Device Fingerprinting Profiles for Continuous Threat Assessment
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Solution Overview
Problem
Existing device fingerprinting techniques provide limited insights into the behavior and identity of network devices, making it difficult to accurately assess potential threats and prevent unauthorized access or malicious activities on networks.
Innovation Solution
Collecting high-definition fingerprint information over an extended period to create detailed profiles of user devices, analyzing device attributes and behavior, and comparing them to historical data to generate threat assessments, enabling proactive security measures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional device fingerprinting techniques are used, then device identification can be performed, but the insight into device behavior and identity remains limited
Solution Approach 1:
The patent segments the fingerprinting process into multiple distinct components: device attributes (hardware, software, network), user behavior patterns (interactions, navigation, input methods), and temporal sequences of activities. This segmentation allows comprehensive collection of device information across multiple dimensions, enabling more accurate threat detection while preserving complete device behavior information.
2Reliability
If comprehensive fingerprint information is collected over extended periods, then detailed device profiles can be created, but the complexity of the fingerprinting system increases
Solution Approach 1:
The patent extracts and isolates specific behavior patterns and device attributes from the complex stream of user interactions. By identifying and extracting key indicators such as typing patterns, navigation sequences, and device configuration details, the system creates manageable fingerprint profiles from otherwise overwhelming data, maintaining reliability while controlling complexity.
Solution Approach 2:
The patent transforms raw behavioral data into standardized parameters and metrics that can be systematically analyzed. By converting diverse user interactions into quantifiable behavioral patterns and device attributes, the system maintains assessment reliability while simplifying the complexity of processing raw data through consistent parameterization.
3Measurement precision
If fingerprint data is collected both before and after authentication, then more comprehensive threat assessments can be generated, but the amount of processing required increases
Solution Approach 1:
The patent performs preliminary fingerprinting data collection and analysis before authentication occurs. By gathering device attributes, initial behavior patterns, and baseline metrics during the pre-authentication phase, the system prepares threat assessment data in advance, reducing the processing burden during actual authentication while maintaining comprehensive assessment precision.
Solution Approach 2:
The patent implements continuous fingerprinting data collection that spans the entire user session from pre-authentication through post-authentication activities. This continuous collection creates an unbroken timeline of device behavior and attributes, enabling comprehensive threat assessment without requiring separate processing batches, thereby reducing overall processing time while maintaining precision.
Data Source
AI summary
This disclosure describes techniques for performing fingerprinting of network devices, where the fingerprinting is capable of providing a high definition and clear picture of the network device and/or the identity of the operator of the network device. In one example, this disclosure describes a method that includes receiving, over a network from a user device, a first set of fingerprint data; generating, based on the first set of fingerprint data, a first threat assessment associated with the user; receiving, over the network from the user device, a second set of fingerprint data; generating, by the computing system and based on the first set of fingerprint data and the second set of fingerprint data, a second threat assessment; and sending, by the computing system and based on the second threat assessment, control signals to a system on the network to cause the system to implement a policy threat mitigation policy.