CXL Memory Hash Monitoring for Sensitive Data Integrity
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Solution Overview
Problem
Existing computer systems face challenges in detecting and addressing data falsification in memory devices due to attacks like row hammer attacks and malware infections, which can compromise the integrity of sensitive data, allowing unauthorized access.
Innovation Solution
A storage apparatus and method utilizing a hash value table and monitoring controller to monitor and verify the integrity of sensitive data through a Compute Express Link (CXL) interface, enabling detection and recovery of falsified data while maintaining system performance and reducing power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data integrity monitoring is implemented to detect falsified data, then data security is improved, but system complexity and power consumption increase
Solution Approach 1:
The patent creates a copy of the original data's hash value and stores it in a hash value table before data writing. This copy serves as a reference for future integrity verification, eliminating the need for complex real-time monitoring systems while maintaining detection capability.
Solution Approach 2:
The hash value is calculated and stored in advance during the data writing process. This preliminary action prepares the verification reference before any potential falsification can occur, enabling efficient later detection without requiring complex ongoing monitoring infrastructure.
2Reliability
If comprehensive data monitoring is performed to detect falsification, then data security is improved, but host performance deteriorates
Solution Approach 1:
The patent extracts the data integrity verification function from the host system and implements it independently in the storage apparatus. This separation allows the host to maintain high performance while the storage apparatus handles verification operations using pre-stored hash values.
Solution Approach 2:
The storage apparatus performs self-verification by comparing retrieved data against its own stored hash values. This self-service capability eliminates the need for host intervention in verification processes, maintaining host performance while ensuring data security.
3Measurement precision
If advanced monitoring mechanisms are deployed to detect data falsification, then detection capability is improved, but power consumption increases
Solution Approach 1:
By storing a copy of the hash value rather than implementing continuous monitoring, the system achieves precise detection capability through simple comparison operations that consume minimal power, avoiding the energy demands of advanced monitoring mechanisms.
Solution Approach 2:
Verification is performed periodically at specific operation points (data retrieval) rather than continuously. This periodic action maintains detection capability while significantly reducing power consumption compared to continuous monitoring mechanisms.
Data Source
AI summary
Disclosed is a storage apparatus for data integrity. The storage apparatus includes a hash value table configured to store information on a secured area in a main memory of a host communicating through a compute express link (CXL) interface and a hash value corresponding to the secured area, and a monitoring controller configured to read sensitive data stored in the secured area from the main memory through the CXL interface based on the information on the secured area, calculate a hash value of the sensitive data, compare the hash value of the sensitive data with the hash value corresponding to the secured area to determine whether the sensitive data is falsified, and recover the falsified sensitive data in response to determining that the sensitive data is falsified.