Forensic Data Review UI Using Reference Hash Sets
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Solution Overview
Problem
Existing digital forensic systems face inefficiencies due to redundancies and version control issues in hash databases, leading to repetitive reviews and inconsistent data handling across investigations and investigators.
Innovation Solution
A system and method for managing and presenting forensic data using reference hash sets, allowing forensic examiners to hash data items and apply presentation rules to vary display properties based on hash matches, enabling efficient cross-referencing and streamlined review processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If forensic investigators review all forensic data items manually, then comprehensive review is achieved, but time consumption and redundancy increase significantly
Solution Approach 1:
The system extracts and identifies duplicate data items across forensic investigations using hash value comparison. By taking out redundant items from the review process through automatic detection and suppression, the system maintains comprehensive review coverage while eliminating time-wasting repetition of the same items across different cases and investigators.
Solution Approach 2:
The hash database serves multiple functions: it stores reference hash values, identifies duplicates across investigations, suppresses redundant items from display, and provides version control. This universal system handles both the completeness of review and the efficiency of time management simultaneously.
2Reliability
If multiple investigators use the same hash database, then consistency is improved, but version control issues and conflicts arise
Solution Approach 1:
The system merges the hash databases of multiple investigators into a single centralized database. By combining individual hash sets with investigator identifiers and timestamps, the system maintains consistency across all users while automatically handling version control through the unified structure, eliminating conflicts that arise from separate maintenance.
3Loss of information
If irrelevant data items are displayed during review, then complete information availability is maintained, but review efficiency decreases due to noise
Solution Approach 1:
The system applies different display qualities to different data items based on their relevance. Relevant items are displayed prominently with full visibility, while identified duplicates are suppressed or displayed with reduced prominence. This local differentiation maintains information availability for important items while filtering noise to improve review efficiency.
Data Source
AI summary
Systems and methods for presenting forensic data in a forensic data review user interface and for generating reference hash sets are provided. The method includes receiving a selection via the forensic data review user interface to display a forensic data collection; in response to receiving the selection, hashing at least one forensic data item in the forensic data collection to generate a hash value; determining that the hash value matches a reference hash value in at least one reference hash set; varying a default display property of the at least one forensic data item according to a presentation rule encoded in the reference hash set and associated with the reference hash value to obtain a varied display property; and displaying the forensic data collection in the forensic data review user interface including the at least one forensic data item according to the varied display property.