The Race to Quantum-Proof the Internet Has Already Begun

The race to quantum-proof the internet is underway as experts warn of “harvest now, decrypt later” risks and slow migration to post-quantum security...

Decryption Thorough Polynomial Ambiguity: Noise-Enhanced High-Memory Convolutional Codes for Post-Quantum Cryptography

We present a novel approach to post-quantum cryptography that employs directed-graph decryption of noise-enhanced high-memory convolutional codes. The proposed construction generates random-like generator matrices that effectively conceal algebraic structure and resist known structural attacks...

Engel P-Adic Isogeny-Based Cryptography over Laurent Series: Foundations, Security, and an ESP32 Implementation

Securing the Internet of Things IoT against quantum attacks requires public-key cryptography that i remains compact and ii runs efficiently on microcontrollers, capabilities many post-quantum PQ schemes lack due to large keys and heavy arithmetic. We address both constraints simultaneously with, ...

Post-Quantum Security of Block Cipher Constructions

Block ciphers are versatile cryptographic ingredients that are used in a wide range of applications ranging from secure Internet communications to disk encryption. While post-quantum security of public-key cryptography has received significant attention, the case of symmetric-key cryptography and...

EUVD-2024-36566

Malicious code in bioql PyPI...

EUVD-2025-6671

Malicious code in bioql PyPI...

Threat Modeling for Enhancing Security of IoT Audio Classification Devices under a Secure Protocols Framework

The rapid proliferation of IoT nodes equipped with microphones and capable of performing on-device audio classification exposes highly sensitive data while operating under tight resource constraints. To protect against this, we present a defence-in-depth architecture comprising a security protoco...

Experimental Evaluation of Post-Quantum Homomorphic Encryption for Privacy-Preserving V2X Communication

Intelligent Transportation Systems ITS fundamentally rely on vehicle-generated data for applications such as congestion monitoring and route optimization, making the preservation of user privacy a critical challenge. Homomorphic Encryption HE offers a promising solution by enabling computation on...

Restricted Boltzmann Machine As a Probabilistic Enigma

We theoretically propose a symmetric encryption scheme based on Restricted Boltzmann Machines that functions as a probabilistic Enigma device, encoding information in the marginal distributions of visible states while utilizing bias permutations as cryptographic keys. Theoretical analysis reveals...

Engineering Trustworthy Machine-Learning Operations with Zero-Knowledge Proofs

As Artificial Intelligence AI systems, particularly those based on machine learning ML, become integral to high-stakes applications, their probabilistic and opaque nature poses significant challenges to traditional verification and validation methods. These challenges are exacerbated in regulated...

Efficient Full-Stack Private Federated Deep Learning with Post-Quantum Security

Federated learning FL enables collaborative model training while preserving user data privacy by keeping data local. Despite these advantages, FL remains vulnerable to privacy attacks on user updates and model parameters during training and deployment. Secure aggregation protocols have been...