Computer Science Research Articles
Single Platform to Read Collections of Research Articles
Improving Performance and Efficiency of Software-Defined Networking by Identifying Malicious Switches through Deep Learning Model
Thangaraj Ethilu, Abirami Sathappan, Paul Rodrigues
Abstract - In recent times, Software Defined Networking (SDN) has developed widely to provide capable solutions for future internet services. As with the solutions, SDN brings us a hazardous rise in malicious threats. We investigated a sort of Distributed Denial of Services (DDoS) assault known as an internet services attack, which evaluates the influence of both traffic flow and throughput depletions in order to characterize the abnormalities. This sort of attack has a significant impact on the whole SDN. This paper introduces a deep learning method to improve the performance efficiency of the SDN by classifying the network switch into either a trusted switch or a malicious switch device. In this research, an attack detection methodology for Internet services utilizing Software Defined Networking (SDN) is proposed. The SDN controller may evaluate traffic flow, detect anomalies, and restrict both incoming and outgoing traffic as well as source nodes. The SDN considers a Convolutional Neural Network (CNN) based attack detection system that can identify malicious node. Kaggle datasets are used to test and train CNN and the features such as packet duration, packet count, byte count, accuracy for identifying the flow of trusted and malicious switches. According to the results, the CNN-based attack detection system can identify the attack with an accuracy of 89 percent. The comparison evaluation with the already proposed LeNet CNN of the feature classification proves that the flow is the trusted one and with the constant throughput with the help of the deep learning model.
Published: 2022Read / Download
A Survey on Malware Classification Using Machine Learning and Deep Learning
Manish Goyal, Raman Kumar
Abstract - In today's era, there is fast development in the field of Information Technology. It is a matter of great concern for cyber professionals to maintain security and privacy. Studies revealed that the number of new malware is increasing tremendously. It is a never-ending cycle between the world of attack and the defense of malicious software. Antivirus companies are always putting their efforts to develop signatures of malicious software and attackers are always in try to overcome those signatures. For the detection of malware machine learning are highly efficient. The process of detection of malware is split into two categories first is feature extraction and the second is malware classification. The effectiveness of classification algorithms depends on the feature extracted. In this paper, firstly an in-depth study of the features is provided that can be used to differentiate malware. Thereafter describe the various stages of machine learning and deep learning that researchers use in their research work and the pros and cons they face that can assist new researchers while selecting an algorithm for their research work.
Published: 2021Read / Download
A Study of Machine Learning in Wireless Sensor Network
Zaki Ahmad Khan, Abdus Samad
Abstract - Within this Paper, a concept of machine learning strategies suggested in this investigation to address the design issues in WSNs is introduced. As can be viewed within this paper, countless endeavors have induced up to now; several layout issues in wireless sensor networks have been remedied employing numerous machine learning strategies. Utilizing machine learning based algorithms in WSNs need to deem numerous constraints, for instance, minimal sources of the network application that really needs distinct events to be tracked as well as other operational and non-operational aspects.
Published: 2017Read / DownloadUsage of Machine Learning for Intrusion Detection in a Network
Prachi
Abstract - Increase in volume and intensity of network attacks, forcing the business systems to revamp their network security solutions in order to avoid huge financial losses. Intrusion Detection Systems are one of the most essential security solutions in order to ensure the security of any network. Considering huge volumes of network data and complex nature of intrusions, the performance optimization of Network Intrusion Detection System became an open problem that is gaining more and more .............................
Published: 2016Read / Download