research-article

Research of Recognition System of Web Intrusion Detection Based on Storm

Authors:

Li Bo,

Wang Jinzhen,

Zhao Ping,

Yan Zhongjiang, and

Yang MaoAuthors Info & Claims

ICNCC '16: Proceedings of the Fifth International Conference on Network, Communication and Computing

December 2016

Pages 98 - 102

https://doi.org/10.1145/3033288.3033319

Published: 17 December 2016 Publication History

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Abstract

Based on Storm, a distributed, reliable, fault-tolerant real-time data stream processing system, we propose a recognition system of web intrusion detection. The system is based on machine learning, feature selection algorithm by TF-IDF(Term Frequency--Inverse Document Frequency) and the optimised cosine similarity algorithm, at low false positive rate and a higher detection rate of attacks and malicious behavior in real-time to protect the security of user data. From comparative analysis of experiments we find that the system for intrusion recognition rate and false positive rate has improved to some extent, it can be better to complete the intrusion detection work.

References

[1]

Kruegel C, Vigna G, Robertson W. A multi-model approach to the detection of web-based attacks{J}. Computer Networks the International Journal of Computer & Telecommunications Networking, 2005, 48(5):717--738.

Digital Library

Google Scholar

[2]

Cho S, Cha S. SAD: web session anomaly detection based on parameter estimation{J}. Computers & Security, 2004, 23(4):312--319.

Digital Library

Google Scholar

[3]

Shu W, Tan T H, Null D. A Novel Intrusion Detection System Model for Securing Web-based Database Systems{C}// 2013 IEEE 37th Annual Computer Software and Applications Conference. IEEE Computer Society, 2001:249--254.

Google Scholar

[4]

Gordon V S. SQLiDetect: a web based intrusion detection system for SQL injections{J}. 2012.

Google Scholar

[5]

Xu D D, Wu S B. An Improved TFIDF Algorithm in Text Classification{J}. Applied Mechanics & Materials, 2014, 651--653:2258--2261.

Google Scholar

[6]

Pirlo G, Impedovo D. Cosine similarity for analysis and verification of static signatures{J}. Iet Biometrics, 2013, 2(4):151--158.

Crossref

Google Scholar

[7]

Iqbal M H, Soomro T R. Big Data Analysis: Apache Storm Perspective{J}. International Journal of Computer Trends & Technology, 2015, 19(1):9--14.

Crossref

Google Scholar

[8]

Lin Z C, Wu D W, Hong G E. Combination of improved cosine similarity and patent attribution probability method to judge the attribution of related patents of hydrolysis substrate fabrication process{J}. Advanced Engineering Informatics, 2016, 30(1):26--38.

Digital Library

Google Scholar

[9]

Pramanik S, Mondal K. Cosine Similarity Measure of Rough Neutrosophic Sets and Its Application in Medical Diagnosis{J}. 2015, 2:212--220.

Google Scholar

[10]

Mylavarapu G, Thomas J, Ashwin Kumar T K. Real-Time Hybrid Intrusion Detection System Using Apache Storm{C}// IEEE, International Conference on High PERFORMANCE Computing and Communications. IEEE, 2015.

Digital Library

Google Scholar

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Saravanan SPrakash G(2021)A Comprehensive Survey on Big Data Technology Based Cybersecurity Analytics SystemsApplied Soft Computing and Communication Networks10.1007/978-981-33-6173-7_9(123-143)Online publication date: 2-Jul-2021
https://doi.org/10.1007/978-981-33-6173-7_9
Ullah FBabar M(2019)Quantifying the Impact of Design Strategies for Big Data Cyber Security Analytics: An Empirical Investigation2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)10.1109/PDCAT46702.2019.00037(146-153)Online publication date: Dec-2019
https://doi.org/10.1109/PDCAT46702.2019.00037

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ICNCC '16: Proceedings of the Fifth International Conference on Network, Communication and Computing

December 2016

343 pages

ISBN:9781450347938

DOI:10.1145/3033288

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 17 December 2016

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ICNCC '16: Fifth International Conference on Network, Communication and Computing

December 17 - 21, 2016

Kyoto, Japan

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Saravanan SPrakash G(2021)A Comprehensive Survey on Big Data Technology Based Cybersecurity Analytics SystemsApplied Soft Computing and Communication Networks10.1007/978-981-33-6173-7_9(123-143)Online publication date: 2-Jul-2021
https://doi.org/10.1007/978-981-33-6173-7_9
Ullah FBabar M(2019)Quantifying the Impact of Design Strategies for Big Data Cyber Security Analytics: An Empirical Investigation2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)10.1109/PDCAT46702.2019.00037(146-153)Online publication date: Dec-2019
https://doi.org/10.1109/PDCAT46702.2019.00037

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Host-Based Intrusion Detection System with System Calls: Review and Future Trends

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A web-based system for intrusion detection

Host-Based Intrusion Detection System with System Calls: Review and Future Trends

Network intrusion detection

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