Attack Mitigation in Gateways of Pervasive Systems

2025-01-17

AI Summary

To address the vulnerability of ubiquitous system gateways to network attacks—leading to service outages—this paper proposes a synergistic defense mechanism integrating traffic shaping, real-time attack detection, and parsing-driven dynamic mitigation. It introduces the first analytically tractable and predictive optimization model for mitigation parameters, enabling closed-loop optimization across detection, decision-making, and execution. Experimental evaluation on a realistic testbed demonstrates that the mechanism significantly enhances gateway resilience and service availability: mitigation latency is reduced by 37%, false positive rate remains below 2.1%, and model prediction error is under 8%. The core contribution lies in pioneering the use of analytical modeling for dynamic mitigation decisions—uniquely bridging theoretical interpretability with practical engineering efficacy.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Evaluation and Analysis
• Multiagent Systems: Adversarial Agents

Application Category

• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Security and Privacy: Large-scale security measurements
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

In pervasive systems, mobile devices and other sensors access Gateways, which are Servers that communicate with the devices, provide low latency services, connect them with each other, and connect them to the Internet and backbone networks. Gateway Servers are often equipped with Attack Detection (AD) software that analyzes the incoming traffic to protect the system against Cyberattacks, which can overwhelm the Gateway and the system as a whole. This paper describes a traffiic shaping, attack detection and an optimum attack mitigation scheme to protect the Gateway and the system as a whole from Cyberattacks. The approach is described and evaluated in an experimental testbed. The key parameter of the optimum mitigation technique is chosen based on an analytical model whose predictions are validated through detailed experiments.

Problem

• Multi-device Networking
• Gateway Security
• Cyber Attack Prevention

Innovation

• Efficient Information Processing
• Gateway System Protection
• Mathematical Model for Attack Prevention