StegoHound：一种用于高效识别和提取 WAV 与 MP3 文件中被隐写技术掩盖的数字证据的新型多方法
StegoHound: A Novel Multi-Approaches Method for Efficient and Effective Identification and Extraction of Digital Evidence Masked by Steganographic Techniques in WAV and MP3 Files
AI总结：
针对 WAV/MP3 音频中隐写与加密隐藏证据难提取的问题，提出 StegoHound 多方法自动化框架，关联原始工件、实时分析与传统检测技术，提升大型文件取证的覆盖率、准确性并降低假阴性。
摘要：
反取证技术，尤其是隐写术和密码学，已成为影响当前数字取证实践的日益紧迫问题。本文通过提出一种新型多方法，推进了音频文件中隐藏证据提取的自动化；该方法能够在未处理工件、索引化与实时取证分析以及传统隐写和密码检测技术之间建立关联。在本研究中，我们采用实验研究方法，对所提出的自动化方案在 WAV 和 MP3 音频文件中检测并提取隐藏工件的效率进行定量分析，并将其与标准行业系统进行比较。本工作推进了取证调查期间提取被密码学和隐写技术隐藏证据的现有自动化水平；所提出的多方法在覆盖率和准确性方面表现出明显提升，尤其是在大型音频文件（MP3 和 WAV）上，而此类文件的手动取证分析复杂、耗时且需要大量专业知识。尽管如此，所提出的多方法自动化偶尔可能产生假阳性（在不存在隐写时检测到隐写）或假阴性（未能检测到存在的隐写），但总体上在高效、有效地检测隐藏证据与最小化假阴性之间实现了良好平衡，从而验证了其可靠性。
英文摘要：
Anti-forensics techniques particularly steganography and cryptography have become increasingly pressing issues that affect the current digital forensics practice. This paper advances the automation of hidden evidence extraction in the context of audio files by proposing a novel multi-approaches method which enables the correlation between unprocessed artefacts, indexed and live forensics analysis and traditional Steganographic and Cryptographic detection techniques. In this work, we opted for experimental research methodology in the form of a quantitative analysis of the efficiency of the proposed automation detecting and extracting hidden artefacts in WAV and MP3 audio files by comparing it to standard industry systems. This work advances the current automation in extracting evidence hidden by Cryptographic and Steganographic techniques during forensics investigations, the proposed multi-approaches demonstrated a clear enhancement in terms of coverage and accuracy notably on large audio files (MP3 and WAV) for which the manual forensics analysis is complex, time-consuming and requires significant expertise. Nonetheless, the proposed multi-approach automation may occasionally produce false positives (detecting steganography where none exists) or false negatives (failing to detect steganography that is present) but overall achieve a good balance between efficiently and effectively detecting hidden evidence and minimising the false negative which validates its reliability.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
