Mobile eDiscovery Collector for Selective Data Extraction
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Solution Overview
Problem
Conventional eDiscovery systems face limitations such as excessive data collection, difficulty in browsing and reviewing encrypted data, limited accessibility and capacity, inaccurate file selection based on extensions, onsite implementation concerns, and require specialized knowledge, leading to inefficiencies and security issues.
Innovation Solution
A mobile device-based data collection manager generates a collector configured to selectively collect data files based on characteristics, stores it in a network server, and notifies the target device for execution, using unique file signatures for accurate identification and storing data in cloud-based storage for enhanced accessibility and security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional eDiscovery systems collect all data residing on computer resources, then complete data coverage is achieved, but cost increases proportionally regardless of damages sought
Solution Approach 1:
The system extracts and collects only the specific data files requested by the discovery request, rather than collecting all data. The collector is configured with selection criteria that identify and collect only relevant files based on file type, date range, and other parameters, eliminating unnecessary data collection and associated costs.
Solution Approach 2:
The system applies different collection strategies to different data categories. High-priority data relevant to the specific legal matter is collected with detailed metadata, while lower-priority data is handled differently or excluded, optimizing resource allocation based on local data characteristics and relevance.
2Reliability
If conventional systems generate encrypted hard drive maps, then data security is maintained, but browsing and review difficulty increases
Solution Approach 1:
The system introduces a web-based interface as an intermediary between the encrypted data storage and the user. Users can browse and review collected data through a convenient web interface without needing to decrypt or access the underlying encrypted hard drive maps directly, maintaining security while improving accessibility.
3Reliability
If systems use non-cloud-based storage, then data control is maintained, but accessibility and capacity are limited
Solution Approach 1:
The system provides multiple access methods and storage options. Data can be stored in cloud-based storage systems that offer enhanced accessibility and capacity, while the mobile device application maintains control over the collection process and data security policies. The web interface provides universal access from any device.
4Ease of manufacture
If systems select files based only on extensions, then selection process is simple, but accuracy decreases due to extension modification
Solution Approach 1:
The system changes the selection parameters from relying solely on file extensions to using multiple parameters including file signature verification, creation dates, modification dates, and content analysis. This multi-parameter approach maintains selection simplicity while significantly improving accuracy by verifying actual file types rather than trusting extensions.
5Reliability
If systems require onsite implementation, then data security is maintained, but security concerns and complexity increase
Solution Approach 1:
The system enables self-service data collection where the mobile device application automatically collects data from target devices without requiring onsite technical personnel. The application handles authentication, data collection, encryption, and upload to cloud storage automatically, reducing implementation complexity while maintaining security through automated security protocols.
6Reliability
If systems require specialized knowledge, then operational control is maintained, but user accessibility decreases
Solution Approach 1:
The system introduces a user-friendly mobile device application and web interface as intermediaries that abstract away the complexity of the data collection process. Users can initiate collections, view progress, and access results through simple graphical interfaces without needing specialized eDiscovery knowledge, while the system maintains operational control through automated workflows and security protocols.
Data Source
AI summary
An approach is provided for collecting data files from target devices. A data collection manager implemented in a mobile device generates a collector based, at least in part, on collection definition data. The collector is configured to perform a data search on a target device. The data collection manager causes to transmit the collector to a network server for storing the collector in the network server, and causes to transmit a notification to the network server to notify a custodian of the target device that the collector is to be downloaded from the network server to the target device for execution. Executing the collector causes the collector to selectively determine one or more data files that have certain characteristics and that are hosted on the target device, collect the one or more data files from the target device, and store the one or more data files in the network server.