Academic Articles & Research Papers

Abstract Communication Model for Distributed Systems

In some distributed and mobile communication models, a message disappears in one place and miraculously appears in another. In reality, of course, there are no miracles. A message goes from one network to another; it can be lost or corrupte...

A Behavioral SIQR-B Model for Cholera Transmission: Impact of Adaptive Risk Perception on Disease Dynamics

Background/Objectives: Cholera remains a major public health problem, particularly in regions with limited access to safe drinking water and sanitation. Traditional compartmental models may underrepresent adaptive human behavioral responses...

Machine Learning and Deep Learning Methods for Cybersecurity

With the development of the Internet, cyber-attacks are changing rapidly and the cyber security situation is not optimistic. This survey report describes key literature surveys on machine learning (ML) and deep learning (DL) methods for net...

Blockchain in Cybersecurity

Blockchain is a promising technology that can help organizations improve their cybersecurity. Blockchain has many inherent features that can help enhance data security, improve threat detection and response, strengthen authentication and au...

Explainable machine learning in cybersecurity: A survey

Machine learning (ML) techniques are increasingly important in cybersecurity, as they can quickly analyse and identify different types of threats from millions of events. In spite of the increasing number of possible applications of ML, suc...

Cybersecurity, safety and robots: Strengthening the link between cybersecurity and safety in the context of care robots

This paper addresses the interplay between robots, cybersecurity, and safety from a European legal perspective, a topic under-explored by current technical and legal literature. The legal framework, together with technical standards, is a n...

Machine learning in cybersecurity: a comprehensive survey

Today’s world is highly network interconnected owing to the pervasiveness of small personal devices (e.g., smartphones) as well as large computing devices or services (e.g., cloud computing or online banking), and thereby each passing minut...

Cybersecurity

Cybersecurity is generally considered as an information security topic, often associated with personal data and information databases: collecting, exposing, corrupting, or deleting these data. However, it is a more global problem, and relat...

Explainable AI for Cybersecurity

In recent years, the utilization of AI in the field of cybersecurity has become more widespread. Black-box AI models pose a significant challenge in terms of interpretability and transparency, which is one of the major drawbacks of AI-based...

A Survey on Cybersecurity in IoT

The proliferation of the Internet of Things (IoT) has transformed the digital landscape, enabling a vast array of interconnected devices to communicate and share data seamlessly. However, the rapid expansion of IoT networks has also introdu...

Explainable artificial intelligence for cybersecurity: a literature survey

Abstract With the extensive application of deep learning (DL) algorithms in recent years, e.g., for detecting Android malware or vulnerable source code, artificial intelligence (AI) and machine learning (ML) are increasingly becoming essent...

A survey of uncertainty in deep neural networks

Abstract Over the last decade, neural networks have reached almost every field of science and become a crucial part of various real world applications. Due to the increasing spread, confidence in neural network predictions has become more a...

A neural network approach to ordinal regression

Ordinal regression is an important type of learning, which has properties of both classification and regression. Here we describe an effective approach to adapt a traditional neural network to learn ordinal categories. Our approach is a gen...

Nonlinear Flight Control Using Neural Networks

The theoretical developmentofa direct adaptivetracking controlarchitectureusingneuralnetworks ispresented. Emphasis is placed on utilization of neural networks in a  ight control architecture based on feedback linearization of the aircraft...

Approximation theory of the MLP model in neural networks

In this survey we discuss various approximation-theoretic problems that arise in the multilayer feedforward perceptron (MLP) model in neural networks. The MLP model is one of the more popular and practical of the many neural network models....

Proceedings of the 22nd international conference on Machine learning

This volume, which is also available online from http://www.machinelearning.org, contains the papers accepted for presentation at ICML-2005, the 22nd lnternational Conference on Machine Learning, which was held at the University of Bonn in ...

Software Engineering in the Small.

The article focuses on issues concerning software engineering The article focuses on issues concerning software engineering. Smaller-sized software companies are developing significant products that need effective, tailored software ...

A Scalable Real-Time SDN-Based MQTT Framework for Industrial Applications

The increasing prominence of concepts such as Smart Production and Industrial Internet of Things (IIoT) within the context of Industry 4.0 has introduced a new set of requirements for the engineering of industrial systems, including support...

IEEE Access Special Section Editorial: Toward Service-Centric Internet of Things (IoT): From Modeling to Practice

The Internet of Things (IoT) refers to an emerging paradigm to seamlessly and ubiquitously integrate a large number of smart things with intra/inter links to the physical and cyber worlds. Sensor-enabled communication technologies connect b...

Absence of Plasmodium falciparum Histidine-Rich Protein 2 and 3 (Pfhrp2/3) Gene Deletions in Rizal, Palawan, the Philippines.