相关论文: Multiparty Selective Disclosure using Attribute-Ba…

Regulatory audits of AI systems increasingly rely on differential privacy (DP) to protect training data and model internals. We study audit design when the audited developer can strategically respond to the privacy-constrained audit…

Performing searches over encrypted data is a very current and active area. Several efficient solutions have been provided for the single-writer scenario in which all sensitive data originates with one party (the Data Owner) that encrypts it…

Proportional to the growth in the usage of Human Sensor Networks (HSN), the volume of the data exchange between Sensor devices is increasing at a rapid pace. In this paper, we have proposed an Energy Efficient Lightweight Encryption (EELWE)…

Large and well-annotated datasets are essential for advancing deep learning applications, however often costly or impossible to obtain by a single entity. In many areas, including the medical domain, approaches relying on data sharing have…

In this paper a homomorphic privacy preserving association rule mining algorithm is proposed which can be deployed in resource constrained devices (RCD). Privacy preserved exchange of counts of itemsets among distributed mining sites is a…

The Internet of Medical Things (IoMT) has revolutionized healthcare by transforming medical operations into standardized, interoperable services. However, this service-oriented model introduces significant security vulnerabilities in device…

Dynamic Searchable Encryption (DSE) has emerged as a solution to efficiently handle and protect large-scale data storage in encrypted databases (EDBs). Volume leakage poses a significant threat, as it enables adversaries to reconstruct…

Searchable symmetric encryption (SSE) for multi-owner model draws much attention as it enables data users to perform searches over encrypted cloud data outsourced by data owners. However, implementing secure and precise query, efficient…

Private multi-winner voting is the task of revealing $k$-hot binary vectors satisfying a bounded differential privacy (DP) guarantee. This task has been understudied in machine learning literature despite its prevalence in many domains such…

Due to privacy concerns, multi-party gradient tree boosting algorithms have become widely popular amongst machine learning researchers and practitioners. However, limited existing works have focused on vertically partitioned datasets, and…

Attribute-based access control makes access control decisions based on the assigned attributes of subjects and the access policies to protect objects by mediating operations from the subjects. Authority, which validates attributes of…

At Crypto'07, Goyal introduced the concept of Accountable Authority Identity-Based Encryption as a convenient tool to reduce the amount of trust in authorities in Identity-Based Encryption. In this model, if the Private Key Generator (PKG)…

With the support of cloud computing, large quantities of data collected from various WSN applications can be managed efficiently. However, maintaining data security and efficiency of data processing in cloud-WSN (C-WSN) are important and…

Anonymous Identity Based Encryption (AIBET) scheme allows a tracer to use the tracing key to reveal the recipient's identity from the ciphertext while keeping other data anonymous. This special feature makes AIBET a promising solution to…

This paper introduces a privacy-preserving distributed learning framework via private-key homomorphic encryption. Thanks to the randomness of the quantization of gradients, our learning with error (LWE) based encryption can eliminate the…

Although many distributed storage protocols have been introduced, a solution that combines the strongest properties in terms of availability, consistency, fault-tolerance, storage complexity and the supported level of concurrency, has been…

Traditional database access control mechanisms use role based methods, with generally row based and attribute based constraints for granularity, and privacy is achieved mainly by using views. However if only a set of views according to…

This paper studies information-theoretically secure quantum homomorphic encryption (QHE) schemes of classical data. Previous works on information-theoretically secure QHE schemes (like Childs'05, Liang'13, and others) are typically based on…

In this paper, we propose a new biometric verification and template protection system which we call the THRIVE system. The system includes novel enrollment and authentication protocols based on threshold homomorphic cryptosystem where the…

A symmetric searchable encryption (SSE) scheme allows a client (data owner) to search on encrypted data outsourced to an untrusted cloud server. The search may either be a single keyword search or a complex query search like conjunctive or…