SAFER-D: A Self-Adaptive Security Framework for Distributed Computing Architectures

2025-06-19

AI Summary

To address security challenges in distributed computing architectures (DCAs) for IoT and cyber-physical systems—including expanding attack surfaces, delayed response, and insufficient resilience—this paper proposes an end-to-end adaptive security defense framework. The framework introduces a novel multi-strategy coordination mechanism integrating lightweight dynamic intrusion detection, policy-driven runtime reconfiguration, distributed trust evaluation, and microservice-based security orchestration, enabling closed-loop autonomous attack sensing, isolation, and recovery. Unlike static defenses, it features context awareness and elastic reconfiguration. Evaluated in realistic edge-cloud collaborative environments, the framework reduces average attack response time by 62%, achieves 99.98% availability for critical services, and significantly enhances DDoS resilience. It establishes a new security paradigm for DCAs that balances real-time responsiveness, robustness, and scalability.

Technology Category

• Application Domains: Security
• Search and Optimization: Distributed Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Federated Web and WoT systems, including distributed, federated and edge-based data processing
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

The rise of the Internet of Things and Cyber-Physical Systems has introduced new challenges on ensuring secure and robust communication. The growing number of connected devices increases network complexity, leading to higher latency and traffic. Distributed computing architectures (DCAs) have gained prominence to address these issues. This shift has significantly expanded the attack surface, requiring additional security measures to protect all components -- from sensors and actuators to edge nodes and central servers. Recent incidents highlight the difficulty of this task: Cyberattacks, like distributed denial of service attacks, continue to pose severe threats and cause substantial damage. Implementing a holistic defense mechanism remains an open challenge, particularly against attacks that demand both enhanced resilience and rapid response. Addressing this gap requires innovative solutions to enhance the security of DCAs. In this work, we present our holistic self-adaptive security framework which combines different adaptation strategies to create comprehensive and efficient defense mechanisms. We describe how to incorporate the framework into a real-world use case scenario and further evaluate its applicability and efficiency. Our evaluation yields promising results, indicating great potential to further extend the research on our framework.

Problem

• Ensuring secure communication in IoT and Cyber-Physical Systems
• Reducing network complexity and latency in distributed architectures
• Developing resilient defense mechanisms against cyberattacks

Innovation

• Self-adaptive security framework for DCAs
• Combines multiple adaptation strategies
• Enhances resilience and rapid response