IoT Device Profiling for Selective Security Pattern Matching
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Solution Overview
Problem
Existing IoT security systems face challenges in efficiently profiling and detecting anomalous or malicious behavior of IoT devices within networks, especially in large and dynamic environments, due to the vast number of possible device profiles and activities, making it computationally prohibitive to apply pattern matching effectively.
Innovation Solution
A system is implemented that profiles IoT devices using a limited set of profiles and generates activity data structures, applying pattern matching engines to detect expected and anomalous behaviors, utilizing engines like IoT device activity generation, profiling, and pattern matching to identify and alert on undesirable actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pattern matching is applied to all possible IoT device profiles and activities, then detection precision is improved, but computational complexity and resource consumption increase exponentially
Solution Approach 1:
The patent segments the vast space of possible IoT device profiles and activities into manageable subsets by establishing hierarchical categories and groups. Pattern matching is then applied selectively to relevant segments rather than exhaustively to all possibilities, reducing computational complexity while maintaining detection precision for actual threats.
Solution Approach 2:
The patent implements partial pattern matching by applying detection rules only to specific subsets of device profiles and activities that are relevant to known threat patterns, rather than performing complete exhaustive matching across all possible profiles. This selective approach reduces computational resources while maintaining effective security detection.
2Reliability
If comprehensive pattern matching is performed across all IoT device profiles, then security detection capability is improved, but processing time increases making real-time detection infeasible
Solution Approach 1:
The patent performs preliminary actions by pre-categorizing and pre-grouping IoT device profiles into hierarchical structures before pattern matching occurs. Detection rules and patterns are also prepared in advance and organized by relevance. This preliminary organization enables rapid pattern matching during actual security events, reducing processing time while maintaining comprehensive detection capability.
Solution Approach 2:
By segmenting the pattern matching process into hierarchical levels and applying rules selectively to relevant segments rather than all profiles simultaneously, the system achieves real-time detection performance without sacrificing security coverage.
3Measurement precision
If the system profiles every IoT device in detail, then detection accuracy is improved, but the system complexity and resource requirements become prohibitive in large networks
Solution Approach 1:
The patent applies local quality by creating detailed profiles only for specific aspects of IoT devices that are relevant to security detection, rather than comprehensively profiling every device attribute. The hierarchical profiling system focuses computational resources on locally relevant characteristics for each device type and threat context, reducing overall system complexity while maintaining detection accuracy.
Data Source
AI summary
Techniques for providing Internet of Things (IoT) security are disclosed. An applicable system includes profiling IoT devices to limit the number of network signatures applicable to the IoT devices and performing pattern matching using a pattern that is appropriate for the profile of a given IoT device.