Results 71 to 80 of about 200,258 (113)

A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection

IEEE Communications Surveys and Tutorials, 2016
A. Buczak, Erhan Guven
semanticscholar   +1 more source

Deep learning approach for Network Intrusion Detection in Software Defined Networking

International Conference on Wireless Networks and Mobile Communications, 2016
Tuan A. Tang, L. Mhamdi, D. McLernon, Syed Ali Raza Zaidi, M. Ghogho   +4 more
semanticscholar   +1 more source

Building an Intrusion Detection System Using a Filter-Based Feature Selection Algorithm

IEEE transactions on computers, 2016
Mohammed A. Ambusaidi, Xiangjian He, P. Nanda, Zhiyuan Tan   +3 more
semanticscholar   +1 more source

Impact of Event Scale-revised.

Journal of Physiotherapy, 2010
H. Motlagh
semanticscholar   +1 more source

Investigación y programa de medidas del ozono troposférico en el Observatorio de Vigilancia Atmosférica de Izaña (INM) [PDF]

, 1997
Cuevas Agulló, Emilio, Redondas, Alberto, Sancho Ávila, Juan Manuel   +2 more
core  

Seawater intrusion processes, investigation and management: Recent advances and future challenges

, 2013
A. Werner, M. Bakker, V. Post, A. Vandenbohede, Chunhui Lu, B. Ataie‐Ashtiani, C. Simmons, D. Barry   +7 more
semanticscholar   +1 more source

Explainable Intrusion Detection for Cyber Defences in the Internet of Things: Opportunities and Solutions

IEEE Communications Surveys and Tutorials, 2023
The field of Explainable Artificial Intelligence (XAI) has garnered considerable research attention in recent years, aiming to provide interpretability and confidence to the inner workings of state-of-the-art deep learning models.
Nour Moustafa, Nickolaos Koroniotis, Marwa Keshk, Albert Y. Zomaya, Z. Tari   +4 more
semanticscholar   +1 more source

In-vehicle network intrusion detection using deep convolutional neural network

Vehicular Communications, 2020
The implementation of electronics in modern vehicles has resulted in an increase in attacks targeting in-vehicle networks; thus, attack detection models have caught the attention of the automotive industry and its researchers. Vehicle network security is
Hyun Min Song, Jiyoung Woo, H. Kim
semanticscholar   +1 more source

Machine Learning Based Intrusion Detection System

2023 3rd International Conference on Technological Advancements in Computational Sciences (ICTACS), 2023
In today's digital landscape, the increasing frequency and sophistication of cyberattacks have highlighted the necessity for robust intrusion detection systems (IDS) to safe- guard sensitive data and critical infrastructure.
R. Udayakumar, D. Balakrishnan, Y. V. Reddy, P. Prabhakar, A. Thilaka   +4 more
semanticscholar   +1 more source

Deep learning approaches for anomaly-based intrusion detection systems: A survey, taxonomy, and open issues

Knowledge-Based Systems, 2020
The massive growth of data that are transmitted through a variety of devices and communication protocols have raised serious security concerns, which have increased the importance of developing advanced intrusion detection systems (IDSs).
Arwa Aldweesh, A. Derhab, Ahmed Z. Emam
semanticscholar   +1 more source