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Designing a Block Cipher in Galois Extension Fields for IoT Security
(MDPI, 2021-11-05)
This paper focuses on a block cipher adaptation of the Galois Extension Fields (GEF) combination technique for PRNGs and targets application in the Internet of Things (IoT) space, an area where the combination technique ...
Further Analysis of PRNG-Based Key Derivation Functions
(IEEE, 2019)
The Internet of Things (IoT) is growing at a rapid pace. With everyday applications and services becoming wirelessly networked, security still is a major concern. Many of these sensors and devices have limitations, such ...
Framework for Evaluating the Severity of Cybervulnerability of a Traffic Cabinet
(National Academy of Sciences, 2017)
The increasing connectivity in transportation infrastructure is driving a need for additional security in transportation systems. For security decisions in a budget-constrained environment, the possible effect of a cyberattack ...
Attacks and Defenses for Single-Stage Residue Number System PRNGs
(MDPI, 2021-06-25)
This paper explores the security of a single-stage residue number system (RNS) pseudorandom number generator (PRNG), which has previously been shown to provide extremely high-quality outputs when evaluated through available ...
Fallthrough Correlation Techniques for Arbitrary-Phase Spread Spectrum Waveforms
(IEEE, 2019-09-11)
The use of practically non-repeating spreading codes to generate sequence-based spread spectrum waveforms is a strong method to improve transmission security, by limiting an observer's opportunity to cross-correlate snapshots ...
Real-Time Mask Recognition
(MDPI, 2021-11-08)
While a variety of image processing studies have been performed to quantify the potential performance of neural network-based models using high-quality still images, relatively few studies seek to apply those models to a ...
Shannon Entropy Loss in Mixed-Radix Conversions
(MDPI, 2021-07-27)
This paper models a translation for base-2 pseudorandom number generators (PRNGs) to mixed-radix uses such as card shuffling. In particular, we explore a shuffler algorithm that relies on a sequence of uniformly distributed ...
Transfer Learning for Radio Frequency Machine Learning: A Taxonomy and Survey
(MDPI, 2022-02-12)
Transfer learning is a pervasive technology in computer vision and natural language processing fields, yielding exponential performance improvements by leveraging prior knowledge gained from data with different distributions. ...
Specific Emitter Identification Using Convolutional Neural Network-Based IQ Imbalance Estimators
(IEEE, 2019)
Specific Emitter Identification is the association of a received signal to a unique emitter, and is made possible by the naturally occurring and unintentional characteristics an emitter imparts onto each transmission, known ...