Data Integrity Monitoring via Security Value Comparison
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Solution Overview
Problem
Current online transaction security systems are vulnerable to unauthorized access and malicious data manipulation, leading to potential loss of business and reputation damage due to cyber attacks exploiting weaknesses in computer communication protocols and individual computers.
Innovation Solution
A method and system for maintaining data integrity by determining and comparing security values of monitored data objects over time, storing copies in a secure repository, and generating alerts for any detected differences, utilizing a combination of administrator, authenticator, change detector, and notification programs to ensure timely detection and response to malicious changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If security monitoring and comparison of data objects is implemented, then data integrity and detection of unauthorized access is improved, but system complexity and resource consumption increases
Solution Approach 1:
The system performs preliminary actions by creating baseline security values and storing reference copies of data objects before monitoring begins. This allows the system to detect changes by comparing current states against pre-established baselines, enabling proactive security monitoring without requiring complex real-time analysis of all possible attack vectors.
Solution Approach 2:
The system creates and stores copies of monitored data objects in a secure repository, maintaining reference versions against which current versions can be compared. This copying approach enables integrity verification without requiring the original objects to remain unchanged, and allows restoration if corruption or unauthorized modification is detected.
2Reliability
If continuous monitoring and comparison of security values is performed, then detection of malicious data manipulation is improved, but processing time and computational resources increase
Solution Approach 1:
The system extracts only the essential security-critical attributes from data objects to create security values, rather than analyzing or comparing entire data sets. This extraction approach focuses computational resources on generating and comparing compact security representations (such as hashes or checksums), significantly reducing processing time while maintaining detection capability for unauthorized modifications.
3Ease of repair
If security values and data copies are stored in a secure repository, then data restoration capability is improved, but storage requirements increase
Solution Approach 1:
The system stores copies of monitored data objects and their associated security values in a secure repository. These copies serve as reference points for detecting unauthorized changes and enable restoration of compromised data to its authentic state, providing a safety net against data corruption or malicious modification.
Solution Approach 2:
The system transforms data objects into security values by applying cryptographic hash functions or other transformation algorithms. These security values are compact representations that enable efficient storage and comparison, allowing the system to maintain restoration capability while minimizing the storage overhead compared to storing complete data copies.
Data Source
AI summary
Aspects of the present invention maintain data integrity of a monitored data object in a monitored storage repository. A first security value for the monitored data object is determined. The first security value is stored along with an authentic copy of the monitored data object in the secure repository. The second security value for the monitored data object is determined after a predetermined time interval. The first security value is compared with the second security value. An alert is generated in response to determining a difference between the second security value and the first security value.