Papers
Topics
Authors
Recent
Search
2000 character limit reached

RSSD: Defend against Ransomware with Hardware-Isolated Network-Storage Codesign and Post-Attack Analysis

Published 12 Jun 2022 in cs.CR and cs.AR | (2206.05821v1)

Abstract: Encryption ransomware has become a notorious malware. It encrypts user data on storage devices like solid-state drives (SSDs) and demands a ransom to restore data for users. To bypass existing defenses, ransomware would keep evolving and performing new attack models. For instance, we identify and validate three new attacks, including (1) garbage-collection (GC) attack that exploits storage capacity and keeps writing data to trigger GC and force SSDs to release the retained data; (2) timing attack that intentionally slows down the pace of encrypting data and hides its I/O patterns to escape existing defense; (3) trimming attack that utilizes the trim command available in SSDs to physically erase data. To enhance the robustness of SSDs against these attacks, we propose RSSD, a ransomware-aware SSD. It redesigns the flash management of SSDs for enabling the hardware-assisted logging, which can conservatively retain older versions of user data and received storage operations in time order with low overhead. It also employs hardware-isolated NVMe over Ethernet to expand local storage capacity by transparently offloading the logs to remote cloud/servers in a secure manner. RSSD enables post-attack analysis by building a trusted evidence chain of storage operations to assist the investigation of ransomware attacks. We develop RSSD with a real-world SSD FPGA board. Our evaluation shows that RSSD can defend against new and future ransomware attacks, while introducing negligible performance overhead.

Citations (12)

Summary

No one has generated a summary of this paper yet.

Paper to Video (Beta)

No one has generated a video about this paper yet.

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.

Authors (3)

Collections

Sign up for free to add this paper to one or more collections.