| Type of Material: | Thesis |
| Title: | AI Techniques Applied To Intrusion Detection System |
| Researcher: | Parameswar, D |
| Guide: | Khanaa, V |
| Department: | Department of Engineering and Technology(Computer Science and Engineering) |
| Publisher: | Bharath University, Chennai |
| Place: | Chennai |
| Year: | 2021 |
| Language: | English |
| Subject: | Computer Science | Computer Science Artificial Intelligence | Engineering and Technology | Computer Science and Information Technology | Engineering and Technology |
| Dissertation/Thesis Note: | PhD; Department of Engineering and Technology(Computer Science and Engineering), Bharath University, Chennai, Chennai; 2021; D15CS518 |
| Fulltext: | Shodhganga |
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| 001 | 454993 | |
| 003 | IN-AhILN | |
| 005 | 2024-09-20 15:10:21 | |
| 008 | __ | 240920t2021||||ii#||||g|m||||||||||eng|| |
| 035 | __ | |a(IN-AhILN)th_454993 |
| 040 | __ | |aBHAU_600073|dIN-AhILN |
| 041 | __ | |aeng |
| 100 | __ | |aParameswar, D|eResearcher |
| 110 | __ | |aDepartment of Engineering and Technology(Computer Science and Engineering)|bBharath University, Chennai|dChennai|ein|0U-0446 |
| 245 | __ | |aAI Techniques Applied To Intrusion Detection System |
| 260 | __ | |aChennai|bBharath University, Chennai|c2021 |
| 300 | __ | |dDVD |
| 502 | __ | |bPhD|cDepartment of Engineering and Technology(Computer Science and Engineering), Bharath University, Chennai, Chennai|d2021|oD15CS518 |
| 520 | __ | |aNetwork Intrusion Detection is an important tool to detect and analyze security threats to a communication network. It complements other network security techniques, such as firewalls, by providing information about the frequency and nature of attacks. A network intrusion detection system (NIDS) often consists of a sensor that analyzes every packet on the network under observation, and forwards the packets which are deemed interesting, together with an alert message to a backend system, that stores them for further analysis and correlation with other events. This research work has been designed and executed in three phases, namely, protocol structure standardization, generation of cross over and mutation values for device identification using the genetic approach and the modified J48 decision tree algorithm for search process. The performance of the developed algorithms/methods is compared with the existing methods, and found to be good. In the first phase, the 64 byte structured protocol standardization te |
| 650 | __ | |aComputer Science and Information Technology|2UGC |
| 650 | __ | |aEngineering and Technology|2AIU |
| 653 | __ | |aComputer Science |
| 653 | __ | |aComputer Science Artificial Intelligence |
| 653 | __ | |aEngineering and Technology |
| 700 | __ | |aKhanaa, V|eGuide |
| 856 | __ | |uhttp://shodhganga.inflibnet.ac.in/handle/10603/354889|yShodhganga |
| 905 | __ | |afromsg |
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