CRSep 17, 2020
Password similarity using probabilistic data structuresDavide Berardi, Franco Callegati, Andrea Melis et al.
Passwords should be easy to remember, yet expiration policies mandate their frequent change. Caught in the crossfire between these conflicting requirements, users often adopt creative methods to perform slight variations over time. While easily fooling the most basic checks for similarity, these schemes lead to a substantial decrease in actual security, because leaked passwords, albeit expired, can be effectively exploited as seeds for crackers. This work describes an approach based on Bloom filters to detect password similarity, which can be used to discourage password reuse habits. The proposed scheme intrinsically obfuscates the stored passwords to protect them in case of database leaks, and can be tuned to be resistant to common cryptanalytic techniques, making it suitable for usage on exposed systems.
CRSep 21, 2016
Insider Threats in Emerging Mobility-as-a-Service ScenariosFranco Callegati, Saverio Giallorenzo, Andrea Melis et al.
Mobility as a Service (MaaS) applies the everything-as-a-service paradigm of Cloud Computing to transportation: a MaaS provider offers to its users the dynamic composition of solutions of different travel agencies into a single, consistent interface. Traditionally, transits and data on mobility belong to a scattered plethora of operators. Thus, we argue that the economic model of MaaS is that of federations of providers, each trading its resources to coordinate multi-modal solutions for mobility. Such flexibility comes with many security and privacy concerns, of which insider threat is one of the most prominent. In this paper, we follow a tiered structure --- from individual operators to markets of federated MaaS providers --- to classify the potential threats of each tier and propose the appropriate countermeasures, in an effort to mitigate the problems.