Distributed Ledger for Digital Forensics Data Integrity
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Solution Overview
Problem
There is a need for a secure and efficient method to collect, manage, and store digital forensics data, as existing technologies face challenges in maintaining the integrity and authenticity of digital evidence due to susceptibility to unauthorized access and corruption.
Innovation Solution
A system utilizing a distributed electronic data register hosted on multiple servers, which securely stores digital forensics data and employs an artificial intelligence engine with machine learning to identify anomalies in real-time, transmitting alerts and maintaining a high-integrity history of the evidence from the point of capture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If digital forensics data is stored using traditional centralized databases, then data access and management are simplified, but data integrity and security are compromised due to susceptibility to unauthorized access and corruption
Solution Approach 1:
The patent segments the centralized database into a distributed network of nodes, where each node stores a portion of the forensics data. This segmentation prevents single-point failures and unauthorized access to the entire dataset, as compromising one node does not affect the overall system integrity. The distributed architecture inherently provides fault tolerance and enhanced security through data fragmentation across multiple locations.
Solution Approach 2:
The patent introduces cryptographic hash functions and digital signature mechanisms as intermediaries between the stored data and verification processes. These cryptographic intermediaries enable automated integrity verification without requiring direct trust in individual nodes, as any data modification would result in hash mismatches that trigger alerts. This intermediary layer provides automated security enforcement without manual intervention.
2Speed
If manual verification methods are used to ensure evidence authenticity, then system complexity is reduced, but detection speed and real-time monitoring capability are significantly slowed
Solution Approach 1:
The patent implements self-service mechanisms where the distributed ledger automatically performs integrity verification through cryptographic hash comparisons. The system autonomously detects anomalies by comparing current data states against stored hash values without requiring manual forensic analysis. This automated self-verification process enables real-time anomaly detection while maintaining cryptographic proof of data integrity, eliminating the need for continuous manual auditing.
Solution Approach 2:
The patent establishes a feedback loop where anomaly detection triggers automated alerts to relevant parties. When the system detects a hash mismatch or unauthorized modification, it immediately generates notifications to investigators and system administrators. This feedback mechanism enables rapid response to potential evidence tampering, allowing real-time intervention while maintaining a complete audit trail of all verification activities.
3Reliability
If cryptographic verification is performed on every data access, then data security is enhanced, but processing time and computational overhead increase
Solution Approach 1:
The patent performs preliminary cryptographic hashing when data is first written to the distributed ledger, storing the hash value alongside the encrypted forensics data. This preliminary action enables subsequent rapid verification, as the system only needs to compare a newly computed hash against the pre-stored hash rather than performing full cryptographic verification of the entire dataset. This approach maintains high authentication reliability while significantly reducing verification time for subsequent accesses.
Data Source
AI summary
A system is provided for high integrity real time processing of digital forensics data. In particular, the system may comprise a distributed electronic data register that may be hosted on a plurality of distributed servers. The distributed register may store digital forensics data within a secure data record within the distributed register. In this regard, entities or individuals who are authorized to access and/or receive the evidence may submit a digital signature to the distributed register. The system may further comprise an artificial intelligence engine that may use machine learning to identify potential anomalies in real time within the chain of evidence and trigger an alert service to transmit real time alerts to one or more systems and/or users. In this way, the system provides a more secure and efficient way to store, process, and manage digital forensics data.