Intelligent IoT Vulnerability Detection via Priority Attack Spheres
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Solution Overview
Problem
Existing solutions for protecting IoT devices from attacks lack intelligence and proactivity, often conducting scans on a schedule or manually, which can lead to delayed detection of vulnerabilities in high-risk locations, increasing the potential for attacks.
Innovation Solution
The system employs intelligent and proactive device vulnerability detection and protection by prioritizing attack spheres based on trend analysis and predictive analysis, focusing scanning and protection efforts on high-risk areas before less vulnerable ones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If scheduled scanning is used for all devices, then scanning coverage is comprehensive, but detection timeliness deteriorates for high-risk devices
Solution Approach 1:
The patent applies local quality by differentiating scanning frequency and depth based on device risk characteristics. High-risk devices in priority attack spheres receive intensive scanning (e.g., daily or real-time), while low-risk devices receive standard scheduled scanning. This resolves the contradiction by optimizing detection timeliness for critical devices without sacrificing comprehensive coverage across all devices.
Solution Approach 2:
The patent implements dynamic scanning schedules that adapt to changing threat landscapes and device risk profiles. The system continuously updates attack sphere priorities based on new vulnerability intelligence, geographic threats, and device characteristics, dynamically adjusting which devices require immediate scanning versus routine scanning. This dynamic approach ensures timely detection of high-risk devices while maintaining overall scanning coverage.
2Device complexity
If uniform scanning frequency is applied to all devices, then resource allocation is simple, but protection effectiveness deteriorates for vulnerable devices
Solution Approach 1:
The patent applies local quality by assigning different scanning frequencies, depths, and resource allocations to devices based on their risk profiles and attack sphere priorities. High-priority devices receive intensive scanning with more computational resources, while low-priority devices receive standard scanning. This resolves the contradiction by improving protection effectiveness for vulnerable devices without requiring overly complex manual resource allocation, as the differentiation is automated based on objective risk criteria.
Solution Approach 2:
The patent changes key parameters of the scanning process (frequency, depth, resource allocation) based on device risk characteristics and attack sphere priorities. The system automatically adjusts these parameters without requiring complex manual configuration, using defined criteria such as device type, geographic location, and vulnerability status to determine appropriate scanning intensity. This resolves the contradiction by improving protection effectiveness through parameter differentiation while keeping resource allocation management simple through automation.
3Use of energy by moving object
If manual triggering is used for vulnerability scans, then scanning resources are conserved, but detection responsiveness deteriorates
Solution Approach 1:
The patent applies preliminary action by proactively identifying devices that require scanning based on predicted attack spheres and emerging threats, before manual triggers are activated. The system pre-prioritizes devices in high-risk attack spheres and automatically initiates scanning when threats are detected, eliminating the need for manual triggering while conserving resources by not scanning all devices continuously. This resolves the contradiction by improving detection responsiveness for critical devices without excessive resource consumption.
Solution Approach 2:
The patent implements feedback mechanisms where scanning results, threat intelligence, and attack sphere updates continuously inform resource allocation decisions. The system learns from scanning outcomes and threat patterns, automatically adjusting which devices require immediate scanning versus deferred scanning. This feedback loop enables responsive detection of high-risk devices while conserving resources by avoiding unnecessary scans of low-risk devices, resolving the contradiction between resource conservation and detection responsiveness.
Data Source
AI summary
System and methods are provided for building intelligence around IoT devices that can prioritize an attack sphere, such that scanning and protection can be focused on risky spheres before others that may be less at risk. The attack spheres include specific device types, vendors, geographic locations, demographics, or organizations. Priority based vulnerability scanning and protection is utilized along with the concept of attack spheres to define priority zones which may be unique. Priority computation based on trend analysis and predictive analysis is used to determine the vulnerability of specific devices and groups of devices. This will significantly reduce the attack exposure and ensures the proactive damage control.