Smart Home Security System with Behavioral Anomaly Detection
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Solution Overview
Problem
Smart home security systems face vulnerabilities due to weak authentication mechanisms in original equipment manufacturer (OEM) network appliances, allowing potential threats from invalid users accessing the system via stolen identities, which can lead to unauthorized control of devices such as lights and doors.
Innovation Solution
A smart home security system that includes a network gateway communicating with OEM servers, a behavior model processor modeling expected household behavior, and an anomaly detector to identify and flag anomalous control messages, with a notification server sending alerts to administrators' devices for approval before executing potentially unauthorized commands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional authentication mechanisms are used in smart home systems, then device compatibility and ease of operation are maintained, but security vulnerability increases due to stolen identities and weak authentication
Solution Approach 1:
The patent introduces a behavior modeling service as an intermediary between the control message receiver and the appliance executor. This service analyzes control messages against learned household behavior patterns before execution, acting as a mediator that enhances security without requiring changes to existing authentication mechanisms or user operations.
Solution Approach 2:
The system performs preliminary behavior analysis on control messages before they are executed on appliances. By pre-establishing household behavior models and pre-analyzing incoming control messages against these models, the system proactively identifies potential security threats before they can cause harm, rather than reacting after authentication failure.
2Reliability
If behavior modeling and anomaly detection are implemented, then security against unauthorized access is improved, but system complexity increases
Solution Approach 1:
The patent segments the security system into distinct functional modules: a behavior modeling service that learns household patterns, an anomaly detector that analyzes control messages, and existing authentication components. This modular segmentation allows the complex behavior analysis functionality to be added without overwhelming the overall system architecture or requiring complete redesign of existing components.
Solution Approach 2:
The behavior modeling service acts as an intermediary layer that sits between the control message receiver and appliance executor. This intermediary approach allows complex security analysis to be performed without directly modifying or complicating the existing authentication and appliance control systems, thereby containing complexity within a specific module rather than propagating it throughout the entire system.
3Measurement precision
If deep packet inspection with signature checking is used, then intrusion detection capability is improved, but processing time and energy consumption increase
Solution Approach 1:
The patent changes the detection parameters from static signature matching to dynamic behavior pattern analysis. Instead of checking control messages against predetermined intrusion signatures, the system learns normal household behavior patterns and detects anomalies based on deviations from these patterns. This parameter change enables more accurate intrusion detection while reducing processing time, as behavior patterns can be recognized more efficiently than performing deep packet inspection with multiple signature checks.
Data Source
AI summary
A system includes a network gateway in communication with a plurality of servers, a household behavior model processor which models a household behavior model based at least on expected usage of each of a plurality of network appliances, wherein each one appliance of the plurality of network appliances is associated with one of the plurality of servers, and behavior of users associated with the network gateway, an anomaly detector which determines, on the basis of the household behavior model, if an anomalous control message which has been sent to one of the plurality of network appliances from one of the servers has been received at the network gateway, and a notification server which sends a notification to an application on an administrator's device upon receipt of the anomalous control message at the network gateway. Related systems, apparatus, and methods are also described.