Bill Kay
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View article: Entropic Analysis of Time Series Through Kernel Density Estimation
Entropic Analysis of Time Series Through Kernel Density Estimation Open
View article: Permutation Entropy for Signal Analysis
Permutation Entropy for Signal Analysis Open
Shannon Entropy is the preeminent tool for measuring the level of uncertainty (and conversely, information content) in a random variable. In the field of communications, entropy can be used to express the information content of given signa…
View article: A comprehensive guide to CAN IDS data and introduction of the ROAD dataset
A comprehensive guide to CAN IDS data and introduction of the ROAD dataset Open
Although ubiquitous in modern vehicles, Controller Area Networks (CANs) lack basic security properties and are easily exploitable. A rapidly growing field of CAN security research has emerged that seeks to detect intrusions or anomalies on…
View article: Permutation Entropy for Signal Analysis
Permutation Entropy for Signal Analysis Open
Shannon Entropy is the preeminent tool for measuring the level of uncertainty (and conversely, information content) in a random variable. In the field of communications, entropy can be used to express the information content of given signa…
View article: Hypergraph Topological Features for Autoencoder-Based Intrusion Detection for Cybersecurity Data
Hypergraph Topological Features for Autoencoder-Based Intrusion Detection for Cybersecurity Data Open
In this position paper, we argue that when hypergraphs are used to capture multi-way local relations of data, their resulting topological features describe global behaviour. Consequently, these features capture complex correlations that ca…
View article: Stepping out of Flatland: Discovering Behavior Patterns as Topological Structures in Cyber Hypergraphs
Stepping out of Flatland: Discovering Behavior Patterns as Topological Structures in Cyber Hypergraphs Open
Data breaches and ransomware attacks occur so often that they have become part of our daily news cycle. This is due to a myriad of factors, including the increasing number of internet-of-things devices, shift to remote work during the pand…
View article: Malicious Cyber Activity Detection Using Zigzag Persistence
Malicious Cyber Activity Detection Using Zigzag Persistence Open
In this study we synthesize zigzag persistence from topological data analysis with autoencoder-based approaches to detect malicious cyber activity and derive analytic insights. Cybersecurity aims to safeguard computers, networks, and serve…
View article: Community Detection in Hypergraphs via Mutual Information Maximization
Community Detection in Hypergraphs via Mutual Information Maximization Open
The hypergraph community detection problem seeks to identify groups of related nodes in hypergraph data. We propose an information-theoretic hypergraph community detection algorithm which compresses the observed data in terms of community …
View article: Community Detection in Hypergraphs via Mutual Information Maximization
Community Detection in Hypergraphs via Mutual Information Maximization Open
The hypergraph community detection problem seeks to identify groups of related nodes in hypergraph data. We propose an information-theoretic hypergraph community detection algorithm which compresses the observed data in terms of community …
View article: Seven open problems in applied combinatorics
Seven open problems in applied combinatorics Open
We present and discuss seven different open problems in applied combinatorics. The application areas relevant to this compilation include quantum computing, algorithmic differentiation, topological data analysis, iterative methods, hypergr…
View article: Topological Analysis of Temporal Hypergraphs
Topological Analysis of Temporal Hypergraphs Open
In this work we study the topological properties of temporal hypergraphs. Hypergraphs provide a higher dimensional generalization of a graph that is capable of capturing multi-way connections. As such, they have become an integral part of …
View article: Seven open problems in applied combinatorics
Seven open problems in applied combinatorics Open
We present and discuss seven different open problems in applied combinatorics. Additionally, the application areas relevant to this compilation include quantum computing, algorithmic differentiation, topological data analysis, iterative me…
View article: Neuromorphic Computing is Turing-Complete
Neuromorphic Computing is Turing-Complete Open
Neuromorphic computing is a non-von Neumann computing paradigm that performs computation by emulating the human brain. Neuromorphic systems are extremely energy-efficient and known to consume thousands of times less power than CPUs and GPU…
View article: Publisher Correction: Opportunities for neuromorphic computing algorithms and applications
Publisher Correction: Opportunities for neuromorphic computing algorithms and applications Open
View article: Opportunities for neuromorphic computing algorithms and applications
Opportunities for neuromorphic computing algorithms and applications Open
View article: Models and Methods for Sparse (Hyper)Network Science in Business, Industry, and Government
Models and Methods for Sparse (Hyper)Network Science in Business, Industry, and Government Open
The authors are hosting an AMS sponsored Mathematics Research Community (MRC) focusing on two themes that have garnered intense attention in network models of complex relational data: (1) how to faithfully model multi-way relations in hype…
View article: Threshold progressions in covering and packing contexts
Threshold progressions in covering and packing contexts Open
Here, using standard methods (due to Janson, Stein–Chen, and Talagrand) from probabilistic combinatorics, we explore the following general theme: As one progresses from each member of a family of objects $\\mathcal{A}$ being “covered” by a…
View article: Smoky Mountain Data Challenge 2021: An Open Call to Solve Scientific Data Challenges Using Advanced Data Analytics and Edge Computing
Smoky Mountain Data Challenge 2021: An Open Call to Solve Scientific Data Challenges Using Advanced Data Analytics and Edge Computing Open
View article: Efficient Contingency Analysis in Power Systems via Network Trigger Nodes
Efficient Contingency Analysis in Power Systems via Network Trigger Nodes Open
Modeling failure dynamics within a power system is a complex and challenging process due to multiple inter-dependencies and convoluted inter-domain relationships. Subject matter experts (SMEs) are interested in understanding these failure …
View article: Identification of Critical Infrastructure via PageRank
Identification of Critical Infrastructure via PageRank Open
Assessing critical infrastructure vulnerabilities is paramount to arranging efficient plans for their protection. Critical infrastructures are cyber-physical systems that can be represented as a network consisting of nodes and edges and hi…
View article: Avoiding Excess Computation in Asynchronous Evolutionary Algorithms
Avoiding Excess Computation in Asynchronous Evolutionary Algorithms Open
View article: Improved Bounds for Burning Fence Graphs
Improved Bounds for Burning Fence Graphs Open
View article: Accurate and Accelerated Neuromorphic Network Design Leveraging A Bayesian Hyperparameter Pareto Optimization Approach
Accurate and Accelerated Neuromorphic Network Design Leveraging A Bayesian Hyperparameter Pareto Optimization Approach Open
Neuromorphic systems allow for extremely efficient hardware implementations for neural networks (NNs). In recent years, several algorithms have been presented to train spiking NNs (SNNs) for neuromorphic hardware. However, SNNs often provi…
View article: Computational Complexity of Neuromorphic Algorithms
Computational Complexity of Neuromorphic Algorithms Open
Neuromorphic computing has several characteristics that make it an extremely compelling computing paradigm for post Moore computation. Some of these characteristics include intrinsic parallelism, inherent scalability, collocated processing…
View article: Neuromorphic Graph Algorithms: Cycle Detection, Odd Cycle Detection, and Max Flow
Neuromorphic Graph Algorithms: Cycle Detection, Odd Cycle Detection, and Max Flow Open
Neuromorphic computing is poised to become a promising computing paradigm in the post Moore’s law era due to its extremely low power usage and inherent parallelism. Spiking neural networks are the traditional use case for neuromorphic syst…
View article: Sparse Binary Matrix-Vector Multiplication on Neuromorphic Computers
Sparse Binary Matrix-Vector Multiplication on Neuromorphic Computers Open
Neuromorphic computers offer the opportunity for low-power, efficient computation. Though they have been primarily applied to neural network tasks, there is also the opportunity to leverage the inherent characteristics of neuromorphic comp…
View article: Neuromorphic Computing is Turing-Complete
Neuromorphic Computing is Turing-Complete Open
Neuromorphic computing is a non-von Neumann computing paradigm that performs computation by emulating the human brain. Neuromorphic systems are extremely energy-efficient and known to consume thousands of times less power than CPUs and GPU…
View article: ROAD: The Real ORNL Automotive Dynamometer Controller Area Network Intrusion Detection Dataset (with a comprehensive CAN IDS dataset survey & guide).
ROAD: The Real ORNL Automotive Dynamometer Controller Area Network Intrusion Detection Dataset (with a comprehensive CAN IDS dataset survey & guide). Open
The Controller Area Network (CAN) protocol is ubiquitous in modern vehicles, but the protocol lacks many important security properties, such as message authentication. To address these insecurities, a rapidly growing field of research has …
View article: Real ORNL Automotive Dynamometer (ROAD) CAN Intrusion Dataset
Real ORNL Automotive Dynamometer (ROAD) CAN Intrusion Dataset Open
The Real ORNL Automotive Dynamometer (ROAD) CAN IDS dataset consistis of over 3.5 hours of one vehicle's CAN data. ROAD contains ambient data recorded during a diverse set of activities, and attacks of increasing stealth with multiple vari…
View article: Real ORNL Automotive Dynamometer (ROAD) CAN Intrusion Dataset
Real ORNL Automotive Dynamometer (ROAD) CAN Intrusion Dataset Open
<p>The Real ORNL Automotive Dynamometer (ROAD) CAN IDS dataset consistis of over 3.5 hours of one vehicle's CAN data. ROAD contains ambient data recorded during a diverse set of activities, and attacks of increasing stealth with…