This academic article by Samantha Aziz and Oleg Komogortsev from Texas State University investigates the privacy risks associated with using eye movement biometrics for cross-platform identity linkage. The study reveals…
Continue readingThe article introduces PromptCrypt, a novel encryption mechanism designed to enhance user privacy in cloud-based language models (LLMs) like ChatGPT. The method encrypts user inputs with Emoji, making the data…
Continue readingThe emergence and increased use of large language models (LLMs) in user-facing systems have led to significant privacy concerns. These concerns have been primarily model-centered, exploring how LLMs lead to…
Continue readingThe paper focuses on the potential benefits and challenges of integrating Large Language Models (LLMs) into Extended Reality (XR) environments. The authors argue that embedding LLMs into XR can lead…
Continue readingThe article discusses the development of a Secure-Aggregation (SecAgg) algorithm for residential short-term load forecasting, which maintains data privacy while also being robust against attacks. The algorithm minimizes communication complexity…
Continue readingThis study presents a new system designed to protect against eavesdropping by jamming microphones with a unique phoneme-based noise. This noise is designed to distract both humans and machines and…
Continue readingThis work explores the relationship between Spotify users’ attributes and their public playlists, focusing on identifying recurring musical characteristics associated with users’ individual attributes like demographics, habits, or personality traits….
Continue readingThe paper ‘SunBlock: Cloudless Protection for IoT Systems’ addresses the increasing security threats and privacy risks associated with the rise of Internet of Things (IoT) devices in homes. Traditional IoT…
Continue readingThis paper presents MAPPING, a model-agnostic framework for debiasing Graph Neural Networks (GNNs) to ensure fair node classification and reduce leakage of sensitive information. Despite the success of GNNs in…
Continue readingThis article presents a study on the feasibility of implementing a spatial-provenance framework in Vehicle-to-Everything (V2X) networks using ZigBee and LoRa devices. The proposed solution addresses the challenge of balancing…
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