Related papers: Injection Attacks Against End-to-End Encrypted App…

Existing end-to-end-encrypted (E2EE) email systems, mainly PGP, have long been evaluated in controlled lab settings. While these studies have exposed usability obstacles for the average user and offer design improvements, there exist users…

File-based encryption (FBE) schemes have been developed by software vendors to address security concerns related to data storage. While methods of encrypting data-at-rest may seem relatively straightforward, the main proponents of these…

Today's mobile devices sense, collect, and store huge amounts of personal information, which users share with family and friends through a wide range of applications. Once users give applications access to their data, they must implicitly…

Deep learning has attracted broad interest in healthcare and medical communities. However, there has been little research into the privacy issues created by deep networks trained for medical applications. Recently developed inference attack…

Federated learning is known to be vulnerable to both security and privacy issues. Existing research has focused either on preventing poisoning attacks from users or on concealing the local model updates from the server, but not both.…

Trusted execution environments (TEEs) provide an environment for running workloads in the cloud without having to trust cloud service providers, by offering additional hardware-assisted security guarantees. However, main memory encryption…

There is an increase in global malware threats. To address this, an encryption-type ransomware has been introduced on the Android operating system. The challenges associated with malicious threats in phone use have become a pressing issue…

Message franking is an indispensable abuse mitigation tool for end-to-end encrypted (E2EE) messaging platforms. With it, users who receive harmful content can securely report that content to platform moderators. However, while real-world…

Mobile edge caching is a promising technology for the next-generation mobile networks to effectively offer service environment and cloud-storage capabilities at the edge of networks. By exploiting the storage and computing resources at the…

Modern applications are end-to-end encrypted to prevent data from being read or secretly modified. 5G tech nology provides ubiquitous access to these applications without compromising the application-specific performance and latency goals.…

This paper introduces a new attack on recent messaging systems that protect communication metadata. The main observation is that if an adversary manages to compromise a user's friend, it can use this compromised friend to learn information…

In order to preserve the privacy of the users demands from other users, in this paper we formulate a novel information theoretic Device-to-Device (D2D) private caching model by adding a trusted server. In the delivery phase, the trusted…

Recent studies improve on-device language model (LM) inference through end-cloud collaboration, where the end device retrieves useful information from cloud databases to enhance local processing, known as Retrieval-Augmented Generation…

Semantic communication is implemented based on shared background knowledge, but the sharing mechanism risks privacy leakage. In this letter, we propose an encrypted semantic communication system (ESCS) for privacy preserving, which combines…

Differential signaling is a method of data transmission that uses two complementary electrical signals to encode information. This allows a receiver to reject any noise by looking at the difference between the two signals, assuming the…

As privacy features in Android operating system improve, privacy-invasive apps may gradually shift their focus to non-standard and covert channels for leaking private user/device information. Such leaks also remain largely undetected by…

In this study, we analyze model inversion attacks with only two assumptions: feature vectors of user data are known, and a black-box API for inference is provided. On the one hand, limitations of existing studies are addressed by opting for…

Smartphones with the platforms of applications are gaining extensive attention and popularity. The enormous use of different applications has paved the way to numerous security threats. The threats are in the form of attacks such as…

Prompt-based approaches offer a cutting-edge solution to data privacy issues in continual learning, particularly in scenarios involving multiple data suppliers where long-term storage of private user data is prohibited. Despite delivering…

Open-weight language models are increasingly used in production settings, raising new security challenges. One prominent threat is backdoor attacks, in which adversaries embed hidden behaviors that activate under specific conditions.…