Results 91 to 100 of about 1,338 (191)
Secure Data Handling in CI/CD Pipelines Using Homomorphic Encryption Techniques [PDF]
This study explores the use of homomorphic encryption (HE) in CI/CD pipelines to secure sensitive information during automated software delivery processes.
Parveen, Iqra
core
Engorgio: An Arbitrary-Precision Unbounded-Size Hybrid Encrypted Database via Quantized Fully Homomorphic Encryption [PDF]
This work proposes an encrypted hybrid database framework that combines vectorized data search and relational data query over quantized fully homomorphic encryption (FHE). We observe that, due to the lack of efficient encrypted data ordering capabilities,
Jiaqi Hu +10 more
core
An Approach to Reduce Storage for Homomorphic Computations [PDF]
We introduce a hybrid homomorphic encryption by combining public key encryption (PKE) and somewhat homomorphic encryption (SHE) to reduce storage for most applications of somewhat or fully homomorphic encryption (FHE).
Jung Hee Cheon, Jinsu Kim
core
Hybrid Cryptosystem with Martino Homomorphic Encryption and Generalization of The ElGamal
Digital data security has become a significant challenge in the ever-evolving digital era. Asymmetric cryptographic systems, such as the Generalization of the ElGamal, excel in providing high security due to the difficulty of solving discrete logarithms ...
Khairina, Annisa
core
Machine Learning (ML) has emerged as one of data science's most transformative and influential domains. However, the widespread adoption of ML introduces privacy-related concerns owing to the increasing number of malicious attacks targeting ML models. To
Nguyen, Khoa +4 more
core +2 more sources
Machine Learning Services by Homomorphic Encryption to Enhancing Privacy
Machine Learning (ML) is a crucial domain within data science, fostering advancements across several industries. Nonetheless, the rising threat of detrimental attacks on machine learning models presents significant privacy issues that may impede their ...
Yadkar, Mohammed Shamar +2 more
core +1 more source
Machine Learning (ML) has become one of the most impactful fields of data science in recent years. However, a significant concern with ML is its privacy risks due to rising attacks against ML models.
Nguyen, Khoa +4 more
core +1 more source
Security issues of telemedicine-based secure transmission of medical images find a very thin line drawn between diagnostic acceptability and cybersecurity. Partial but imperfect solutions emerge. JPEG2000 and HEVC concentrate only on compression, failing
Ashraf Al Sharah +6 more
doaj +1 more source
The IoT Smart grid systems require privacy-sensitive, scalable, and secure communication, but the traditional cryptographic methods are susceptible to quantum attacks, central failure, and high computational costs.
Prashant Kumar Shukla +4 more
doaj +1 more source
Enhancing foreign exchange reserve security for central banks using Blockchain, FHE, and AWS
In order to maintain the value of the national currency and control foreign debt, central banks are vital to the management of a nation’s foreign exchange reserves.
Khandakar Md Shafin, Saha Reno
doaj +1 more source

