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We describe a password generation scheme based on Markov models built from English text (specifically, Charles Dickens *A Tale Of Two Cities*). We show a (linear-running-time) bijection between random bitstrings of any desired length and generated text, ensuring that all passwords are generated with equal probability. We observe that the generated passwords appear to strike a reasonable balance between memorability and security. Using the system, we get 56-bit passwords like The cusay is wither? t, rather than passwords like tQ$%Xc4Ef.
Recent advances in generative machine learning models rekindled research interest in the area of password guessing. Data-driven password guessing approaches based on GANs, language models and deep latent variable models show impressive generalization
With the growing amount of cyber threats, the need for development of high-assurance cyber systems is becoming increasingly important. The objective of this paper is to address the challenges of modeling and detecting sophisticated network attacks, s
This paper gives the definition and property of a bit-pair shadow, and devises the three algorithms of a public key cryptoscheme called JUOAN that is based on a multivariate permutation problem and an anomalous subset product problem to which no sube
Intrusion detection is only a starting step in securing IT infrastructure. Prediction of intrusions is the next step to provide an active defense against incoming attacks. Current intrusion prediction methods focus mainly on prediction of either intr
In string bit models, the superstring emerges as a very long chain of bits, in which s fermionic degrees of freedom contribute positively to the ground state energy in a way to exactly cancel the destabilizing negative contributions of d=s bosonic de