d-DSE: Distinct Dynamic Searchable Encryption Resisting Volume Leakage in Encrypted Databases
Developing a new perspective on handling volume leakage in encrypted databases through distinct search with the d-DSE scheme.
Recovering Frequencies from Poisoning Attacks against Local Differential Privacy
LDPRecover proposes a method to recover accurate aggregated frequencies from poisoning attacks under LDP protocols, even without knowledge of the attack details.
Order-Theoretical Foundation for Data Flow Security
The author establishes a direct correspondence between data security concepts and partial order concepts, simplifying established theories and offering efficient algorithms. The main thesis is that basic concepts in data security theory are applications of fundamental partial order theory.
AMUSE: Adaptive Multi-Segment Encoding for Dataset Watermarking
The author proposes AMUSE, an adaptive multi-segment encoding-decoding method for dataset watermarking, aiming to improve message extraction accuracy and watermarked dataset quality.
Distinct Dynamic Searchable Encryption (d-DSE) Resisting Volume Leakage in Encrypted Databases
The author presents a new approach, d-DSE, to handle volume leakage in encrypted databases by utilizing distinct search and security notions. The core argument revolves around the development of a practical solution for secure data search with reduced communication costs.
Data Extraction Vulnerabilities in Retrieval-Augmented Generation Systems
The author highlights the risk of data leakage in Retrieval-Augmented Generation systems due to instruction-following capabilities, showcasing vulnerabilities across various models and sizes.
Essential Steps for Data Protection Online
The author emphasizes the importance of taking proactive steps to protect personal data online through various strategies such as updating information, managing app permissions, and using secure passwords.
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