Academic Articles & Research Papers

Smart Substation Communications and Cybersecurity: A Comprehensive Survey

Electrical grids generate, transport, distribute and deliver electrical power to consumers through a complex Critical Infrastructure which progressively shifted from an air-gaped to a connected architecture. Specifically, Smart Substations ...

Cybersecurity for Critical Infrastructures: Attack and Defense Modeling

Disruption of electric power operations can be catastrophic on national security and the economy. Due to the complexity of widely dispersed assets and the interdependences among computer, communication, and power infrastructures, the requir...

Cybersecurity for Industry 5.0: trends and gaps

Industry 5.0 promises to revolutionize the industry by focusing on human-centric, sustainability, and resilience empowered by emerging technologies such as Artificial Intelligence (AI) and digitalization. This paradigm shift is expected to ...

Cybersecurity and Blockchain Usage in Contemporary Business

The use of computers is becoming more and more common. The power and maliciousness of powerful attackers are increasing. Organizations must improve their ability to mitigate information security threats. Adequate protection is more critical...

Cybersecurity and Emerging Threats in Cybersecurity

Cybersecurity is a widely used term with highly diverse, frequently subjective, and occasionally uninformative definitions. Disrupting force processes in national security and the economy can be disastrous. The challenge of meeting safety a...

Public-Private Cybersecurity

Calls for public-private partnerships to address U.S. cybersecurity failures have become ubiquitous. But the academic literature and public debate have not fully appreciated the extent to which the United States has already backed into a de...

Cybersecurity

In this chapter, students will learn how cybersecurity has become a key issue in global security. Once the primary domain of military and intelligence activities, cyber attacks and intrusions have had a broad impact, from the attacks agains...

Anomaly Detection for Cybersecurity of the Substations

Cybersecurity of the substations in a power system is a major issue as the substations become increasingly dependent on computer and communication networks. This paper is concerned with anomaly detection in the computer network environment ...

Vulnerability Assessment of Cybersecurity for SCADA Systems

Vulnerability assessment is a requirement of NERC's cybersecurity standards for electric power systems. The purpose is to study the impact of a cyber attack on supervisory control and data acquisition (SCADA) systems. Compliance of the requ...

Hacking the Human: The Prevalence Paradox in Cybersecurity

OBJECTIVE: This work assesses the efficacy of the "prevalence effect" as a form of cyberattack in human-automation teaming, using an email task. BACKGROUND: Under the prevalence effect, rare signals are more difficult to detect, even when t...

Cybersecurity and cyberwar: what everyone needs to know

1. Why cyberspace is wonderfulEL and complicated What is cyberspace? Why do people talk about the difference of a networked world? How does the Internet actually work? Who owns this thing? WaitEL You mean no one runs the internet? What can ...

Cybersecurity for distributed energy resources and smart inverters

The increased penetration of distributed energy resources (DER) will significantly increase the number of devices that are owned and controlled by consumers and third‐parties. These devices have a significant dependency on digital communica...

A survey of graphs in natural language processing

Abstract Graphs are a powerful representation formalism that can be applied to a variety of aspects related to language processing. We provide an overview of how Natural Language Processing problems have been projected into the graph framew...

Impact of Machine Learning in Natural Language Processing: A Review

The recent times have seen unprecedented growth in research and development in the field of Artificial Intelligence and its allied fields, subfields, like Machine Learning, Deep Learning and Natural Language Processing. The new found excite...

Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1

We introduce a method to train Binarized Neural Networks (BNNs) - neural networks with binary weights and activations at run-time. At training-time the binary weights and activations are used for computing the parameters gradients. During t...

A Survey on Neural Network Interpretability

Along with the great success of deep neural networks, there is also growing concern about their black-box nature. The interpretability issue affects people's trust on deep learning systems. It is also related to many ethical problems, e.g.,...

Pattern Recognition with Neural Networks in C++

From the Publisher: The addition of artificial neural network computing to traditionalpattern recognition has given rise to a new, different, and more powerful methodology that is presented in this interesting book. This is a practical gui...

Memristor devices for neural networks

Abstract Neural network technologies have taken center stage owing to their powerful computing capability for supporting deep learning in artificial intelligence. However, conventional synaptic devices such as SRAM and DRAM are not satisfac...

Hyperbolic Neural Networks

Hyperbolic spaces have recently gained momentum in the context of machine learning due to their high capacity and tree-likeliness properties. However, the representational power of hyperbolic geometry is not yet on par with Euclidean geomet...

The power of quantum neural networks