Results 81 to 90 of about 462 (258)

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Fuzzy Searchable Symmetric Encryption: Design and Implementation of a Novel Scheme Toward Real-World Applications [PDF]

openMost services and applications employ cloud-based solutions to store user data. To provide users with the ability to perform search queries, these services typically encrypt the data with keys known to the server, allowing search results to be ...
RAGUSA, SIMONE
core  

Searchable symmetric encryption

, 2020
The paper aims to study the various Searchable Symmetric Encryption (SSE) schemes available [1,2,3,4,5] to understand the feasibility and efficiency of the schemes in helping to keep our data secure, when a huge amount of data is stored in a third-party ...
Thio, Brian Yu Li
core  

Multi-Client Symmetric Searchable Encryption with Forward Privacy [PDF]

, 2019
Symmetric Searchable encryption (SSE) is an encryption technique that allows users to search directly on their outsourced encrypted data, in a way that the privacy of both the files and the search queries is preserved. Naturally, with every search query,
Antonis Michalas, Alexandros Bakas
core  

The Power of Bamboo: On the Post-Compromise ty for Searchable Symmetric Encryption

, 2023
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.
Xu, P., Susilo, W., Xu, Peng, Picek, S., Liang, K., Chen, Tianyang, Susilo, Willy, Picek, Stjepan, Chen, T., Jin, H., Luo, Bo, Luo, B., Liang, Kaitai, Jin, Hai   +13 more
core   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source

SWiSSSE: System-Wide Security for Searchable Symmetric Encryption [PDF]

, 2023
This paper initiates a new direction in the design and analysis of searchable symmetric encryption (SSE) schemes. We provide the first comprehensive security model and definition for SSE that takes into account leakage from the entirety of the SSE system,
Bogdan Warinschi, Kenneth G. Paterson, Sikhar Patranabis, Zichen Gui   +3 more
core  

Verifiable and Searchable Symmetric Encryption Scheme Based on the Public Key Cryptosystem

, 2023
With the rapid development of Internet of Things technology and cloud computing technology, all industries need to outsource massive data to third-party clouds for storage in order to reduce storage and computing costs.
Shuai Li, Gangqiang Duan
core   +1 more source

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

Advanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas, Panagiotis Krokidas, Vasileios Vavourakis, Clara Essmann, George Giannakopoulos   +4 more
wiley   +1 more source

Forward and Backward Private Searchable Encryption from Constrained Cryptographic Primitives [PDF]

, 2017
Using dynamic Searchable Symmetric Encryption, a user with limited storage resources can securely outsource a database to an untrusted server, so that the database can still be searched and updated efficiently.
Ohrimenko, Olga, Olga Ohrimenko, Bost, Raphael, Minaud, Brice, Raphaël Bost, Brice Minaud   +5 more
core   +1 more source