Lune

OSDI2024Top-tier venue

Ransom Access Memories: Achieving Practical Ransomware Protection in Cloud with DeftPunk

Zhongyu Wang, Yaheng Song, Erci Xu, Haonan Wu, Guangxun Tong, Shizhuo Sun, Haoran Li, Jincheng Liu, Lijun Ding, Rong Liu, Jiaji Zhu, Jiesheng Wu

2024Year
10Citations
3Top-tier citations

Abstract

In this paper, we focus on building a ransomware detection and recovery system for cloud block stores. We start by discussing the possibility of directly using existing methods or porting one to our scenario with modifications. These attempts, though failed, led us to identify the unique IO characteristics of ransomware, and further drove us to build DeftPunk, a block-level ransomware detection and recovery system. DeftPunk uses a two-layer classifier for fast and accurate detection, creates pre-/post-attack snapshots to avoid data loss, and leverages log-structured support for low overhead recovery. Our large-scale benchmark shows that DeftPunk can achieve nearly 100% recall across 13 types of ransomware and low runtime overhead.

Ask about this paper

Your agent reads all of it.

Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.

Questions to start from

Your agent calls

Luneget_paper_fulltext

Ask in Lune

Free to start. No credit card required.

lune papers fulltext bd2bf397-e98b-4df2-9a97-bcf43fdc6e28

Cited by top-tier papers3

Ask how each one uses it

Builds on4

Related papers

Dusk over the sea between two cliffs drawn in fine vertical lines