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User profiling is a critical component of adaptive risk-based authentication, yet it raises significant privacy concerns, particularly when handling sensitive data. Profiling involves collecting and aggregating various user features,…
Credential theft and remote attacks are the most serious threats to user authentication mechanisms. The crux of these problems is that we cannot control such behaviors. However, if a password does not contain user secrets, stealing it is…
Risk-based authentication (RBA) is used in online services to protect user accounts from unauthorized takeover. RBA commonly uses contextual features that indicate a suspicious login attempt when the characteristic attributes of the login…
Face images are a rich source of information that can be used to identify individuals and infer private information about them. To mitigate this privacy risk, anonymizations employ transformations on clear images to obfuscate sensitive…
In this paper, we present a new approach for facial anonymization in images and videos, abbreviated as FIVA. Our proposed method is able to maintain the same face anonymization consistently over frames with our suggested identity-tracking…
Voice anonymization techniques have been found to successfully obscure a speaker's acoustic identity in short, isolated utterances in benchmarks such as the VoicePrivacy Challenge. In practice, however, utterances seldom occur in isolation:…
Anonymity is a desirable feature for vehicle-to-vehicle (V2V) communications, but it conflicts with other requirements such as non-repudiation and revocation. Existing, pseudonym-based V2V communications schemes rely on certificate…
One of the most important issues in peer-to-peer networks is anonymity. The major anonymity for peer-to-peer users concerned with the users' identities and actions which can be revealed by any other members. There are many approaches…
We introduce EL PASSO, a privacy-preserving, asynchronous Single Sign-On (SSO) system. It enables personal authentication while protecting users' privacy against both identity providers and relying parties, and allows selective attribute…
Anonymous data collection systems allow users to contribute the data necessary to build services and applications while preserving their privacy. Anonymity, however, can be abused by malicious agents aiming to subvert or to sabotage the…
Spectrally-efficient secure non-orthogonal multiple access (NOMA) has recently attained a substantial research interest for fifth generation development. This work explores crucial security issue in NOMA which is stemmed from utilizing the…
Enforcement of privacy regulation is essential for collaborative data analytics. In this work, we address a scenario in which two companies expect to securely join their datasets with respect to their common customers to maximize data…
Advancements in face recognition (FR) technologies have amplified privacy concerns, necessitating methods that protect identity while maintaining recognition utility. Existing face anonymization methods typically focus on obscuring identity…
Physically unclonable functions (PUFs) can be employed for device identification, authentication, secret key storage, and other security tasks. However, PUFs are susceptible to modeling attacks if a number of PUFs' challenge-response pairs…
Efficient user revocation is a necessary but challenging problem in many multi-user cryptosystems. Among known approaches, server-aided revocation yields a promising solution, because it allows to outsource the major workloads of system…
In the UNIX/Linux environment the kernel can log every command process created by every user using process accounting. This data has many potential uses, including the investigation of security incidents. However, process accounting data is…
Social key recovery mechanisms enable users to recover their vaults with the help of trusted contacts, or trustees, avoiding the need for a single point of trust or memorizing complex strings. However, existing mechanisms overlook the…
Third-party analysis on private records is becoming increasingly important due to the widespread data collection for various analysis purposes. However, the data in its original form often contains sensitive information about individuals,…
Risk-based authentication (RBA) aims to protect users against attacks involving stolen passwords. RBA monitors features during login, and requests re-authentication when feature values widely differ from previously observed ones. It is…
There are currently two approaches to anonymization: "utility first" (use an anonymization method with suitable utility features, then empirically evaluate the disclosure risk and, if necessary, reduce the risk by possibly sacrificing some…