A survey of machine and deep learning methods for internet of things (IoT) security
The Internet of Things (IoT) integrates billions of smart devices that can communicate with
one another with minimal human intervention. IoT is one of the fastest developing fields in …
one another with minimal human intervention. IoT is one of the fastest developing fields in …
Deep learning in mobile and wireless networking: A survey
The rapid uptake of mobile devices and the rising popularity of mobile applications and
services pose unprecedented demands on mobile and wireless networking infrastructure …
services pose unprecedented demands on mobile and wireless networking infrastructure …
IoT vulnerability assessment for sustainable computing: threats, current solutions, and open challenges
Over the last few decades, sustainable computing has been widely used in areas like social
computing, artificial intelligence-based agent systems, mobile computing, and Internet of …
computing, artificial intelligence-based agent systems, mobile computing, and Internet of …
Improving attacks on round-reduced speck32/64 using deep learning
A Gohr - Advances in Cryptology–CRYPTO 2019: 39th Annual …, 2019 - Springer
This paper has four main contributions. First, we calculate the predicted difference
distribution of Speck32/64 with one specific input difference under the Markov assumption …
distribution of Speck32/64 with one specific input difference under the Markov assumption …
Salsa: Attacking lattice cryptography with transformers
Currently deployed public-key cryptosystems will be vulnerable to attacks by full-scale
quantum computers. Consequently," quantum resistant" cryptosystems are in high demand …
quantum computers. Consequently," quantum resistant" cryptosystems are in high demand …
Machine learning-assisted differential distinguishers for lightweight ciphers
A Baksi, A Baksi - Classical and Physical Security of Symmetric Key …, 2022 - Springer
At CRYPTO'19, Gohr first introduces the deep learning-based cryptanalysis on round-
reduced SPECK. Using a deep residual network, Gohr trains several neural network-based …
reduced SPECK. Using a deep residual network, Gohr trains several neural network-based …
Enforcing security in Internet of Things frameworks: A systematic literature review
With the rise of the Internet of Things (IoT) technology, the number of IoT devices/sensors
has increased significantly. It is anticipated that large-scale sensor-based systems will …
has increased significantly. It is anticipated that large-scale sensor-based systems will …
A survey of deep learning techniques for cybersecurity in mobile networks
The widespread use of mobile devices, as well as the increasing popularity of mobile
services has raised serious cybersecurity challenges. In the last years, the number of …
services has raised serious cybersecurity challenges. In the last years, the number of …
Classical and physical security of symmetric key cryptographic algorithms
A Baksi - 2021 IFIP/IEEE 29th International Conference on Very …, 2021 - ieeexplore.ieee.org
Symmetric key cryptography is one of the cornerstones of security in the modern era of
electronic communication. The symmetric key algorithms, known as the ciphers, are to …
electronic communication. The symmetric key algorithms, known as the ciphers, are to …
Salsa fresca: Angular embeddings and pre-training for ml attacks on learning with errors
Learning with Errors (LWE) is a hard math problem underlying recently standardized post-
quantum cryptography (PQC) systems for key exchange and digital signatures. Prior work …
quantum cryptography (PQC) systems for key exchange and digital signatures. Prior work …