A survey on machine learning techniques for cyber security in the last decade

K Shaukat, S Luo, V Varadharajan, IA Hameed… - IEEE …, 2020 - ieeexplore.ieee.org
Pervasive growth and usage of the Internet and mobile applications have expanded
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …

Cyber threat detection using machine learning techniques: A performance evaluation perspective

K Shaukat, S Luo, S Chen, D Liu - … international conference on …, 2020 - ieeexplore.ieee.org
The present-day world has become all dependent on cyberspace for every aspect of daily
living. The use of cyberspace is rising with each passing day. The world is spending more …

[PDF][PDF] Intrusion prevention system using convolutional neural network for wireless sensor network

PR Chandre, P Mahalle, G Shinde - IAES International Journal of Artificial …, 2022 - viit.ac.in
Now-a-days, there is exponential growth in the field of wireless sensor network. In wireless
sensor networks (WSN's), most of communication happen through wireless media hence …

Detection of cyber crime based on facial pattern enhancement using machine learning and image processing techniques

RD Jujjuri, AK Tripathi, VS Chandrika… - … intelligence for the …, 2022 - igi-global.com
Cybercrime has several antecedents, including the rapid expansion of the internet and the
wide variety of users around the world. It is now possible to use this data for a variety of …

[PDF][PDF] A user-centric approach to explainable AI in a security operation center environment.

HS Eriksson - 2022 - duo.uio.no
Living in the information age, countries, societies, and individuals become ever more
emerged in technology for each passing day. However, with every new software, hardware …

A distributed and privacy-preserving random forest evaluation scheme with fine grained access control

Y Zhou, H Shen, M Zhang - Symmetry, 2022 - mdpi.com
Random forest is a simple and effective model for ensemble learning with wide potential
applications. Implementation of random forest evaluations while preserving privacy for the …

Analysis of machine learning techniques for spam detection

S Raheja, S Kasturia - Applications of Machine Learning in Big …, 2022 - taylorfrancis.com
This paper discusses the spam detection and different machine learning models to detect
these spam messages. The present work also discusses the testing and evaluation of spam …

Prevention of intrusion attacks via deep learning algorithm in wireless sensor network in smart cities

D Choudhary, R Pahuja - Advances in Clean Energy Technologies: Select …, 2021 - Springer
Nowadays, there is exponential growth in the field of wireless sensor networks. In WSN's
security is a major concern, since most of communication happen through a wireless media; …

Combining Lexical, Host, and Content-based features for Phishing Websites detection using Machine Learning Models

S Hamadouche, O Boudraa… - … Endorsed Transactions on …, 2024 - publications.eai.eu
In cybersecurity field, identifying and dealing with threats from malicious websites (phishing,
spam, and drive-by downloads, for example) is a major concern for the community …