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Here, the perturbation equation for a dissipative medium is derived from the first principle from the linearized compressible Navier-Stokes equation without Stokes's hypothesis. The dispersion relations of this generic governing equation are obtained for one and three-dimensional perturbations, which exhibit both the dispersive and dissipative nature of the perturbations traveling in a dissipative medium, depending upon the length scale. We specifically provide a theoretical cut-off wave number above which the perturbation equation represents diffusive and dissipative nature. Such behavior has not been reported before, as per the knowledge of the authors., Comment: 12 page 1 figure. arXiv admin note: substantial text overlap with arXiv:2212.13795

Passwords are the most common mechanism for authenticating users online. However, studies have shown that users find it difficult to create and manage secure passwords. To that end, passphrases are often recommended as a usable alternative to passwords, which would potentially be easy to remember and hard to guess. However, as we show, user-chosen passphrases fall short of being secure, while state-of-the-art machine-generated passphrases are difficult to remember. In this work, we aim to tackle the drawbacks of the systems that generate passphrases for practical use. In particular, we address the problem of generating secure and memorable passphrases and compare them against user chosen passphrases in use. We identify and characterize 72, 999 user-chosen in-use unique English passphrases from prior leaked password databases. Then we leverage this understanding to create a novel framework for measuring memorability and guessability of passphrases. Utilizing our framework, we design MASCARA, which follows a constrained Markov generation process to create passphrases that optimize for both memorability and guessability. Our evaluation of passphrases shows that MASCARA-generated passphrases are harder to guess than in-use user-generated passphrases, while being easier to remember compared to state-of-the-art machine-generated passphrases. We conduct a two-part user study with crowdsourcing platform Prolific to demonstrate that users have highest memory-recall (and lowest error rate) while using MASCARA passphrases. Moreover, for passphrases of length desired by the users, the recall rate is 60-100% higher for MASCARA-generated passphrases compared to current system-generated ones., Comment: This paper appeared on ACM ASIACCS '23 conference. The pdf includes Github repository with all data and code