Inferring State Machine from the Protocol Implementation via Large Language Model

• URL: http://arxiv.org/abs/2405.00393v2
• Date: Fri, 14 Jun 2024 12:03:56 GMT
• Title: Inferring State Machine from the Protocol Implementation via Large Language Model
• Authors: Haiyang Wei, Zhengjie Du, Haohui Huang, Yue Liu, Guang Cheng, Linzhang Wang, Bing Mao,
• Abstract summary: We propose an innovative state machine inference approach powered by Large Language Models (LLMs) Our evaluation across six protocol implementations demonstrates the method's high efficacy, achieving an accuracy rate exceeding 90%. Our proposed method not only marks a significant step forward in accurate state machine inference but also opens new avenues for improving the security and reliability of protocol implementations.
• Score: 18.942047454890847
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: State machines play a pivotal role in augmenting the efficacy of protocol analyzing to unveil more vulnerabilities. However, the task of inferring state machines from network protocol implementations presents significant challenges. Traditional methods based on dynamic analysis often overlook crucial state transitions due to limited coverage, while static analysis faces difficulties with complex code structures and behaviors. To address these limitations, we propose an innovative state machine inference approach powered by Large Language Models (LLMs). Utilizing text-embedding technology, this method allows LLMs to dissect and analyze the intricacies of protocol implementation code. Through targeted prompt engineering, we systematically identify and infer the underlying state machines. Our evaluation across six protocol implementations demonstrates the method's high efficacy, achieving an accuracy rate exceeding 90% and successfully delineating differences on state machines among various implementations of the same protocol. Importantly, integrating this approach with protocol fuzzing has notably enhanced AFLNet's code coverage by 10% over RFCNLP, showcasing the considerable potential of LLMs in advancing network protocol security analysis. Our proposed method not only marks a significant step forward in accurate state machine inference but also opens new avenues for improving the security and reliability of protocol implementations.

Related papers

• Automatic State Machine Inference for Binary Protocol Reverse Engineering [20.35198277628804]
  We propose an automatic PSM inference framework for unknown protocols. We refine a probabilistic PSM algorithm to infer protocol states and the transition conditions between these states. Experimental results show that, compared with existing PRE techniques, our method can infer PSMs while enabling more precise classification of protocols.
  arXiv  Detail & Related papers  (2024-12-03T16:33:17Z)
• Games for AI Control: Models of Safety Evaluations of AI Deployment Protocols [52.40622903199512]
  This paper introduces AI-Control Games, a formal decision-making model of the red-teaming exercise as a multi-objective, partially observable game. We apply our formalism to model, evaluate and synthesise protocols for deploying untrusted language models as programming assistants.
  arXiv  Detail & Related papers  (2024-09-12T12:30:07Z)
• A Novel Stabilizer-based Entanglement Distillation Protocol for Qudits [0.016385815610837167]
  Entanglement distillation is pivotal for robust quantum information processing in error-prone environments. A construction based on stabilizer codes offers an effective method for designing such protocols. We present a novel two-copy distillation protocol that maximizes the fidelity increase per iteration for Bell-diagonal states in any prime dimension.
  arXiv  Detail & Related papers  (2024-08-05T11:14:28Z)
• A Survey and Comparative Analysis of Security Properties of CAN Authentication Protocols [92.81385447582882]
  The Controller Area Network (CAN) bus leaves in-vehicle communications inherently non-secure. This paper reviews and compares the 15 most prominent authentication protocols for the CAN bus. We evaluate protocols based on essential operational criteria that contribute to ease of implementation.
  arXiv  Detail & Related papers  (2024-01-19T14:52:04Z)
• Towards Semantic Communication Protocols for 6G: From Protocol Learning to Language-Oriented Approaches [60.6632432485476]
  6G systems are expected to address a wide range of non-stationary tasks. This poses challenges to traditional medium access control (MAC) protocols that are static and predefined. Data-driven MAC protocols have recently emerged, offering ability to tailor their signaling messages for specific tasks. This article presents a novel categorization of these data-driven MAC protocols into three levels: Level 1 MAC. task-oriented neural protocols constructed using multi-agent deep reinforcement learning (MADRL); Level 2 MAC. neural network-oriented symbolic protocols developed by converting Level 1 MAC outputs into explicit symbols; and Level 3 MAC. language-oriented semantic protocols harnessing
  arXiv  Detail & Related papers  (2023-10-14T06:28:50Z)
• Bicoptor 2.0: Addressing Challenges in Probabilistic Truncation for Enhanced Privacy-Preserving Machine Learning [6.733212399517445]
  This paper focuses on analyzing the problems and proposing solutions for the probabilistic truncation protocol in existing PPML works. In terms of accuracy, we reveal that precision selections recommended in some of the existing works are incorrect. We propose a solution and a precision selection guideline for future works.
  arXiv  Detail & Related papers  (2023-09-10T01:43:40Z)
• Practical quantum secure direct communication with squeezed states [55.41644538483948]
  We report the first table-top experimental demonstration of a CV-QSDC system and assess its security. This realization paves the way into future threat-less quantum metropolitan networks, compatible with coexisting advanced wavelength division multiplexing (WDM) systems.
  arXiv  Detail & Related papers  (2023-06-25T19:23:42Z)
• Extracting Protocol Format as State Machine via Controlled Static Loop Analysis [14.201174164060994]
  This work focuses on a class of protocols whose formats are described via constraint-enhanced regular expressions and parsed using finite-state machines. Our new technique extracts a state machine by regarding each loop as a state and the dependency between loop iterations as state transitions. The evaluation results show that we can infer a state machine and, thus, the message formats, in five minutes with over 90% precision and recall.
  arXiv  Detail & Related papers  (2023-05-22T20:58:06Z)
• Data post-processing for the one-way heterodyne protocol under composable finite-size security [62.997667081978825]
  We study the performance of a practical continuous-variable (CV) quantum key distribution protocol. We focus on the Gaussian-modulated coherent-state protocol with heterodyne detection in a high signal-to-noise ratio regime. This allows us to study the performance for practical implementations of the protocol and optimize the parameters connected to the steps above.
  arXiv  Detail & Related papers  (2022-05-20T12:37:09Z)
• Reinforcement learning-enhanced protocols for coherent population-transfer in three-level quantum systems [50.591267188664666]
  We deploy a combination of reinforcement learning-based approaches and more traditional optimization techniques to identify optimal protocols for population transfer. Our approach is able to explore the space of possible control protocols to reveal the existence of efficient protocols. The new protocols that we identify are robust against both energy losses and dephasing.
  arXiv  Detail & Related papers  (2021-09-02T14:17:30Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.