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arXiv:2604.21436v1 Announce Type: new Abstract: Similar to a strategic interaction between rational and intelligent agents, cryptography problems can be examined through the prism of game theory. In t…
arXiv:2604.21421v1 Announce Type: new Abstract: Protecting patient privacy in clinical narratives is essential for enabling secondary use of healthcare data under regulations such as GDPR and HIPAA. W…
arXiv:2604.21416v1 Announce Type: new Abstract: Poisoning-based backdoor attacks pose significant threats to deep neural networks by embedding triggers in training data, causing models to misclassify …
arXiv:2604.21394v1 Announce Type: new Abstract: Steganography embeds secret messages in seemingly innocuous carriers for covert communication under surveillance. Current Provably Secure Steganography …
arXiv:2604.21310v1 Announce Type: new Abstract: Deep learning has emerged as a powerful approach for malware detection, demonstrating impressive accuracy across various data representations. However, …
arXiv:2604.21308v1 Announce Type: new Abstract: Enterprise LLM agents can dramatically improve workplace productivity, but their core capability, retrieving and using internal context to act on a user…
arXiv:2604.21282v1 Announce Type: new Abstract: Automated code vulnerability detection is critical for software security, yet existing approaches face a fundamental trade-off between detection accurac…
arXiv:2604.21261v1 Announce Type: new Abstract: This paper presents ECCFROG522PP, a 522-bit prime-field elliptic curve in short Weierstrass form, designed with a focus on deterministic generation and …
arXiv:2604.21188v1 Announce Type: new Abstract: The rapid integration of artificial intelligence (AI) into Internet of Things (IoT) and edge computing systems has intensified the need for robust, hard…
arXiv:2604.21169v1 Announce Type: new Abstract: In Ethereum, transaction-bundling services are a critical component of block builders, such as Flashbots Bundles, and are widely used by MEV searchers. …
arXiv:2604.21159v1 Announce Type: new Abstract: Many approaches to LLM red-teaming leverage an attacker LLM to discover jailbreaks against a target. Several of them task the attacker with identifying …
arXiv:2604.21153v1 Announce Type: new Abstract: This paper studies 43-class malware type classification on MalNet-Image Tiny, a public benchmark derived from Android APK files. The goal is to assess w…
arXiv:2604.21131v1 Announce Type: new Abstract: AI-agent guardrails are memoryless: each message is judged in isolation, so an adversary who spreads a single attack across dozens of sessions slips pas…
arXiv:2604.21083v1 Announce Type: new Abstract: Third-party Large Language Model (LLM) API gateways are rapidly emerging as unified access points to models offered by multiple vendors. However, the in…
arXiv:2604.21055v1 Announce Type: new Abstract: Layer-2 (L2) protocols address the fundamental limitations of Layer-1 (L1) blockchains by offloading computation while anchoring trust to the parent cha…
arXiv:2604.21001v1 Announce Type: new Abstract: Password-based authentication is one of the most commonly used methods for verifying user identities, and its widespread usage continues in virtual real…
arXiv:2604.20994v1 Announce Type: new Abstract: The growth of agentic AI has drawn significant attention to function calling Large Language Models (LLMs), which are designed to extend the capabilities…
arXiv:2604.20945v1 Announce Type: new Abstract: Effective safety auditing of large language models (LLMs) demands tools that go beyond black-box probing and systematically uncover vulnerabilities root…
arXiv:2604.20934v1 Announce Type: new Abstract: Software-Defined Networking (SDN) is another technology that has been developing in the last few years as a relevant technique to improve network progra…
arXiv:2604.20932v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) systems are increasingly deployed in sensitive domains such as healthcare and law, where they rely on private, doma…
arXiv:2604.20930v1 Announce Type: new Abstract: Internal Safety Collapse (ISC) is a failure mode in which frontier LLMs, when executing legitimate professional tasks whose correct completion structura…
arXiv:2604.20927v1 Announce Type: new Abstract: Preprints are essential for the timely and open dissemination of research. arXiv, the most widely used preprint service, takes the idea of open science …
arXiv:2604.20911v1 Announce Type: new Abstract: LLM agents deployed in production operate under operator-defined behavioral policies (system-prompt instructions such as prohibitions on credential disc…
arXiv:2604.20903v1 Announce Type: new Abstract: We propose Sensitivity-Uncertainty Alignment (SUA), a framework for analyzing failures of large language models under adversarial and ambiguous inputs. …