Lempel-Ziv Jaccard距离：Ssdeep和Sdhash的有效替代
Lempel-Ziv Jaccard Distance, an Effective Alternative to Ssdeep and Sdhash
摘要：
最近的工作提出了Lempel-Ziv Jaccard距离（LZJD）作为一种方法来衡量恶意软件分类的二进制字节序列之间的相似性。我们提出并测试LZJD的有效性作为一个数字取证的相似性摘要哈希。为此，我们开发了一个高性能的Java实现，使用与sdhash相同的命令行参数，使其易于集成到现有的工作流中。我们的测试表明，LZJD对于此任务是有效的，并且在匹配相关文件片段和被随机噪声损坏的文件的能力方面明显优于sdhash和ssdeep。此外，LZJD在比较时比sdhash快60倍。
英文摘要：
Recent work has proposed the Lempel-Ziv Jaccard Distance (LZJD) as a method to measure the similarity between binary byte sequences for malware classification. We propose and test LZJD's effectiveness as a similarity digest hash for digital forensics. To do so we develop a high performance Java implementation with the same command-line arguments as sdhash, making it easy to integrate into existing workflows. Our testing shows that LZJD is effective for this task, and significantly outperforms sdhash and ssdeep in its ability to match related file fragments and files corrupted with random noise. In addition, LZJD is up to 60x faster than sdhash at comparison time.
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。
