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A review of the application of machine learning in water quality evaluation

Mengyuan Zhu, Jiawei Wang, Xiao Yang, Yu Zhang et al. • Eco-Environment & Health (2022)

With the rapid increase in the volume of data on the aquatic environment, machine learning has become an important tool for data analysis, classification, and prediction. Unlike traditional models used in water-related research, data-driven...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.eehl.2022.06.001 PMC: 10702893

Can machine learning be secure?

Marco Barreno, Blaine A. Nelson, Russell Sears, Anthony D. Joseph et al. • ACM Asia Conference on Computer and Communications Security (ASIA CCS) (2006)

Machine learning systems offer unparalled flexibility in dealing with evolving input in a variety of applications, such as intrusion detection systems and spam e-mail filtering. However, machine learning algorithms themselves can be a targe...

OPENALEX DOI: https://doi.org/10.1145/1128817.1128824

Exploring Traffic Patterns Through Network Programmability: Introducing SDNFLow, a Comprehensive OpenFlow-Based Statistics Dataset for Attack Detection

Jorge Buzzio-Garcia, Jaime Vergara, Santiago Rios-Guiral, Christian Garzon et al. • IEEE Access (2024)

In the contemporary cybersecurity landscape, robust attack detection mechanisms are important for organizations. However, the current state of research in Software-Defined Networking (SDN) suffers from a notable lack of recent SDN-OpenFlow-...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3378271

Cybersecurity in Smart Grids: Detecting False Data Injection Attacks Utilizing Supervised Machine Learning Techniques

Anwer Shees, Mohd Tariq, Arif I. Sarwat • Energies (2024)

By integrating advanced technologies and data-driven systems in smart grids, there has been a significant revolution in the energy distribution sector, bringing a new era of efficiency and sustainability. Nevertheless, with this advancement...

DOAJ Open Access (DOAJ) DOI: 10.3390/en17235870

Leveraging Cloud Technology for Personalized Multiple Sclerosis Care: A Comprehensive Data Management and Visualization Approach

Jose Manuel PINILLOS RUBIO, Minerva VIGUERA MORENO • Applied Medical Informatics (2024)

This project develops a cloud-based solution for securely managing clinical data and patient-reported outcomes (PROMs) for multiple sclerosis (MS) patients. Utilizing REDCap for data collection, we incorporated clinical outcomes and PROMs f...

DOAJ Open Access (DOAJ)

The security of machine learning

Marco Barreno, Blaine A. Nelson, Anthony D. Joseph, J. D. Tygar • Machine Learning (2010)

Machine learning’s ability to rapidly evolve to changing and complex situations has helped it become a fundamental tool for computer security. That adaptability is also a vulnerability: attackers can exploit machine learning systems. We pre...

OPENALEX cc-by-nc DOI: https://doi.org/10.1007/s10994-010-5188-5

Adversarial machine learning

Ling Huang, Anthony D. Joseph, Blaine A. Nelson, Benjamin I. P. Rubinstein et al. • ACM Workshop on Artificial Intelligence and Security (AISec) (2011)

In this paper (expanded from an invited talk at AISEC 2010), we discuss an emerging field of study: adversarial machine learning---the study of effective machine learning techniques against an adversarial opponent. In this paper, we: give a...

OPENALEX DOI: https://doi.org/10.1145/2046684.2046692

Perbandingan Algoritma Decision Tree dan K-Nearest Neighbor untuk Klasifikasi Serangan Jaringan IoT

Zishwa Muhammad Jauhar Nafis, Rahmatun Nazilla, Rega Nugraha, Shofwatul ’Uyun Shofwatul ’Uyun • Komputika (2024)

Seiring dengan perkembangan jumlah penggunaan Internet of Things yang terus meningkat dan meluas. Ancaman keamanan pada jaringan IoT juga meningkat. Terdapat beberapa teknik yang diterapkan untuk mengatasi ancaman keamanan ini. Salah satuny...

DOAJ Open Access (DOAJ) DOI: 10.34010/komputika.v13i2.12609

Machine Learning

Ethem Alpaydın • The MIT Press eBooks (2021)

A concise overview of machine learning—computer programs that learn from data—the basis of such applications as voice recognition and driverless cars. Today, machine learning underlies a range of applications we use every day, from product ...

OPENALEX Open Access DOI: https://doi.org/10.7551/mitpress/13811.001.0001

Evaluating designers’ acceptance of AI generated content using TAM and TRI frameworks

Shao-Feng Wang, Ke-Yi Liu, Yang Liu, Fei-Yang Zhao et al. • Scientific Reports (2026)

Abstract Artificial intelligence technology, based on big data algorithms, can replace much of the repetitive and rule-based work. However, whether AI can substitute the roles of artists or designers in the art and design industry, which pr...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-51244-0

Hyperspectral imaging for the detection of plant pathogens in seeds: recent developments and challenges

Luciellen da Costa Ferreira, Ian Carlos Bispo Carvalho, Lúcio André de Castro Jorge, Alice Maria Quezado-Duval et al. • Frontiers in Plant Science (2024)

Food security, a critical concern amid global population growth, faces challenges in sustainable agricultural production due to significant yield losses caused by plant diseases, with a multitude of them caused by seedborne plant pathogen. ...

DOAJ Open Access (DOAJ) DOI: 10.3389/fpls.2024.1387925

MONITORING SYSTEM FOR CRITICAL INFRASTRUCTURE OBJECTS BASED ON DIGITAL TWINS

Дмитро АНРДЄЄВ, Олексій ЛИГУН, Андрій ДРОЗД, Олена ПОНОЧОВНА • Компютерні системи та інформаційні технології (2025)

Critical infrastructures are fundamental to the seamless operation of modern societies, encompassing sectors such as energy, healthcare, transportation, and communications. Ensuring their reliability, performance, continuous operation, safe...

DOAJ Open Access (DOAJ) DOI: 10.31891/csit-2025-2-3