Centralized Security Management System for 4G Wireless Networks
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Solution Overview
Problem
4G wireless networks face challenges in detecting and mitigating malicious data packets, particularly in wireless environments where abnormal operating conditions can masquerade as denial of service attacks, making it difficult for service providers to defend without additional resources and knowledge of the network environment.
Innovation Solution
A centralized security management system that collects data from network devices, determines baseline operations, identifies anomalies, and uses behavioral engines to differentiate between normal and malicious activity, employing correlation and mitigation techniques across various technologies and devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If manufacturers and service providers create devices and network solutions to detect malicious packets, then detection capability is improved, but the ability to detect perceived abnormal operating conditions remains insufficient
Solution Approach 1:
The system enables devices to monitor their own operational parameters and self-diagnose abnormal conditions. Each device reports its own state metrics (CPU usage, memory consumption, network activity patterns) to the centralized management system, allowing the system to detect anomalies based on actual device behavior rather than relying solely on pre-defined attack signatures.
Solution Approach 2:
The centralized management system continuously collects operational data from network devices, analyzes it against established baselines, and provides feedback about abnormal conditions. This feedback loop enables the system to adapt to evolving attack patterns by learning from actual device behavior and updating detection criteria dynamically.
2Reliability
If service providers implement comprehensive monitoring and mitigation systems, then security coverage is improved, but resource requirements and system complexity increase
Solution Approach 1:
The security management system is divided into functional segments: a centralized management system that handles analysis and decision-making, and distributed monitoring agents that collect data from individual devices. This segmentation allows each component to focus on specific tasks, reducing overall system complexity while maintaining comprehensive security coverage.
Solution Approach 2:
The centralized management system serves multiple functions: data collection, baseline establishment, anomaly detection, attack classification, and mitigation coordination. By consolidating these functions into a single system, the patent reduces the number of separate security devices needed and simplifies the overall architecture.
3Measurement precision
If the system collects and analyzes extensive data from network devices, then detection accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The system pre-establishes baseline operational parameters for network devices during normal operation. These baselines are stored and used for rapid comparison during anomaly detection. By performing the data collection and baseline establishment in advance, the system can quickly identify deviations from normal behavior without requiring extensive real-time analysis.
Solution Approach 2:
The system collects comprehensive data from multiple devices and parameters, but only analyzes and reports on deviations from established baselines. This approach allows the system to maintain high detection accuracy by examining all relevant data points while reducing processing time by focusing analysis only on anomalous patterns rather than continuously processing all data.
Data Source
AI summary
A centralized security management system (CSMS) is provided to monitor a network to detect and mitigate attacks in or to the network. The CSMS includes a variety of devices located throughout the network to collect and synthesize data collected or obtained from devices operating in the network. The collected data is analyzed using behavioral engines or other software algorithms to develop trends for a normal and abnormal operating condition. The abnormal operating conditions are analyzed further to determine attacks to the devices or the network. Based on the attacks, a mitigation scheme is implemented to remove or reduce the attacks.