Distributed Denial of Service Attack Detection by Expert Systems
The Denial of Service (DoS) attacks are the attacks that overload the system resources such as CPU, network bandwidth, memory and so on to prevent system to provide services any legitimate users. The Distributed Denial of Service (DDoS) attacks are DoS attacks that organized with several systems wid...
| Main Authors: | , |
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| Format: | Article |
| Language: | fas |
| Published: |
Allameh Tabataba'i University Press
2016-11-01
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| Series: | مطالعات مدیریت کسب و کار هوشمند |
| Subjects: | |
| Online Access: | https://ims.atu.ac.ir/article_6991_2e762cdcd30005e7e3667313dee6dd6a.pdf |
| _version_ | 1797386069965012992 |
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| author | Alireza Sadabadi Bita Amirshahi |
| author_facet | Alireza Sadabadi Bita Amirshahi |
| author_sort | Alireza Sadabadi |
| collection | DOAJ |
| description | The Denial of Service (DoS) attacks are the attacks that overload the system resources such as CPU, network bandwidth, memory and so on to prevent system to provide services any legitimate users. The Distributed Denial of Service (DDoS) attacks are DoS attacks that organized with several systems widely (BotNet) to shut down the servers. Many companies have developed many DDoS detector systems but as the attack patterns are getting more complex day by day, the prediction of DDoS attacks by a specific method with a reasonable cost still is a hard task. In this paper, we tried to detect DDoS attacks by expert systems that use the attack symptoms and histories. We used expert system because DDoS attacks algorithms and patterns are complicated increasingly and as a result, we need to learn the attack detector systems. Finally, we implemented our system with visual studio .net and compared the results with simulation software such as "Netica". |
| first_indexed | 2024-03-08T22:04:39Z |
| format | Article |
| id | doaj.art-d2f2a080164b4021b67808bb58335d37 |
| institution | Directory Open Access Journal |
| issn | 2821-0964 2821-0816 |
| language | fas |
| last_indexed | 2024-03-08T22:04:39Z |
| publishDate | 2016-11-01 |
| publisher | Allameh Tabataba'i University Press |
| record_format | Article |
| series | مطالعات مدیریت کسب و کار هوشمند |
| spelling | doaj.art-d2f2a080164b4021b67808bb58335d372023-12-19T10:32:46ZfasAllameh Tabataba'i University Pressمطالعات مدیریت کسب و کار هوشمند2821-09642821-08162016-11-01517639210.22054/ims.2016.69916991Distributed Denial of Service Attack Detection by Expert SystemsAlireza Sadabadi0Bita Amirshahi1MA, Payame Noor University, Rey Branch, Tehran, IranAssistant Professor, Department of Computer Engineering and Information Technology, Payam Noor University, Tehran, IranThe Denial of Service (DoS) attacks are the attacks that overload the system resources such as CPU, network bandwidth, memory and so on to prevent system to provide services any legitimate users. The Distributed Denial of Service (DDoS) attacks are DoS attacks that organized with several systems widely (BotNet) to shut down the servers. Many companies have developed many DDoS detector systems but as the attack patterns are getting more complex day by day, the prediction of DDoS attacks by a specific method with a reasonable cost still is a hard task. In this paper, we tried to detect DDoS attacks by expert systems that use the attack symptoms and histories. We used expert system because DDoS attacks algorithms and patterns are complicated increasingly and as a result, we need to learn the attack detector systems. Finally, we implemented our system with visual studio .net and compared the results with simulation software such as "Netica".https://ims.atu.ac.ir/article_6991_2e762cdcd30005e7e3667313dee6dd6a.pdfdistributed denial of service attacksbotnetexpert systemflow entropybayesian networksfuzzy scale |
| spellingShingle | Alireza Sadabadi Bita Amirshahi Distributed Denial of Service Attack Detection by Expert Systems مطالعات مدیریت کسب و کار هوشمند distributed denial of service attacks botnet expert system flow entropy bayesian networks fuzzy scale |
| title | Distributed Denial of Service Attack Detection by Expert Systems |
| title_full | Distributed Denial of Service Attack Detection by Expert Systems |
| title_fullStr | Distributed Denial of Service Attack Detection by Expert Systems |
| title_full_unstemmed | Distributed Denial of Service Attack Detection by Expert Systems |
| title_short | Distributed Denial of Service Attack Detection by Expert Systems |
| title_sort | distributed denial of service attack detection by expert systems |
| topic | distributed denial of service attacks botnet expert system flow entropy bayesian networks fuzzy scale |
| url | https://ims.atu.ac.ir/article_6991_2e762cdcd30005e7e3667313dee6dd6a.pdf |
| work_keys_str_mv | AT alirezasadabadi distributeddenialofserviceattackdetectionbyexpertsystems AT bitaamirshahi distributeddenialofserviceattackdetectionbyexpertsystems |