Network Intrusion Detection System
Abstract & Details
Research Area
Information Technology
Keywords
Intrusion detection system
packet filtering
packet capture
malicious
Abstract
Intrusion detection has become a critical component of network administration due to the vast number of attacks persistently threaten our computers. Traditional intrusion detection systems are limited and do not provide a complete solution for the problem. Here we are concentrating and analyzing overall performance as well as security of the proposed IDS. Moreover the proposed IDS approve the effectiveness of the proposed method, and presented results shows advantages of network based security. The proposed model of IDSs offers several advantages over alternative systems. First of all it provided higher security, it supported high availability and scalability, and most important thing it produced good results in terms of normal and abnormal behaviors of captured packet. The proposed model includes integration of individual components to produced batter results.
Packet sniffing or packet capture software is extensively used as tools for protocol analysis and security. In protocol design research, such a tool comes handy in analyzing, debugging and testing of a new protocol implementation. In Security, as is true for any tools, it may be used both as a positive way to detect intrusions or attacks on a system as well as in the malicious way to hack for private and personal data of others. Even though use of upper layer encryption techniques make it difficult to gather data directly, yet these tools are important in learning about existing sessions, collecting encrypted data to launch offline attacks to generate the encryption key and any such attack limited only by ones imagination. Packet sniffing is integrated with our project as a key tool to extract the headers of packets to differentiate them from rest of the malicious content.
License
This work is licensed under a Creative
Commons
Attribution-ShareAlike 4.0 International License.
Author Information
| # | Name | Institute / Affiliation |
|---|---|---|
| 1 | Kunal Iyengar | Rajiv Gandhi Institute of Technology |
| 2 | Grishma Wadhia | Rajiv Gandhi Institute of Technology |
| 3 | Parth Vasani | Rajiv Gandhi Institute of Technology |
| 4 | Jyoti Mishra | Rajiv Gandhi Institute of Technology |
| 5 | Dr Sunil B Wankhede | Rajiv Gandhi Institute of Technology |
How to Cite
Use the following formats to cite this article in your research.
APA Style
Iyengar, Kunal, Wadhia, Grishma, Vasani, Parth, Mishra, Jyoti, & Wankhede, Dr Sunil B (2017). Network Intrusion Detection System. International Journal of Advance Research and Innovative Ideas In Education, 3(2), 4478-4484.
MLA Style
Iyengar, Kunal, et al. "Network Intrusion Detection System." International Journal of Advance Research and Innovative Ideas In Education, vol. 3, no. 2, 2017, pp. 4478-4484.
IEEE Style
Kunal Iyengar, Grishma Wadhia, Parth Vasani, Jyoti Mishra, and Dr Sunil B Wankhede, "Network Intrusion Detection System," International Journal of Advance Research and Innovative Ideas In Education, vol. 3, no. 2, pp. 4478-4484, 2017.
Vancouver Style
Iyengar Kunal, Wadhia Grishma, Vasani Parth, Mishra Jyoti, Wankhede Dr Sunil B. Network Intrusion Detection System. International Journal of Advance Research and Innovative Ideas In Education. 2017;3(2):4478-4484.
Harvard Style
Iyengar, Kunal, Wadhia, Grishma, Vasani, Parth, Mishra, Jyoti, & Wankhede, Dr Sunil B (2017) 'Network Intrusion Detection System', International Journal of Advance Research and Innovative Ideas In Education, 3(2), pp. 4478-4484.
Chicago Style
Iyengar, Kunal, et al. "Network Intrusion Detection System." International Journal of Advance Research and Innovative Ideas In Education 3, no. 2 (2017): 4478-4484.
Turabian Style
Iyengar, Kunal, et al. "Network Intrusion Detection System." International Journal of Advance Research and Innovative Ideas In Education 3, no. 2 (2017): 4478-4484.
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