Hierarchical Temporal Memory Access Control
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Solution Overview
Problem
Defining access control rules for computer systems is burdensome due to the multi-dimensional considerations required, necessitating a more efficient method to manage access and behavior.
Innovation Solution
A computer-implemented method using a hierarchical temporal memory (HTM) to generate a sparse distributed representation of access records, training the HTM to model authorized access, and determining unauthorized access by comparing operational records against a threshold, with the option to preclude access when unauthorized use is detected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If access control rules are defined manually for each user, resource, and permission, then access control can be enforced, but the complexity and effort required to define and maintain these rules increases significantly
Solution Approach 1:
The system enables automated access control rule generation by training the HTM model on historical access logs. The model autonomously learns authorized access patterns and automatically generates access control rules without requiring manual definition, thereby reducing complexity while maintaining enforcement reliability
Solution Approach 2:
The patent replaces the manual mechanical process of defining access control rules with an automated neural network-based system. The HTM model processes historical data and automatically generates rules, substituting human effort with an intelligent automated system that reduces complexity
2Ease of operation
If traditional access control systems are used, then access decisions can be made, but the systems cannot effectively detect unauthorized access patterns or anomalies
Solution Approach 1:
The HTM model continuously analyzes access logs and provides feedback on recognized versus unrecognized patterns. This feedback mechanism enables the system to detect unauthorized access by identifying deviations from learned authorized patterns, improving detection capability while maintaining ease of operation
Solution Approach 2:
The system performs preliminary training by analyzing historical access logs before actual access control enforcement. This preliminary action builds a model of authorized behavior, enabling the system to detect unauthorized access patterns during operational use without compromising ease of operation
3Reliability
If comprehensive access control rules are defined to cover all scenarios, then security is improved, but the time and effort required to define and maintain these rules increases
Solution Approach 1:
The system performs preliminary training by analyzing historical access logs to build a comprehensive model of authorized access patterns. This preliminary action captures security requirements automatically, eliminating the need for time-consuming manual rule definition while maintaining comprehensive security coverage
Solution Approach 2:
The HTM model autonomously learns and generates access control rules from historical data without requiring manual intervention. This self-service capability reduces the time and effort required to define and maintain comprehensive security rules while ensuring thorough coverage of access scenarios
Data Source
AI summary
A computer implemented method for access control for a restricted resource in a computer system, the method including receiving a first set of records for the computer system, each record detailing an occurrence in the computer system during a training time period when the resource is accessed in an approved manner; generating a sparse distributed representation of the set of records to form a training set for a hierarchical temporal memory (HTM); training the HTM based on the training set in order that the trained HTM provides a model of the operation of the computer system during the training time period; receiving a second set of records for the computer system, each record detailing an occurrence in the computer system during an operating time period for the computer system in use by a consumer of the resource; generating a sparse distributed representation of the second set of records to form an input set for the trained HTM; executing the trained HTM based on the input set to determine a degree of recognition of the records of the input set; and responsive to a determination that a degree of recognition of one or more records of the input set is below a threshold degree, identifying the operation of the computer system by the consumer as unauthorized.