Amanote Research

Amanote Research

    RegisterSign In

Learning to Detect Malicious URLs

ACM Transactions on Intelligent Systems and Technology - United States
doi 10.1145/1961189.1961202
Full Text
Open PDF
Abstract

Available in full text

Categories
Artificial IntelligenceTheoretical Computer Science
Date

April 1, 2011

Authors
Justin MaLawrence K. SaulStefan SavageGeoffrey M. Voelker
Publisher

Association for Computing Machinery (ACM)


Related search

A SVM-based Technique to Detect Phishing URLs

Information Technology Journal
2012English

Malicious Website Detection Based on URLs Static Features

DEStech Transactions on Computer Science and Engineering
2018English

Detecting Malicious URLs Using Binary Classification Through Adaboost Algorithm

International Journal of Electrical and Computer Engineering
Electronic EngineeringElectricalComputer Science
2020English

Threshold Based Mechanism to Detect Malicious URL’s in Social Networks

IOSR Journal of Computer Engineering
2016English

A Survey on Techniques to Detect Malicious Activites on Web

International Journal of Advanced Computer Science and Applications
Computer Science
2019English

Learning to Detect Motion Boundaries

2015English

Learning to Detect Partially Labeled People

English

Malicious URL Detection Based on Machine Learning

International Journal of Advanced Computer Science and Applications
Computer Science
2020English

Learning to Detect Aircraft at Low Resolutions

English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2025 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy