Network Attack Detection And Classification using ANN Algorithm

Advancement of computer networktechnology and the IT business lead to new security issues in networks emerge on a regular basis, making it increasingly difficult to ignore. How to successfully prevent dangerous network hackers from invading, so that network systems and computers are safe and regular...

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Bibliographic Details
Published in2022 6th International Conference on Computing Methodologies and Communication (ICCMC) pp. 66 - 71
Main Authors Akhil Reddy, D, Puneet, V, Siva Rama Krishna, S, Kranthi, S
Format Conference Proceeding
LanguageEnglish
Published IEEE 29.03.2022
Subjects
Classification algorithms
Computer hacking
Cyber Attacks
Cyber Security
Deep Learning
Feature extraction
IDS
Intrusion detection
Machine Learning
Machine learning algorithms
Network security
Neural networks
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Summary:Advancement of computer networktechnology and the IT business lead to new security issues in networks emerge on a regular basis, making it increasingly difficult to ignore. How to successfully prevent dangerous network hackers from invading, so that network systems and computers are safe and regular functioning, is a critical job for today's network administrators. In recent decades, network security has become increasingly important due to the rapid growth of the Internet and the growing number of users. Intrusion detection systems (IDSs), which attempt to maintain the maximum level of security, have recently become one of the most popular research subjects in network security. Deep learning neural network is used to extract features of network monitoring data, and classify intrusion types. The method will be validated using KDD CUP'99 dataset or any other relevant dataset. The results will be compared with other algorithms to show that the proposed method has a significant improvement over the traditional machine learning model accuracies.
DOI:10.1109/ICCMC53470.2022.9753934