Search Results
Crypto-Oriented Neural Architecture Design
As neural networks revolutionize many applications, significant privacy conflicts between model users and providers emerge.
Crypto-Nets: Neural Networks over Encrypted Data
To achieve the privacy requirements, we use homomorphic encryption in the following protocol: the data owner encrypts the data and sends the ciphertexts to the third party to obtain a prediction from a trained model.
Generalized Power Attacks against Crypto Hardware using Long-Range Deep Learning
To make cryptographic processors more resilient against side-channel attacks, engineers have developed various countermeasures.
Cryptography and Security
Accelerating Verified-Compiler Development with a Verified Rewriting Engine
Compilers are a prime target for formal verification, since compiler bugs invalidate higher-level correctness guarantees, but compiler changes may become more labor-intensive to implement, if they must come with proof patches.
Programming Languages F.3.1; D.2.4; F.4.2; D.3.4
A First Look at the Crypto-Mining Malware Ecosystem: A Decade of Unrestricted Wealth
Our analysis pipeline applies both static and dynamic analysis to extract information from the samples, such as wallet identifiers and mining pools.
Cryptography and Security
Market-Derived Financial Sentiment Analysis: Context-Aware Language Models for Crypto Forecasting
A domain-specific language model was fine-tuned on these labels, achieving up to an 11% improvement in short-term trend prediction accuracy over traditional sentiment-based benchmarks.
Where's Crypto?: Automated Identification and Classification of Proprietary Cryptographic Primitives in Binary Code
The continuing use of proprietary cryptography in embedded systems across many industry verticals, from physical access control systems and telecommunications to machine-to-machine authentication, presents a significant obstacle to black-box security-evaluation efforts.
Cryptography and Security 68M25 E.3
Review of deep learning models for crypto price prediction: implementation and evaluation
In this study, we review the literature about deep learning for cryptocurrency price forecasting and evaluate novel deep learning models for cryptocurrency stock price prediction.
Learning the Enigma with Recurrent Neural Networks
We demonstrate that RNNs can learn decryption algorithms -- the mappings from plaintext to ciphertext -- for three polyalphabetic ciphers (Vigen\`ere, Autokey, and Enigma).
Blockchain mechanism and distributional characteristics of cryptos
We investigate the relationship between underlying blockchain mechanism of cryptocurrencies and its distributional characteristics.
Cryptography and Security General Finance
