon synthesis), leaving a systematic blind spot for a dis…
arXiv:2604.18652v1 Announce Type: new Abstract: The transition of agentic AI from brittle prototypes to production systems is stalled by a pervasive crisis of craft. We suggest that the prevailing orc…
arXiv:2604.18649v1 Announce Type: new Abstract: As generative AI faces intensifying legal challenges, the machine learning community has increasingly relied on post-hoc mitigation -- especially machin…
arXiv:2604.18633v1 Announce Type: new Abstract: Web tracking by ad networks, social networks, and other third parties is privacy-invasive. To protect users' privacy an increasing number of countries a…
&#;x26;#;x5b;This is a Guest Diary by L. Carty, an ISC intern as part of the SANS.edu Bachelor&#;x26;#;39;s Degree in Applied Cybersecurity (BACS) program &#;x26;#;x5b;1].]