惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

Martin Fowler
Martin Fowler
Jina AI
Jina AI
J
Java Code Geeks
Microsoft Security Blog
Microsoft Security Blog
Recent Announcements
Recent Announcements
I
InfoQ
L
LangChain Blog
The Cloudflare Blog
IT之家
IT之家
博客园 - 叶小钗
Apple Machine Learning Research
Apple Machine Learning Research
B
Blog
A
About on SuperTechFans
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
Last Week in AI
Last Week in AI
Blog — PlanetScale
Blog — PlanetScale
罗磊的独立博客
云风的 BLOG
云风的 BLOG
Microsoft Azure Blog
Microsoft Azure Blog
Engineering at Meta
Engineering at Meta
F
Fortinet All Blogs
博客园 - 聂微东
美团技术团队
博客园_首页

cs.CR updates on arXiv.org

Agentic Vulnerability Reasoning on Windows COM Binaries From Beats to Breaches:How Offensive AI Infers Sensitive User Information from Playlists Undetectable Backdoors in Model Parameters: Hiding Sparse Secrets in High Dimensions When Embedding-Based Defenses Fail: Rethinking Safety in LLM-Based Multi-Agent Systems Token-Efficient Change Detection in LLM APIs Selfie-Capture Dynamics as an Auxiliary Signal Against Deepfakes and Injection Attacks for Mobile Identity Verification Trident: Improving Malware Detection with LLMs and Behavioral Features When Alignment Isn't Enough: Response-Path Attacks on LLM Agents RefusalGuard: Geometry-Preserving Fine-Tuning for Safety in LLMs Checkerboard: A Simple, Effective, Efficient and Learning-free Clean Label Backdoor Attack with Low Poisoning Budget Block-wise Codeword Embedding for Reliable Multi-bit Text Watermarking Secret Stealing Attacks on Local LLM Fine-Tuning through Supply-Chain Model Code Backdoors Enhancing Linux Privilege Escalation Attack Capabilities of Local LLM Agents Defusing the Trigger: Plug-and-Play Defense for Backdoored LLMs via Tail-Risk Intrinsic Geometric Smoothing Evaluating Jailbreaking Vulnerabilities in LLMs Deployed as Assistants for Smart Grid Operations: A Benchmark Against NERC Standards Behavioral Canaries: Auditing Private Retrieved Context Usage in RL Fine-Tuning FlexServe: A Fast and Secure LLM Serving System for Mobile Devices with Flexible Resource Isolation Breaking MCP with Function Hijacking Attacks: Novel Threats for Function Calling and Agentic Models Text Steganography with Dynamic Codebook and Multimodal Large Language Model An AI Agent Execution Environment to Safeguard User Data TwoHamsters: Benchmarking Multi-Concept Compositional Unsafety in Text-to-Image Models Fundamental Limitations of Favorable Privacy-Utility Guarantees for DP-SGD Symbolic Guardrails for Domain-Specific Agents: Stronger Safety and Security Guarantees Without Sacrificing Utility Hardening x402: PII-Safe Agentic Payments via Pre-Execution Metadata Filtering QShield: Securing Neural Networks Against Adversarial Attacks using Quantum Circuits Hijacking Text Heritage: Hiding the Human Signature through Homoglyphic Substitution Like a Hammer, It Can Build, It Can Break: Large Language Model Uses, Perceptions, and Adoption in Cybersecurity Operations on Reddit Private Seeds, Public LLMs: Realistic and Privacy-Preserving Synthetic Data Generation One Word at a Time: Incremental Completion Decomposition Breaks LLM Safety Measuring and Exploiting Contextual Bias in LLM-Assisted Security Code Review
An Integration of policy and reputation based trust mecha...
Siddiqui Muhammad Yasir, Alam Gir, Jenny Lundberg · 2024-06-19 · via cs.CR updates on arXiv.org

Due to popularization of internet and e-commerce, more and more people getting involved in online shopping market. A large number of companies have been transferred to the internet where online customers have been increased due to easy access. The online business facilitates people to communicate without knowing each other. The e-commerce systems are the combination of commerce behavior and internet technologies. Therefore, trust aspects are positive elements in buyer-seller transactions and a potential source of competitive e-commerce industry. There are two different approaches to handle the trust. The first approach has a solid authentication set of rules where decisions are made on some digital or logical rules called policy based trust mechanism. The second approach is a decentralized trust approach where reputation assembled and shared in distributed environment called reputation based trust mechanism. Objectives: In this thesis, the strengths and weaknesses of policy and reputation based trust mechanisms have been identified through systematic literature review and industrial interviews. Furthermore, the process of integrated trust mechanism has been proposed. The integrated trust mechanism is proposed through mapping process, weakness of one mechanism with the strength of other. The proposed integrated trust mechanism was validated by conducting experiment with buyer/seller scenario in auction system. The analysis of collected results indicated that proposed integrated trust mechanism improved the trust of buyer against eBay and Tradera. At the end, we have discussed some key points that may affect trust relationship between seller and buyer. Furthermore, there is a need for further validation of proposed trust mechanism in auction system/e-commerce industry.