paper-with-me

Papers

Reverse Engineering and Security Evaluation of Commercial Tags for RFID-Based IoT Applications

2024-02-05 · Tiago M. Fernández-Caramés, Paula Fraga-Lamas, Manuel Suárez-Albela, Luis Castedo

The Internet of Things (IoT) is a distributed system of physical objects that requires the seamless integration of hardware (e.g., sensors, actuators, electronics) and network communications in order to collect and exchange data. IoT smart objects need to be somehow identified to determine the origin of the data and to automatically detect the elements around us. One of the best positioned technologies to perform identification is RFID (Radio Frequency Identification), which in the last years has gained a lot of popularity in applications like access control, payment cards or logistics. Despite its popularity, RFID security has not been properly handled in numerous applications. To foster security in such applications, this article includes three main contributions. First, in order to establish the basics, a detailed review of the most common flaws found in RFID-based IoT systems is provided, including the latest attacks described in the literature. Second, a novel methodology that eases the detection and mitigation of such flaws is presented. Third, the latest RFID security tools are analyzed and the methodology proposed is applied through one of them (Proxmark 3) to validate it. Thus, the methodology is tested in different scenarios where tags are commonly used for identification. In such systems it was possible to clone transponders, extract information, and even emulate both tags and readers. Therefore, it is shown that the methodology proposed is useful for auditing security and reverse engineering RFID communications in IoT applications. It must be noted that, although this paper is aimed at fostering RFID communications security in IoT applications, the methodology can be applied to any RFID communications protocol.

📄 PDF Abstract BibTeX arXiv:2402.03591

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

DecompileBench: A Comprehensive Benchmark for Evaluating Decompilers in Real-World Scenarios

2025-05-16 · Zeyu Gao, Yuxin Cui, Hao Wang, Siliang Qin 외

Decompilers are fundamental tools for critical security tasks, from vulnerability discovery to malware analysis, yet their evaluation remains fragmented. Existing approaches primarily focus on syntactic correctness throu…

Malware Analysis

Black-Box Guardrail Reverse-engineering Attack

2025-11-06 · Hongwei Yao, Yun Xia, Shuo Shao, Haoran Shi 외 arxiv

Large language models (LLMs) increasingly employ guardrails to enforce ethical, legal, and application-specific constraints on their outputs. While effective at mitigating harmful responses, these guardrails introduce a …

Reinforcement LearningData Augmentation

Hardware Trust and Assurance through Reverse Engineering: A Survey and Outlook from Image Analysis and Machine Learning Perspectives

2020-02-11 · Ulbert J. Botero, Ronald Wilson, Hangwei Lu, Mir Tanjidur Rahman 외

In the context of hardware trust and assurance, reverse engineering has been often considered as an illegal action. Generally speaking, reverse engineering aims to retrieve information from a product, i.e., integrated ci…

Exploring the Efficacy of Large Language Models (GPT-4) in Binary Reverse Engineering

2024-06-09 · Saman Pordanesh, Benjamin Tan

This study investigates the capabilities of Large Language Models (LLMs), specifically GPT-4, in the context of Binary Reverse Engineering (RE). Employing a structured experimental approach, we analyzed the LLM's perform…

Malware Analysis

Challenges and Future Directions in Agentic Reverse Engineering Systems

2026-04-15 · Salem Radey, Jack West, Kassem Fawaz arxiv

Agentic systems built on large language models (LLMs) are increasingly being used for complex security tasks, including binary reverse engineering (RE). Despite recent growth in popularity and capability, these systems c…