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.
|Title of host publication||Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||5|
|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
|Name||Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019|
|Conference||6th Annual International Conference on Computational Science and Computational Intelligence, CSCI 2019|
|Period||5/12/19 → 7/12/19|
Bibliographical notePublisher Copyright:
© 2019 IEEE.
- Artificial intelligence
- Artificial neural networks
- Machine learning