Suspect Identification via Correlated Device Identities
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Solution Overview
Problem
Existing methods for identifying suspects at crime scenes are inefficient in quickly narrowing down the large number of devices associated with potential suspects, often resulting in a cumbersome process that requires extensive manual investigation.
Innovation Solution
A method and apparatus utilizing a central server to correlate device identities across multiple location and time events, identifying suspect devices by determining common devices associated with access points near crime scenes, and subsequently obtaining owner information through network operators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional manual investigation methods are used to identify suspects, then thorough investigation can be conducted, but the process becomes extremely time-consuming and inefficient
Solution Approach 1:
The system performs preliminary actions by continuously collecting and storing device identification data from access points before crimes occur. When a crime happens, the investigation reduces to querying pre-collected data rather than starting from scratch, dramatically reducing investigation time while maintaining accuracy
Solution Approach 2:
Device identification data serves as an intermediary between crime scene investigation and suspect identification. Instead of directly investigating suspects, the system uses device data as a mediator to narrow down potential suspects, making the identification process both faster and more accurate
2Reliability
If all devices associated with access points near crime scenes are considered as suspect devices, then comprehensive coverage is achieved, but the number of suspect devices becomes extremely large and difficult to manage
Solution Approach 1:
The system segments the large set of suspect devices by correlating device identities across multiple crime events. Devices are divided into segments based on their presence at one, two, or multiple crime scenes, with devices appearing at multiple events representing the most high-value suspects
Solution Approach 2:
Instead of analyzing all devices equally, the system applies partial action by focusing investigation resources on devices that appear at multiple crime scenes. This excessive filtering approach ensures that while some potentially relevant devices may be excluded, the high-priority suspects are concentrated in a manageable list
Data Source
AI summary
A method and apparatus for identifying a suspect through location and time events is provided herein. During operation a central server continuously receives updates from multiple networks regarding device identifiers and associated access points. When an event (e.g., a crime) occurs at a certain location, an access point(s) near the event are identified and devices associated with the access point(s) at the time of the event are determined. The identified devices are then utilized to determine potential suspects.