IoT Data Security via Intermediary and Blockchain
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Solution Overview
Problem
IoT networks face significant challenges with data privacy and security due to vulnerabilities such as default passwords and 'backdoors' that can be exploited, leading to cyberattacks and data abuse, with IoT devices often having access to sensitive information like credit card numbers and personal data.
Innovation Solution
Implementing a system that segregates data by context using blockchain technologies to securely audit and manage access, with a federated or private blockchain for inter-category transactions, and machine-learning models to identify and prevent suspicious data usage patterns, classifying requests as normal, block, or request approval, and sending alerts to users for feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If IoT devices are deployed with default passwords and basic security configurations, then device complexity and ease of operation are improved, but security reliability deteriorates due to vulnerabilities and backdoors
Solution Approach 1:
The patent introduces an intermediary security system that sits between IoT devices and data systems. This intermediary monitors data access requests, validates device credentials, and enforces security policies without requiring complex security configurations on individual IoT devices. The intermediary handles authentication and authorization, allowing simple device operation while maintaining high security reliability through centralized control.
2Productivity
If data access is freely permitted to all IoT devices, then productivity and ease of operation are improved, but harmful factors increase due to unauthorized access and data abuse
Solution Approach 1:
The patent implements a feedback mechanism where the security system continuously monitors data access patterns from IoT devices. When suspicious or unauthorized access attempts are detected, the system provides feedback by blocking the request and potentially alerting administrators. This feedback loop enables productive data access for legitimate operations while automatically preventing harmful access patterns, thus maintaining both productivity and security.
3Reliability
If comprehensive security monitoring is implemented for all data access, then security reliability is improved, but device complexity and processing overhead increase
Solution Approach 1:
The patent extracts the complex security monitoring functionality from individual IoT devices and concentrates it in a centralized security system. The IoT devices themselves remain simple, generating only basic access requests. The complex tasks of authentication, authorization, and pattern analysis are performed by the external security system, thereby maintaining high security reliability without increasing device complexity at the IoT endpoint.
Data Source
AI summary
In an approach, a processor receives from a network device a request. A processor obtains from a database a device profile for the network device. A processor determines whether the device profile of the network device has a data usage pattern related to data identified by a data identifier. In response to determining the device profile has a related data usage pattern, a processor receives the related data usage pattern from the database. In response to determining the device profile does not have a related data usage pattern, a processor obtains a device type profile from the database. A processor classifies the data usage request based on at least one of the device profile and the device type profile. A processor executes a security action based on the classification of the data usage request. A processor stores the data usage request and executed security action to the database.