AFLNet Five Years Later: On Coverage-Guided Protocol Fuzzing

• URL: http://arxiv.org/abs/2412.20324v3
• Date: Tue, 29 Apr 2025 06:47:43 GMT
• Title: AFLNet Five Years Later: On Coverage-Guided Protocol Fuzzing
• Authors: Ruijie Meng, Van-Thuan Pham, Marcel Böhme, Abhik Roychoudhury,
• Abstract summary: This paper reviews the technical contributions of AFLNet over the past five years.<n>AFLNet was the first code- and state-coverage-guided protocol fuzzer.
• Score: 20.704858261496792
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Protocol implementations are stateful which makes them difficult to test: Sending the same test input message twice might yield a different response every time. Our proposal to consider a sequence of messages as a seed for coverage-directed greybox fuzzing, to associate each message with the corresponding protocol state, and to maximize the coverage of both the state space and the code was first published in 2020 in a short tool demonstration paper. AFLNet was the first code- and state-coverage-guided protocol fuzzer; it used the response code as an indicator of the current protocol state. Over the past five years, the tool paper has gathered hundreds of citations, the code repository was forked almost 200 times and has seen over thirty pull requests from practitioners and researchers, and our initial proposal has been improved upon in many significant ways. In this paper, we first provide an extended discussion and a full empirical evaluation of the technical contributions of AFLNet and then reflect on the impact that our approach and our tool had in the past five years, on both the research and the practice of protocol fuzzing.

Related papers

• Experimental Simulation of Two Pulses and Three Pulses Coherent One Way Quantum Key Distribution Protocol in Noisy/Noiseless and Wired/Wireless Environment [1.8638865257327277]
  Coherent One Way (COW) protocol is one of the most famous protocol because of its ease of hardware deployment. We demonstrate the encoding as well as decoding portions of the protocols under both noisy and noiseless scenario.
  arXiv  Detail & Related papers  (2024-09-23T11:02:52Z)
• Stateful protocol fuzzing with statemap-based reverse state selection [3.7687375904925484]
  Stateful Coverage-Based Greybox Fuzzing (SCGF) is considered the state-of-the-art method for network protocol greybox fuzzing. This paper proposes a statemap-based reverse state selection method for SCGF.
  arXiv  Detail & Related papers  (2024-08-13T12:11:41Z)
• FastFiD: Improve Inference Efficiency of Open Domain Question Answering via Sentence Selection [61.9638234358049]
  FastFiD is a novel approach that executes sentence selection on encoded passages. This aids in retaining valuable sentences while reducing the context length required for generating answers.
  arXiv  Detail & Related papers  (2024-08-12T17:50:02Z)
• Rethinking Human Evaluation Protocol for Text-to-Video Models: Enhancing Reliability,Reproducibility, and Practicality [58.87422943009375]
  This paper introduces the Text-to-Video Human Evaluation (T2VHE) protocol, a comprehensive and standardized protocol for T2V models. The protocol includes well-defined metrics, thorough annotator training, and an effective dynamic evaluation module. We will open-source the entire setup of the T2VHE protocol, including the complete protocol workflow, the dynamic evaluation component details, and the annotation interface code.
  arXiv  Detail & Related papers  (2024-06-13T06:09:22Z)
• 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)
• Quantum Two-Way Communication Protocol Beyond Superdense Coding [36.25599253958745]
  We introduce a generalization of one-way superdense coding to two-way communication protocols for transmitting classical bits by using entangled quantum pairs. The proposed protocol gives a 50% increase in both data rate and energy efficiency compared to the classical protocol.
  arXiv  Detail & Related papers  (2023-09-06T08:48:07Z)
• Towards Efficient Fine-tuning of Pre-trained Code Models: An Experimental Study and Beyond [52.656743602538825]
  Fine-tuning pre-trained code models incurs a large computational cost. We conduct an experimental study to explore what happens to layer-wise pre-trained representations and their encoded code knowledge during fine-tuning. We propose Telly to efficiently fine-tune pre-trained code models via layer freezing.
  arXiv  Detail & Related papers  (2023-04-11T13:34:13Z)
• KG-FiD: Infusing Knowledge Graph in Fusion-in-Decoder for Open-Domain Question Answering [68.00631278030627]
  We propose a novel method KG-FiD, which filters noisy passages by leveraging the structural relationship among the retrieved passages with a knowledge graph. We show that KG-FiD can improve vanilla FiD by up to 1.5% on answer exact match score and achieve comparable performance with FiD with only 40% of computation cost.
  arXiv  Detail & Related papers  (2021-10-08T18:39:59Z)
• Quantum key distribution based on orthogonal state encoding [0.0]
  Two quantum key distribution protocols are presented. One does not need to employ order-rearrangement techniques while the other needs to. We modify the protocols for implementing in noisy channels by applying the testing state method.
  arXiv  Detail & Related papers  (2021-07-05T12:14:05Z)
• Hierarchical Bi-Directional Self-Attention Networks for Paper Review Rating Recommendation [81.55533657694016]
  We propose a Hierarchical bi-directional self-attention Network framework (HabNet) for paper review rating prediction and recommendation. Specifically, we leverage the hierarchical structure of the paper reviews with three levels of encoders: sentence encoder (level one), intra-review encoder (level two) and inter-review encoder (level three) We are able to identify useful predictors to make the final acceptance decision, as well as to help discover the inconsistency between numerical review ratings and text sentiment conveyed by reviewers.
  arXiv  Detail & Related papers  (2020-11-02T08:07:50Z)
• State-of-Art-Reviewing: A Radical Proposal to Improve Scientific Publication [19.10668029301668]
  State-Of-the-Art Review (SOAR) is a neoteric reviewing pipeline that serves as a 'plug-and-play' replacement for peer review. At the heart of our approach is an interpretation of the review process as a multi-objective, massively distributed and extremely-high-latency optimisation.
  arXiv  Detail & Related papers  (2020-03-31T17:58:36Z)

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.