After each partial disclosure, the remaining unknown "dust" of the key—the unresolved characters—experiences a transient period where the probability distribution over possible completions is non-uniform. We define the "dust settling" as the moment when this distribution becomes statistically indistinguishable from uniform (maximum entropy) given the known constraints.
in the ideal case. However, due to checksum or validation constraints (e.g., a Luhn-like algorithm), the distribution over ( K_U ) may be biased. Define the dust ( D(t) ) at discrete time ( t ) (number of brute-force attempts) as the Kullback-Leibler divergence from the uniform distribution over valid completions: serial key dust settle
No prior work has quantified how long (in terms of computational steps or guesses) it takes for this dust to settle. This paper fills that gap. 2. Formal Model 2.1 Key Representation Let a serial key be a string ( K = k_1 k_2 \ldots k_n ) where each ( k_i \in \Sigma ), ( |\Sigma| = 32 ) (alphanumeric excluding ambiguous chars). Total keyspace size ( N = 32^n ). 2.2 Partial Disclosure Event An attacker learns a set of positions ( P \subset 1,\ldots,n ) and their values. Let ( U = 1,\ldots,n \setminus P ) be the unknown positions. Before any attack, entropy ( H(K) = n \log_2 32 ). After disclosure, conditional entropy: After each partial disclosure, the remaining unknown "dust"