Detection of phishing attacks with machine learning techniques in cognitive security architecture

Ivan Ortiz Garces; Maria Fernada Cazares; Roberto Omar Andrade

doi:10.1109/CSCI49370.2019.00071

Detection of phishing attacks with machine learning techniques in cognitive security architecture

Ivan Ortiz Garces, Maria Fernada Cazares, Roberto Omar Andrade

Spatial Data Infrastructure Research Group Artificial Intelligence Geoportals and Applied Computing (IDE IA GEO CA)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

17 Scopus citations

Abstract

The number of phishing attacks has increased in Latin America, exceeding the operational skills of cybersecurity analysts. The cognitive security application proposes the use of bigdata, machine learning, and data analytics to improve response times in attack detection. This paper presents an investigation about the analysis of anomalous behavior related with phishing web attacks and how machine learning techniques can be an option to face the problem. This analysis is made with the use of an contaminated data sets, and python tools for developing machine learning for detect phishing attacks through of the analysis of URLs to determinate if are good or bad URLs in base of specific characteristics of the URLs, with the goal of provide realtime information for take proactive decisions that minimize the impact of an attack.

Original language	English
Title of host publication	Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	366-370
Number of pages	5
ISBN (Electronic)	9781728155845
DOIs	https://doi.org/10.1109/CSCI49370.2019.00071
State	Published - Dec 2019
Event	6th Annual International Conference on Computational Science and Computational Intelligence, CSCI 2019 - Las Vegas, United States Duration: 5 Dec 2019 → 7 Dec 2019

Publication series

Name	Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019

Conference

Conference	6th Annual International Conference on Computational Science and Computational Intelligence, CSCI 2019
Country/Territory	United States
City	Las Vegas
Period	5/12/19 → 7/12/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

Artificial intelligence
Artificial neural networks
Cybersecurity
Machine learning
Phishing

Access to Document

10.1109/CSCI49370.2019.00071

Cite this

Ortiz Garces, I., Cazares, M. F., & Andrade, R. O. (2019). Detection of phishing attacks with machine learning techniques in cognitive security architecture. In Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019 (pp. 366-370). Article 9070902 (Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CSCI49370.2019.00071

Ortiz Garces, Ivan ; Cazares, Maria Fernada ; Andrade, Roberto Omar. / Detection of phishing attacks with machine learning techniques in cognitive security architecture. Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 366-370 (Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019).

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title = "Detection of phishing attacks with machine learning techniques in cognitive security architecture",

abstract = "The number of phishing attacks has increased in Latin America, exceeding the operational skills of cybersecurity analysts. The cognitive security application proposes the use of bigdata, machine learning, and data analytics to improve response times in attack detection. This paper presents an investigation about the analysis of anomalous behavior related with phishing web attacks and how machine learning techniques can be an option to face the problem. This analysis is made with the use of an contaminated data sets, and python tools for developing machine learning for detect phishing attacks through of the analysis of URLs to determinate if are good or bad URLs in base of specific characteristics of the URLs, with the goal of provide realtime information for take proactive decisions that minimize the impact of an attack.",

keywords = "Artificial intelligence, Artificial neural networks, Cybersecurity, Machine learning, Phishing",

author = "{Ortiz Garces}, Ivan and Cazares, {Maria Fernada} and Andrade, {Roberto Omar}",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 6th Annual International Conference on Computational Science and Computational Intelligence, CSCI 2019 ; Conference date: 05-12-2019 Through 07-12-2019",

year = "2019",

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doi = "10.1109/CSCI49370.2019.00071",

language = "English",

series = "Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019",

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Ortiz Garces, I, Cazares, MF & Andrade, RO 2019, Detection of phishing attacks with machine learning techniques in cognitive security architecture. in Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019., 9070902, Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019, Institute of Electrical and Electronics Engineers Inc., pp. 366-370, 6th Annual International Conference on Computational Science and Computational Intelligence, CSCI 2019, Las Vegas, United States, 5/12/19. https://doi.org/10.1109/CSCI49370.2019.00071

Detection of phishing attacks with machine learning techniques in cognitive security architecture. / Ortiz Garces, Ivan; Cazares, Maria Fernada; Andrade, Roberto Omar.
Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 366-370 9070902 (Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Ortiz Garces, Ivan

AU - Cazares, Maria Fernada

AU - Andrade, Roberto Omar

PY - 2019/12

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AB - The number of phishing attacks has increased in Latin America, exceeding the operational skills of cybersecurity analysts. The cognitive security application proposes the use of bigdata, machine learning, and data analytics to improve response times in attack detection. This paper presents an investigation about the analysis of anomalous behavior related with phishing web attacks and how machine learning techniques can be an option to face the problem. This analysis is made with the use of an contaminated data sets, and python tools for developing machine learning for detect phishing attacks through of the analysis of URLs to determinate if are good or bad URLs in base of specific characteristics of the URLs, with the goal of provide realtime information for take proactive decisions that minimize the impact of an attack.

KW - Artificial intelligence

KW - Artificial neural networks

KW - Cybersecurity

KW - Machine learning

KW - Phishing

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BT - Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019

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Ortiz Garces I, Cazares MF, Andrade RO. Detection of phishing attacks with machine learning techniques in cognitive security architecture. In Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 366-370. 9070902. (Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019). doi: 10.1109/CSCI49370.2019.00071

Detection of phishing attacks with machine learning techniques in cognitive security architecture

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