Security Without Detection: Economic Denial as a Primitive for Edge and IoT Defense
Samaresh Kumar Singh, Joyjit Roy

TL;DR
This paper introduces Economic Denial Security (EDS), a detection-independent framework that makes attacks economically infeasible in resource-constrained IoT and edge environments by employing adaptive mechanisms that significantly slow down attackers and increase their costs.
Contribution
The paper presents a novel detection-independent security framework, EDS, with formal game-theoretic analysis, provable cost amplification, and practical implementation on microcontrollers for IoT/edge defense.
Findings
Achieves 32-560x attack slowdown
Demonstrates 85-520:1 cost asymmetry
Reduces attack success by 8-62%
Abstract
Detection-based security fails against sophisticated attackers using encryption, stealth, and low-rate techniques, particularly in IoT/edge environments where resource constraints preclude ML-based intrusion detection. We present Economic Denial Security (EDS), a detection-independent framework that makes attacks economically infeasible by exploiting a fundamental asymmetry: defenders control their environment while attackers cannot. EDS composes four mechanisms adaptive computational puzzles, decoy-driven interaction entropy, temporal stretching, and bandwidth taxation achieving provably superlinear cost amplification. We formalize EDS as a Stackelberg game, deriving closed-form equilibria for optimal parameter selection (Theorem 1) and proving that mechanism composition yields 2.1x greater costs than the sum of individual mechanisms (Theorem 2). EDS requires < 12KB memory, enabling…
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Taxonomy
TopicsNetwork Security and Intrusion Detection · Advanced Malware Detection Techniques · Security and Verification in Computing
