DDOS Detection Using Machine Learning Technique
Numerous attacks are performed on network infrastructures. These include attacks on network availability, confidentiality and integrity. Distributed denial-of-service (DDoS) attack is a persistent attack which affects the availability of the network. Comm
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Abstract Numerous attacks are performed on network infrastructures. These include attacks on network availability, confidentiality and integrity. Distributed denial-of-service (DDoS) attack is a persistent attack which affects the availability of the network. Command and Control (C & C) mechanism is used to perform such kind of attack. Various researchers have proposed different methods based on machine learning technique to detect these attacks. In this paper, DDoS attack was performed using ping of death technique and detected using machine learning technique by using WEKA tool. NSL-KDD dataset was used in this experiment. Random forest algorithm was used to perform classification of the normal and attack samples. 99.76% of the samples were correctly classified. Keywords DDoS · Machine learning · Ping of death · Network security · Random forest · NSL-KDD
S. Pande · A. Khamparia (B) School of Computer Science Engineering, Lovely Professional University, Phagwara, Punjab, India e-mail: [email protected] S. Pande e-mail: [email protected] D. Gupta Maharaja Agrasen Institute of Technology, New Delhi, India e-mail: [email protected] D. N. H. Thanh Department of Information Technology, School of Business Information Technology, University of Economics Ho Chi Minh City, Ho Chi Minh City, Vietnam e-mail: [email protected] © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. Khanna et al. (eds.), Recent Studies on Computational Intelligence, Studies in Computational Intelligence 921, https://doi.org/10.1007/978-981-15-8469-5_5
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1 Introduction With the ongoing convergence of data innovation (IT), various data gadgets are turning out to be massively muddled. Associated with one another, they keep on making furthermore spare significant computerized information, introducing a period of big data. However, the probability is extremely high that they may expose significant data as they transmit a lot of it through consistent correspondence with one another. A framework turns out to be more vulnerable as more digital devices are connected. Hackers may additionally target it to take information, individual data, and mechanical insider facts and break them for unlawful additions [1]. Given these conditions, attack detection system (ADS) ought to likewise be more smart and successful than previously to battle attack from hackers, which are continuously evolving. Confidentiality, integrity and availability can be considered as the main pillars of security [2, 3]. All these pillars are discussed below.
1.1 Confidentiality Confidentiality is also called as secrecy. The motive behind secrecy is to keep sensitive information away from illegitimate user and to provide access to the legitimate user. Along with this, assurance must be given on restricted access of the information.
1.2 Integrity Integrity means keeping up the data as it is without any modification in the data. Data must be received as it at the receiver en
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