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中国地质大学科学技术发展院左仁广等 GPMR国家重点实验室. Earth-Science Reviews, May 2019, Deep learning and its application in geochemical mapping
多源；地学空间；数据；挖掘；研究热点；前沿
2021/10/20
近日，中国地质大学地质过程与矿产资源国家重点实验左仁广教授团队的最新研究成果在Earth-Science Reviews刊 发——Deep learning and its application in geochemical mapping。论文第一和通讯作者为左仁广教授。
Simulating Homomorphic Evaluation of Deep Learning Predictions
neural networks homomorphic encryption TFHE
2019/5/31
Convolutional neural networks (CNNs) is a category of deep neural networks that are primarily used for classifying image data. Yet, their continuous gain in popularity poses important privacy concerns...
Deep Learning based Side Channel Attacks in Practice
Deep Learning based Side-Channel Attacks Data Dimensionality Data Scaling
2019/5/29
A recent line of research has investigated a new profiling technique based on deep learning as an alternative to the well-known template attack. The advantage of this new profiling approach is twofold...
Deep Learning based Model Building Attacks on Arbiter PUF Compositions
physically unclonable function machine learning deep learning
2019/5/28
Robustness to modeling attacks is an important requirement for PUF circuits. Several reported Arbiter PUF com- positions have resisted modeling attacks. and often require huge computational resources ...
Bias-variance Decomposition in Machine Learning-based Side-channel Analysis
Side-channel analysis Machine learning Deep learning
2019/5/28
Machine learning techniques represent a powerful option in profiling side-channel analysis. Still, there are many settings where their performance is far from expected. In such occasions, it is very i...
DL-LA: Deep Learning Leakage Assessment: A modern roadmap for SCA evaluations
side channel leakage assessment deep learning
2019/5/21
In recent years, deep learning has become an attractive ingredient to side-channel analysis (SCA) due to its potential to improve the success probability or enhance the performance of certain frequent...
Dataset Bridges Human Vision and Machine Learning（图）
Dataset Bridges Human Vision Machine Learning
2019/10/30
Neuroscientists and computer vision scientists say a new dataset of unprecedented size -- comprising functional brain scans of four volunteers who each viewed 5,000 images -- will help researchers bet...
A Comprehensive Study of Deep Learning for Side-Channel Analysis
Side Channel Analysis Profiling Attacks Machine Learning
2019/5/5
In Side Channel Analysis, masking is known to be a reliable and robust counter-measure. Recently, several papers have focused on the application of the Deep Learning (DL) theory to improve the efficie...
One trace is all it takes: Machine Learning-based Side-channel Attack on EdDSA
Side-channel attacks EdDSA Machine learning
2019/4/10
Profiling attacks, especially those based on machine learning proved as very successful techniques in recent years when considering side-channel analysis of block ciphers implementations. At the same ...
nGraph-HE: A Graph Compiler for Deep Learning on Homomorphically Encrypted Data
Homomorphic encryption intermediate representation deep learning
2019/4/3
Homomorphic encryption (HE)---the ability to perform computation on encrypted data---is an attractive remedy to increasing concerns about data privacy in deep learning (DL). However, building DL model...
Make Some ROOM for the Zeros: Data Sparsity in Secure Distributed Machine Learning
secure computation machine learning
2019/3/13
Exploiting data sparsity is crucial for the scalability of many data analysis tasks. However, while there is an increasing interest in efficient secure computation protocols for distributed machine le...
TOWARDS DEEP LEARNING FOR ARCHITECTURE: A MONUMENT RECOGNITION MOBILE APP
Artificial Intelligence Machine Learning Deep Learning Convolutional Neural Networks
2019/3/4
In recent years, the diffusion of large image datasets and an unprecedented computational power have boosted the development of a class of artificial intelligence (AI) algorithms referred to as deep l...
CodedPrivateML: A Fast and Privacy-Preserving Framework for Distributed Machine Learning
privacy-preserving machine learning information-theoretic privacy
2019/2/26
How to train a machine learning model while keeping the data private and secure? We present CodedPrivateML, a fast and scalable approach to this critical problem. CodedPrivateML keeps both the data an...
Modeling Power Efficiency of S-boxes Using Machine Learning
Power Efficiency Optimal S-box Dynamic power
2019/2/26
In the era of lightweight cryptography, designing cryptographically good and power efficient 4x4 S-boxes is a challenging problem. While the optimal cryptographic properties are easy to determine, ver...
Noninteractive Zero Knowledge for NP from (Plain) Learning With Errors
noninteractive zero knowledge correlation intractability learning with errors
2019/2/25
We finally close the long-standing problem of constructing a noninteractive zero-knowledge (NIZK) proof system for any NP language with security based on the plain Learning With Errors (LWE) problem, ...