Image de couverture de livre

Rethinking Autonomy: Preventing Failures in AI-Driven Software Engineering

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Navneet, Satyam Kumar, Chandra, Joydeep
Format:	Preprint
Publié:	2025
Sujets:	Software Engineering Artificial Intelligence Cryptography and Security Performance
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation
par: Chandra, Joydeep, et autres
Publié: (2025)

Investigating Detection and Obfuscation of Prompt Injection Attacks Against Software Reverse Engineering AI Agents
par: Crawford, Brian, et autres
Publié: (2026)

Data and Context Matter: Towards Generalizing AI-based Software Vulnerability Detection
par: Safdar, Rijha, et autres
Publié: (2025)

DevOps-Gym: Benchmarking AI Agents in Software DevOps Cycle
par: Tang, Yuheng, et autres
Publié: (2026)

LinuxArena: A Control Setting for AI Agents in Live Production Software Environments
par: Tracy, Tyler, et autres
Publié: (2026)

SOK: Exploring Hallucinations and Security Risks in AI-Assisted Software Development with Insights for LLM Deployment
par: Haque, Ariful, et autres
Publié: (2025)

Securing the Future of IVR: AI-Driven Innovation with Agile Security, Data Regulation, and Ethical AI Integration
par: Shaikh, Khushbu Mehboob, et autres
Publié: (2025)

Safety and Performance, Why Not Both? Bi-Objective Optimized Model Compression against Heterogeneous Attacks Toward AI Software Deployment
par: Zhu, Jie, et autres
Publié: (2024)

From Detection to Prevention: Explaining Security-Critical Code to Avoid Vulnerabilities
par: Krishnamurthy, Ranjith, et autres
Publié: (2026)

Rethinking and Exploring String-Based Malware Family Classification in the Era of LLMs and RAG
par: Chen, Yufan, et autres
Publié: (2025)

AdaptiveGuard: Towards Adaptive Runtime Safety for LLM-Powered Software
par: Yang, Rui, et autres
Publié: (2025)

Bridging Semantics & Structure for Software Vulnerability Detection using Hybrid Network Models
par: Gajjar, Jugal, et autres
Publié: (2025)

Automatically Generating Rules of Malicious Software Packages via Large Language Model
par: Zhang, XiangRui, et autres
Publié: (2025)

Co-PatcheR: Collaborative Software Patching with Component(s)-specific Small Reasoning Models
par: Tang, Yuheng, et autres
Publié: (2025)

Harnessing Large Language Models for Software Vulnerability Detection: A Comprehensive Benchmarking Study
par: Tamberg, Karl, et autres
Publié: (2024)

A Qualitative Study on Using ChatGPT for Software Security: Perception vs. Practicality
par: Kholoosi, M. Mehdi, et autres
Publié: (2024)

EaTVul: ChatGPT-based Evasion Attack Against Software Vulnerability Detection
par: Liu, Shigang, et autres
Publié: (2024)

Reflection-Driven Control for Trustworthy Code Agents
par: Wang, Bin, et autres
Publié: (2025)

Benchmarking Prompt Engineering Techniques for Secure Code Generation with GPT Models
par: Bruni, Marc, et autres
Publié: (2025)

Options, Not Clicks: Lattice Refinement for Consent-Driven MCP Authorization
par: Li, Ying, et autres
Publié: (2026)

SKILLS: Structured Knowledge Injection for LLM-Driven Telecommunications Operations
par: Brett, Ivo
Publié: (2026)

A sketch of an AI control safety case
par: Korbak, Tomek, et autres
Publié: (2025)

AI security and cyber risk in IoT systems
par: Radanliev, Petar, et autres
Publié: (2024)

AI Code Generators for Security: Friend or Foe?
par: Natella, Roberto, et autres
Publié: (2024)

Semantic-Aware Fuzzing: An Empirical Framework for LLM-Guided, Reasoning-Driven Input Mutation
par: Lu, Mengdi, et autres
Publié: (2025)

Containment Verification: AI Safety Guarantees Independent of Alignment
par: Moon, Royce, et autres
Publié: (2026)

Risks of ignoring uncertainty propagation in AI-augmented security pipelines
par: Mezzi, Emanuele, et autres
Publié: (2024)

Identifying the Supply Chain of AI for Trustworthiness and Risk Management in Critical Applications
par: Sheh, Raymond K., et autres
Publié: (2025)

Securing the AI Frontier: Urgent Ethical and Regulatory Imperatives for AI-Driven Cybersecurity
par: Kulothungan, Vikram
Publié: (2025)

Poisoning Programs by Un-Repairing Code: Security Concerns of AI-generated Code
par: Improta, Cristina
Publié: (2024)

Testing Storage-System Correctness: Challenges, Fuzzing Limitations, and AI-Augmented Opportunities
par: Wang, Ying, et autres
Publié: (2026)

Block MedCare: Advancing healthcare through blockchain integration with AI and IoT
par: Simonoski, Oliver, et autres
Publié: (2024)

AIBoMGen: Generating an AI Bill of Materials for Secure, Transparent, and Compliant Model Training
par: Vandendriessche, Wiebe, et autres
Publié: (2026)

Broken by Default: A Formal Verification Study of Security Vulnerabilities in AI-Generated Code
par: Blain, Dominik, et autres
Publié: (2026)

Zer0n: An AI-Assisted Vulnerability Discovery and Blockchain-Backed Integrity Framework
par: Parmar, Harshil, et autres
Publié: (2026)

MalCodeAI: Autonomous Vulnerability Detection and Remediation via Language Agnostic Code Reasoning
par: Gajjar, Jugal, et autres
Publié: (2025)

Tracking Software Security Topics
par: Vu, Phong Minh, et autres
Publié: (2024)

Cyber Threat Detection and Vulnerability Assessment System using Generative AI and Large Language Model
par: M, Keerthi Kumar., et autres
Publié: (2026)

SCoPE: Evaluating LLMs for Software Vulnerability Detection
par: Gonçalves, José, et autres
Publié: (2024)

Evaluating LLaMA 3.2 for Software Vulnerability Detection
par: Gonçalves, José, et autres
Publié: (2025)