Passwords: Divided they Stand, United they Fall
Harshal Tupsamudre, Sachin Lodha

TL;DR
This paper introduces a novel partition attack model that analyzes password security by dividing the search space into partitions based on leaked data, revealing vulnerabilities and proposing countermeasures to improve password robustness.
Contribution
It proposes a general partition attack framework, demonstrates its effectiveness on real-world data, and suggests a system to counter such attacks by uniform partition distribution.
Findings
Partition attack model encompasses various attack techniques.
Real-world password databases are vulnerable to partition attacks.
Uniform partition densities can mitigate attack success.
Abstract
Today, offline attacks are one of the most severe threats to password security. These attacks have claimed millions of passwords from prominent websites including Yahoo, LinkedIn, Twitter, Sony, Adobe and many more. Therefore, as a preventive measure, it is necessary to gauge the offline guessing resistance of a password database and to help users choose secure passwords. The rule-based mechanisms that rely on minimum password length and different character classes are too naive to capture the intricate human behavior whereas those based on probabilistic models require the knowledge of an entire password distribution which is not always easy to learn. In this paper, we propose a space partition attack model which uses information from previous leaks, surveys, attacks and other sources to divide the password search space into non-overlapping partitions and learn partition densities. We…
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Taxonomy
TopicsUser Authentication and Security Systems · Advanced Malware Detection Techniques · Psychedelics and Drug Studies
