Economic Denial Security Framework for IoT and Edge Defense
A recent study published on arXiv proposes a novel approach called Economic Denial Security (EDS) aimed at increasing the costs associated with cyberattacks. This strategy particularly addresses advanced attackers who use encryption to remain undetected in resource-constrained IoT and edge environments where conventional defenses fall short. EDS employs four main methods to escalate attack expenses: adaptive computational challenges, decoy-driven interaction entropy, temporal stretching, and bandwidth taxing. Game theory evaluations indicate that implementing multiple strategies can raise attack costs by a factor of 2.1 compared to relying on a single tactic. This submission has undergone revisions.
Key facts
- Paper arXiv:2512.23849 introduces Economic Denial Security (EDS)
- EDS renders attacks economically infeasible instead of detecting them
- Targets IoT and edge environments with limited resources
- Four mechanisms: adaptive computational puzzles, decoy-driven interaction entropy, temporal stretching, bandwidth taxation
- Game theory used to mathematically prove optimal configuration
- Combining multiple safety mechanisms costs 2.1 times more than using them separately
- Submission type: replace-cross (revised version)
- Addresses evasion tactics like encryption, stealth, and low-rate attack patterns
Entities
Institutions
- arXiv