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K. Liang

118 records found

Current black-box backdoor attacks in convolutional neural networks formulate attack objective(s) as singleobjective optimization problems in single domain. Designing triggers in single domain harms semantics and trigger robustness as well as introduces visual and spectral anomal ...
Federated Learning (FL) is a beneficial decentralized learning approach for preserving the privacy of local datasets of distributed agents. However, the distributed property of FL and untrustworthy data introducing the vulnerability to backdoor attacks. In this attack scenario, a ...

FEVERLESS

Fast and Secure Vertical Federated Learning based on XGBoost for Decentralized Labels

Vertical Federated Learning (VFL) enables multiple clients to collaboratively train a global model over vertically partitioned data without leaking private local information. Tree-based models, like XGBoost and LightGBM, have been widely used in VFL to enhance the interpretation ...
This paper introduces the Biometrics Data Space framework, which is a secure ecosystem built on Data Spaces technology and it is designed to address the challenges of suspect identification during cross-border crime investigation. Apart from Data Spaces technology, the proposed f ...

d-DSE

Distinct Dynamic Searchable Encryption Resisting Volume Leakage in Encrypted Databases

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 search queries and potentially compromise th ...

MUDGUARD

Taming Malicious Majorities in Federated Learning using Privacy-preserving Byzantine-robust Clustering

Byzantine-robust Federated Learning (FL) aims to counter malicious clients and train an accurate global model while maintaining an extremely low attack success rate. Most existing systems, however, are only robust when most of the clients are honest. FLTrust (NDSS '21) and Zeno++ ...

Query Recovery from Easy to Hard

Jigsaw Attack against SSE

Searchable symmetric encryption schemes often unintentionally disclose certain sensitive information, such as access, volume, and search patterns. Attackers can exploit such leakages and other available knowledge related to the user's database to recover queries. We find that the ...

Inject Less, Recover More

Unlocking the Potential of Document Recovery in Injection Attacks Against SSE

Searchable symmetric encryption has been vulnerable to inference attacks that rely on uniqueness in leakage patterns. However, many keywords in datasets lack distinctive leakage patterns, limiting the effectiveness of such attacks. The file injection attacks, initially proposed b ...
It has become a trend for clients to outsource their encrypted databases to remote servers and then leverage the Searchable Encryption technique to perform secure data retrieval. However, the method has yet to be considered a crucial need for replication on searchable encrypted d ...

The Power of Bamboo

On the Post-Compromise Security for Searchable Symmetric Encryption

Dynamic searchable symmetric encryption (DSSE) enables users to delegate the keyword search over dynamically updated encrypted databases to an honest-but-curious server without losing keyword privacy. This paper studies a new and practical security risk to DSSE, namely, secret ke ...
The increasing popularity of remote Cloud File Sharing (CFS) has become a major concern for privacy breach of sensitive data. Aiming at this concern, we present a new resource sharing framework by integrating enterprise-side Attribute-Based Access Control/eXtensible Access Contro ...
Genotype imputation estimates missing genotypes from the haplotype or genotype reference panel in individual genetic sequences, which boosts the potential of genome-wide association and is essential in genetic data analysis. However, the genetic sequences involve people's privacy ...
Password hardening encryption (PHE) is an emerging primitive in recent years. It can resist offline attack brought by keyword guessing attack from server via adding a third party with crypto services joining the decryption process. This primitive enhances the password authenticat ...
Modeling password distributions is a fundamental problem in password security, benefiting the research and applications on password guessing, password strength meters, honey password vaults, etc. As one of the best segment-based password models, WordPCFG has been proposed to capt ...

HPAKE

Honey Password-authenticated Key Exchange for Fast and Safer Online Authentication

Password-only authentication is one of the most popular secure mechanisms for real-world online applications. But it easily suffers from a practical threat - password leakage, incurred by external and internal attackers. The external attacker may compromise the password file stor ...
This work aims to provide a more secure access control in Hyperledger Fabric blockchain by combining multiple ID’s, attributes, and policies with the components that regulate access control. The access control system currently used by Hyperledger Fabric is first completely analyz ...

FABRIC

Fast and secure unbounded cross-system encrypted data sharing in cloud computing

Existing proxy re-encryption (PRE) schemes to secure cloud data sharing raise challenges such as supporting the heterogeneous system efficiently and achieving the unbounded feature. To address this problem, we proposed a fast and secure unbounded cross-domain proxy re-encryption ...
Synthetic data generation plays a crucial role in many areas where data is scarce and privacy/confidentiality is a significant concern. Generative Adversarial Networks (GANs), arguably one of the most widely used data synthesis techniques, allow for the training of a model (i.e., ...

DEV-ETA

An Interpretable Detection Framework for Encrypted Malicious Traffic

Traffic encrypted technology enables Internet users to protect their data secrecy, but it also brings a challenge to malicious package detection. To tackle this issue, researchers have investigated into encrypted traffic analysis (ETA) in recent years. Existing works, however, on ...