Academic Articles & Research Papers

Detect anomalous quartic gauge couplings at muon colliders with quantum kernel k-means

Abstract In recent years, with the increasing luminosities of colliders, handling the growing amount of data has become a major challenge for future New Physics (NP) phenomenological research. In order to improve efficiency, machine learnin...

Execution Anomaly Detection in Distributed Systems through Unstructured Log Analysis

Detection of execution anomalies is very important for the maintenance, development, and performance refinement of large scale distributed systems. Execution anomalies include both work flow errors and low performance problems. People often...

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...

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 ...

An Explainable AI-Driven Zero-Day Attack Detection Framework for Securing Edge Devices in Smart Cities

The rapid proliferation of edge computing in smart cities has enhanced real-time data processing capabilities, but it has also exposed critical vulnerabilities to sophisticated cyber threats such as zero-day attacks. Traditional signature-b...

Decentralized intelligence in smart grids: a comprehensive survey of edge computing and federated learning

Modern power grids are becoming more distributed and data-intensive, while centralized, cloud-based analytics struggle to keep pace. Routing everything through a central system introduces delays, strains network capacity, complicates compli...

Robustness of Short-Term Wind Power Forecasting against False Data Injection Attacks

The accuracy of wind power forecasting depends a great deal on the data quality, which is so susceptible to cybersecurity attacks. In this paper, we study the cybersecurity issue of short-term wind power forecasting. We present one class of...

A study on process information-driven cyber threat detection for I&C systems in NPP

The increasing digitalization of Instrumentation and Control (I&C) systems in Nuclear Power Plants (NPPs) has improved operational efficiency while introducing cybersecurity vulnerabilities. Conventional network-based intrusion detection sy...

Hyperspectral Methane Plume Segmentation Through Foundation Computer Vision Models

Efficient large-scale monitoring of methane emissions is crucial for sustainable environmental management, necessitating advanced remote sensing techniques that process hyperspectral imagery to provide detailed insights into the Earth&#x201...

Spatially Aware Fusion in 3D Convolutional Autoencoders for Video Anomaly Detection

Surveillance videos are crucial for crime prevention and public safety, yet the challenge of defining abnormal events hinders their effectiveness, limiting the applicability of supervised methods. This paper introduces an unsupervised end-t...

Video Processing Using Deep Learning Techniques: A Systematic Literature Review

Studies show lots of advanced research on various data types such as image, speech, and text using deep learning techniques, but nowadays, research on video processing is also an emerging field of computer vision. Several surveys are presen...

Deep Learning for Time Series Anomaly Detection: A Survey

Time series anomaly detection is important for a wide range of research fields and applications, including financial markets, economics, earth sciences, manufacturing, and healthcare. The presence of anomalies can indicate novel or unexpect...

A Comprehensive Survey on Graph Anomaly Detection With Deep Learning

Anomalies are rare observations (e.g., data records or events) that deviate significantly from the others in the sample. Over the past few decades, research on anomaly mining has received increasing interests due to the implications of thes...

A survey of deep learning-based network anomaly detection

Membership inference attacks against transfer learning for generalized model

For the problem of poor performance of exciting membership inference attack (MIA) when facing the transfer learning model that is generalized, the MIA for the transfer learning model that is generalized was first systematically studied, the...

Deep Learning for Spatio-Temporal Data Mining: A Survey

With the fast development of various positioning techniques such as Global Position System (GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly available nowadays. Mining valuable knowledge from spatio-temp...

Deep Learning for the Earth Sciences

Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only re...

Deep Learning for Anomaly Detection: A Survey

Anomaly detection is an important problem that has been well-studied within diverse research areas and application domains. The aim of this survey is two-fold, firstly we present a structured and comprehensive overview of research methods i...

Deep Learning for Anomaly Detection

Anomaly detection, a.k.a. outlier detection or novelty detection, has been a lasting yet active research area in various research communities for several decades. There are still some unique problem complexities and challenges that require ...

Unsupervised Deep Anomaly Detection for Industrial Multivariate Time Series Data

With the rapid development of deep learning, researchers are actively exploring its applications in the field of industrial anomaly detection. Deep learning methods differ significantly from traditional mathematical modeling approaches, eli...