Reducing False Notification in Identifying Malicious Application Programming Interface(API) to Detect Malwares Using Artificial Neural Network with Discriminant Analysis
This paper argues the accuracy of behavior based detection systems, in which the Application Programming Interfaces (API) calls are analyzed and monitored. The work identifies the problems that affecting the accuracy of such detection models. The work was extracted (4744) API call through analyzin...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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University of Baghdad
2017-04-01
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| Series: | Ibn Al-Haitham Journal for Pure and Applied Sciences |
| Subjects: | |
| Online Access: | https://jih.uobaghdad.edu.iq/index.php/j/article/view/320 |
| _version_ | 1811309373632282624 |
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| author | Abbas M. Al-Bakri Hussein L. Hussein |
| author_facet | Abbas M. Al-Bakri Hussein L. Hussein |
| author_sort | Abbas M. Al-Bakri |
| collection | DOAJ |
| description |
This paper argues the accuracy of behavior based detection systems, in which the Application Programming Interfaces (API) calls are analyzed and monitored. The work identifies the problems that affecting the accuracy of such detection models. The work was extracted (4744) API call through analyzing. The new approach provides an accurate discriminator and can reveal malicious API in PE malware up to 83.2%. Results of this work evaluated with Discriminant Analysis
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| first_indexed | 2024-04-13T09:41:03Z |
| format | Article |
| id | doaj.art-8da59c29d7f742ebbf23b4202bf673f4 |
| institution | Directory Open Access Journal |
| issn | 1609-4042 2521-3407 |
| language | English |
| last_indexed | 2024-04-13T09:41:03Z |
| publishDate | 2017-04-01 |
| publisher | University of Baghdad |
| record_format | Article |
| series | Ibn Al-Haitham Journal for Pure and Applied Sciences |
| spelling | doaj.art-8da59c29d7f742ebbf23b4202bf673f42022-12-22T02:51:55ZengUniversity of BaghdadIbn Al-Haitham Journal for Pure and Applied Sciences1609-40422521-34072017-04-01273Reducing False Notification in Identifying Malicious Application Programming Interface(API) to Detect Malwares Using Artificial Neural Network with Discriminant AnalysisAbbas M. Al-BakriHussein L. Hussein This paper argues the accuracy of behavior based detection systems, in which the Application Programming Interfaces (API) calls are analyzed and monitored. The work identifies the problems that affecting the accuracy of such detection models. The work was extracted (4744) API call through analyzing. The new approach provides an accurate discriminator and can reveal malicious API in PE malware up to 83.2%. Results of this work evaluated with Discriminant Analysis https://jih.uobaghdad.edu.iq/index.php/j/article/view/320PE Malwares, Malicious API, ANN, Discriminant Analysis |
| spellingShingle | Abbas M. Al-Bakri Hussein L. Hussein Reducing False Notification in Identifying Malicious Application Programming Interface(API) to Detect Malwares Using Artificial Neural Network with Discriminant Analysis Ibn Al-Haitham Journal for Pure and Applied Sciences PE Malwares, Malicious API, ANN, Discriminant Analysis |
| title | Reducing False Notification in Identifying Malicious Application Programming Interface(API) to Detect Malwares Using Artificial Neural Network with Discriminant Analysis |
| title_full | Reducing False Notification in Identifying Malicious Application Programming Interface(API) to Detect Malwares Using Artificial Neural Network with Discriminant Analysis |
| title_fullStr | Reducing False Notification in Identifying Malicious Application Programming Interface(API) to Detect Malwares Using Artificial Neural Network with Discriminant Analysis |
| title_full_unstemmed | Reducing False Notification in Identifying Malicious Application Programming Interface(API) to Detect Malwares Using Artificial Neural Network with Discriminant Analysis |
| title_short | Reducing False Notification in Identifying Malicious Application Programming Interface(API) to Detect Malwares Using Artificial Neural Network with Discriminant Analysis |
| title_sort | reducing false notification in identifying malicious application programming interface api to detect malwares using artificial neural network with discriminant analysis |
| topic | PE Malwares, Malicious API, ANN, Discriminant Analysis |
| url | https://jih.uobaghdad.edu.iq/index.php/j/article/view/320 |
| work_keys_str_mv | AT abbasmalbakri reducingfalsenotificationinidentifyingmaliciousapplicationprogramminginterfaceapitodetectmalwaresusingartificialneuralnetworkwithdiscriminantanalysis AT husseinlhussein reducingfalsenotificationinidentifyingmaliciousapplicationprogramminginterfaceapitodetectmalwaresusingartificialneuralnetworkwithdiscriminantanalysis |