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Evaluates the economic viability of mass surveillance in information security, suggesting new frameworks.
Traditional cryptographic evaluation models assess security within an abstract mathematical vacuum, asking primarily whether an adversary can theoretically invert a cipher given unlimited resources. While mathematically rigorous, this paradigm fails to model real-world threat economics, particularly under modern Harvest Now, Decrypt Later (HNDL) surveillance frameworks where the marginal cost of bulk payload interception approaches zero. This paper introduces a macroeconomic and thermodynamic framework for threat modeling: The Constraint Economics of Surveillance, developed under Constrained Systems Principles (CSP). By coupling CSP to the non-self-contained semantic carriers of Information Reconstruction Theory (IRT) (๐ผ๐ =๐ (๐ก,๐)), we reframe information security from an arms race of computational hardness into an explicit resource audit of the observer [1]. We formalize the total attack cost (๐ถ๐ด) across five operational phasesโGathering (๐ถ๐บ), Storage (๐ถ๐), Correlation (๐ถ๐ถ), Reconstruction (๐ถ๐ ), and Endpoint Compromise (๐ถ๐ธ)โusing dimensionally valid conversion parameters (๐๐ธ,๐๐,๐๐ผ). We derive the adversarial Return on Gain (๐ ๐บ) metric using formal conditional probability chains, proving how architectural uncertainty at the interpretation layer (๐Interp) depresses aggregate success probabilities while exponentially driving up state reconstruction energy (๐ธreconstruct). Under IRT, bulk recording degrades from a rational "lottery ticket" investment into a bankrupting, high-entropy resource trap. Ultimately, we prove that systemic security does not require an infinitely unbreakable cipher, but rather an architectural guarantee that total thermodynamic, infrastructure, and correlation costs force the adversaryโs Return on Gain below unity (๐ ๐บ<1), rendering mass surveillance economically non-viable. Keywords: Cryptographic Economics, Harvest Now Decrypt Later (HNDL), Constrained Systems Principles (CSP), Conditional Entropy, Multi-Channel Security, Interpretation Layer Security (ILS), Post-Quantum Defense..
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Michelle Cannon (2026) studied this question.
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