Corpus ID: 201932076

Performance Analysis of Big Data Intrusion Detection System over Random Forest Algorithm

@inproceedings{AlAwsat2018PerformanceAO,
  title={Performance Analysis of Big Data Intrusion Detection System over Random Forest Algorithm},
  author={Al-Furat Al-Awsat},
  year={2018}
}
  • Al-Furat Al-Awsat
  • Published 2018
    • The Internet has grown rapidly in the last ten years. Consequently, the interconnection of computers and network devices has become so complex for monitoring that even the security experts do not fully understand its deepest inner workings. Personal computers have become very fast every year. It is not rare for a very ordinary person to connect to the Internet through 20 Mbs lines or faster. With this huge network data the network security has becomes very important for monitoring the data. The… CONTINUE READING
    ripublication.com
    9 Citations
    Highly Influential Citations
    1
    Background Citations
    7
    Methods Citations
    5

    Figures and Tables from this paper

    Figures and Tables

    9 Citations
    Citation Type

    Citation Type

    Big Data Security Analysis in Network Intrusion Detection System
    Performance Evaluation of Classification Algorithms in the Design of Apache Spark based Intrusion Detection System
    • 1
    Intrusion detection model using naive bayes and deep learning technique
    • 1
    • PDF
    Anomaly-based Intrusion Detection using Machine Learning Algorithms-A Review Paper
    • Ambreen Sabha
    • 2020
    • Highly Influenced
    • PDF
    Ensemble-Based Online Machine Learning Algorithms for Network Intrusion Detection Systems Using Streaming Data
    • 1
    • PDF
    An Approach for Optimizing Ensemble Intrusion Detection Systems
    • PDF
    CICIDS-2017 Dataset Feature Analysis With Information Gain for Anomaly Detection
    • 6
    • PDF
    Implementing DMZ in Improving Network Security of Web Testing in STMIK AKBA
    • 7
    • PDF
    Machine learning analysis of microbial flow cytometry data from nanoparticles, antibiotics and carbon sources perturbed anaerobic microbiomes
    • 6

    References

    SHOWING 1-10 OF 19 REFERENCES
    A Novel Data Mining based Hybrid Intrusion Detection Framework
    • 27
    • PDF
    Towards MapReduce based classification approaches for Intrusion Detection
    • Rachana Sharma, P. Sharma, P. Mishra, E. Pilli
    • Computer Science
    • 2016 6th International Conference - Cloud System and Big Data Engineering (Confluence)
    • 2016
    • 4
    Relevance feature selection with data cleaning for intrusion detection system
    • 27
    Anomaly Based Intrusion Detection Using Hybrid Learning Approach of Combining k-Medoids Clustering and Naïve Bayes Classification
    • R. Chitrakar, Huang Chuan-he
    • Computer Science
    • 2012 8th International Conference on Wireless Communications, Networking and Mobile Computing
    • 2012
    • 48
    Development of an Intrusion Detection System based on Big Data for Detecting Unknown Attacks
    • Miss Gurpreet Kaur Jangla, M. Deepa, A. Amne
    • 2015
    • 6
    A Clustering Algorithm Use SOM and K-Means in Intrusion Detection
    • 34
    Big Data Analytics for Network Intrusion Detection: A Survey
    • 40
    Knowledge Discovery from Big Data for Intrusion Detection Using LDA
    • 21
    • PDF
    An Intrusion-Detection Model
    • D. Denning
    • Computer Science
    • 1986 IEEE Symposium on Security and Privacy
    • 1986
    • 1,195
    • PDF
    The role of big data in improving power system operation and protection
    • M. Kezunovic, Le Xie, S. Grijalva
    • Engineering
    • 2013 IREP Symposium Bulk Power System Dynamics and Control - IX Optimization, Security and Control of the Emerging Power Grid
    • 2013
    • 130
    • PDF