Modeling Browsing Behavior Analysis for Malicious Robot Detection in Distributed Denial of Service Attacks

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

FATHIAN M.; ABDOLLAHI AZGOMI M.; DEHGHANI H.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: JOURNAL OF ELECTRONIC AND CYBER DEFENCE Year:2016 | Volume:4 | Issue:2 (14) Page(s): 1-13

Download Full-Text

Persian Verion

View:

563

Download:

Cites:

Information Journal Paper

Title

Modeling Browsing Behavior Analysis for Malicious Robot Detection in Distributed Denial of Service Attacks

Author(s)

FATHIAN M. | ABDOLLAHI AZGOMI M. | DEHGHANI H. | Issue Writer Certificate

Keywords

DDoS AttackQ1

E-Commerce SecurityQ1

Malicious Web Robot DetectionQ1

Data MiningQ1

Abstract

Distributed denial of service (DDoS) attacks are one of the most important threats for E-commerce. Their main goal is to prevent the users from accessing to web sites and internet resources through excessive use of the resources. In these attacks, availability which is one of the elements of security is targeted. One of the ways to achieve this goal is to apply web robots by which the attackers design and carry out the DDoS Attacks at application layer. Various methods have been used to distinguish between malicious and non-malicious web robots. One of the most popular methods in the recent years is Data Mining and machine learning. This method is based on extracting and selecting those features which are fit for web sessions via web server access log files and applying Data Mining algorithms. Considering the fact that the DDoS Attacks are dynamic and customizable, in this research, an attempt is made to present a customizable dynamic defensive mechanism for detecting malicious web robots through the analysis of behaviors of their browsing. At the present study, features extraction was carried out based on the characteristics of DDoS Attacks together with optimization of the previous methods to determine web sessions. Furthermore refining the extracted features and selecting a set of efficient features reduced the time required for building a model. As a consequence, the efficiency enhanced by two percent compared to the best similar study.

Cites

No record.

References

No record.

Cite

APA: Copy

FATHIAN, M., ABDOLLAHI AZGOMI, M., & DEHGHANI, H.. (2016). Modeling Browsing Behavior Analysis for Malicious Robot Detection in Distributed Denial of Service Attacks. JOURNAL OF ELECTRONIC AND CYBER DEFENCE, 4(2 (14) ), 1-13. SID. https://sid.ir/paper/243192/en

Vancouver: Copy

FATHIAN M., ABDOLLAHI AZGOMI M., DEHGHANI H.. Modeling Browsing Behavior Analysis for Malicious Robot Detection in Distributed Denial of Service Attacks. JOURNAL OF ELECTRONIC AND CYBER DEFENCE[Internet]. 2016;4(2 (14) ):1-13. Available from: https://sid.ir/paper/243192/en

IEEE: Copy

M. FATHIAN, M. ABDOLLAHI AZGOMI, and H. DEHGHANI, “Modeling Browsing Behavior Analysis for Malicious Robot Detection in Distributed Denial of Service Attacks,” JOURNAL OF ELECTRONIC AND CYBER DEFENCE, vol. 4, no. 2 (14) , pp. 1–13, 2016, [Online]. Available: https://sid.ir/paper/243192/en

Related Journal Papers