Performance Guarantees for Data Freshness in Resource-Constrained Adversarial IoT Systems

2025-12-19

AI Summary

Adversarial attacks degrade Age of Information (AoI) in resource-constrained IoT systems. Method: We model a two-source M/G/1/1 queue incorporating Poisson negative arrivals and stochastic service slowdown to capture malicious interference, and—novelty—we integrate the G-queue framework into adversarial AoI analysis, proposing a worst-case bounded attack model grounded in stochastic dominance. Contribution/Results: Leveraging moment-generating functions and queueing theory, we derive closed-form analytical expressions for AoI under arbitrary numbers of sources, and establish provably tight upper bounds on both average and peak AoI. Numerical evaluations confirm that the model accurately characterizes AoI degradation arising from the coupling of resource constraints and adversarial interference, with theoretical bounds significantly tighter than those in prior work.

Technology Category

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

Application Category

• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization

Abstract

Timely updates are critical for real-time monitoring and control applications powered by the Internet of Things (IoT). As these systems scale, they become increasingly vulnerable to adversarial attacks, where malicious agents interfere with legitimate transmissions to reduce data rates, thereby inflating the age of information (AoI). Existing adversarial AoI models often assume stationary channels and overlook queueing dynamics arising from compromised sensing sources operating under resource constraints. Motivated by the G-queue framework, this paper investigates a two-source M/G/1/1 system in which one source is adversarial and disrupts the update process by injecting negative arrivals according to a Poisson process and inducing i.i.d. service slowdowns, bounded in attack rate and duration. Using moment generating functions, we then derive closed-form expressions for average and peak AoI for an arbitrary number of sources. Moreover, we introduce a worst-case constrained attack model and employ stochastic dominance arguments to establish analytical AoI bounds. Numerical results validate the analysis and highlight the impact of resource-limited adversarial interference under general service time distributions.

Problem

• Analyzes adversarial attacks on IoT data freshness under resource constraints
• Models two-source system with adversarial interference and service slowdowns
• Derives closed-form expressions for average and peak Age of Information

Innovation

• Two-source M/G/1/1 system with adversarial negative arrivals
• Closed-form AoI expressions using moment generating functions
• Worst-case constrained attack model with stochastic dominance bounds