Defending Against Deep Learning-Based Traffic Fingerprinting Attacks With Adversarial Examples
In an increasingly digital and interconnected world, online anonymity and privacy are paramount issues for Internet users. To address this, tools like The Onion Router (Tor) offer anonymous and private communication by routing traffic through multiple ...
ArmSpy++: Enhanced PIN Inference through Video-based Fine-grained Arm Posture Analysis
As one of the most common ways for user authentication, Personal Identification Number (PIN), due to its simplicity and convenience, has suffered from plenty of side-channel attacks, which pose a severe threat to people’s privacy and property. The success ...
Category-Based Administrative Access Control Policies
As systems evolve, security administrators need to review and update access control policies. Such updates must be carefully controlled due to the risks associated with erroneous or malicious policy changes. We propose a category-based access control (...
Formal Security Analysis of the OpenID FAPI 2.0 Family of Protocols: Accompanying a Standardization Process
FAPI 2.0 is a suite of Web protocols developed by the OpenID Foundation’s FAPI Working Group (FAPI WG) for third-party data sharing and digital identity in high-risk environments. Even though the specifications are not completely finished, several ...
Cyber Threat Intelligence meets the Analytic Tradecraft
The volumes and sophistication of cyber threats in today’s cyber threat landscape have risen to levels where automated quantitative tools for Cyber Threat Intelligence (CTI) have become an indispensable part in the cyber defense arsenals. The AI and cyber ...
DP-Poison: Poisoning Federated Learning under the Cover of Differential Privacy
Federated learning (FL) enables resource-constrained node devices to learn a shared model while keeping the training data local. Since recent research has demonstrated multiple privacy leakage attacks in FL, e.g., gradient inference attacks and membership ...
Backdoor Attacks in Peer-to-Peer Federated Learning
Most machine learning applications rely on centralized learning processes, opening up the risk of exposure of their training datasets. While federated learning (FL) mitigates to some extent these privacy risks, it relies on a trusted aggregation server ...
The Effect of Domain Terms on Password Security
The predominant authentication method still relies on usernames and passwords. To enhance memorability, domain terms may have been opted to include as part of passwords. However, there is little analysis of the extent to which such practice affects ...
AutoFR: Automated Filter Rule Generation for Adblocking
Adblocking relies on filter lists, which are manually curated and maintained by a community of filter list authors. Filter list curation is a laborious process that does not scale well to a large number of sites or over time. In this article, we introduce ...
Understanding Information Disclosure from Secure Computation Output: A Comprehensive Study of Average Salary Computation
Secure multi-party computation has seen substantial performance improvements in recent years and is being increasingly used in commercial products. While a significant amount of work was dedicated to improving its efficiency under standard security models,...