Electronic Resource
Random Forests for Online Intrusion Detection in Computer Networks
| العنوان: | Random Forests for Online Intrusion Detection in Computer Networks |
|---|---|
| المؤلفون: | Heitor Scalco Neto, Wilian Soares Lacerda, Rafael Verão Françozo |
| بيانات النشر: | Science Publications 2021-10-19 |
| نوع الوثيقة: | Electronic Resource |
| مستخلص: | This study proposes a methodology to build an Online Network Intrusion Detection System by using the Computational Intelligence technique called Random Forests and an API to preprocess the network packets. The experiments were carried out from two network traffic databases: The ISCX (i); and a test database (ii) created with the proposed API in our own network environment. The results obtained with the Random Forests technique show accuracy rates around 98%, bringing significant advances in the area of Intrusion Detection and affirming the high efficiency of the use of the technique to solve problems of intrusion detection in real network environments. |
| مصطلحات الفهرس: | Research Article |
| الاتاحة: | Open access content. Open access content |
| ملاحظة: | English |
| Other Numbers: | AESCI oai:thescipub.com:jcssp.2021.905.914 1280398522 |
| المصدر المساهم: | SCIENCE PUBNS From OAIster®, provided by the OCLC Cooperative. |
| رقم الانضمام: | edsoai.on1280398522 |
| قاعدة البيانات: | OAIster |
| الوصف غير متاح. |