In this modern era, the network related applications, programs and services are growing enormously but the network security issues also grow along with them. Keeping the network secure is a challenging and a crucial task. To maintain the secure network there must be some system which can detect and identify any malicious activity happening in network. This system is called as Intrusion Detection System. There are many traditional network security tools and techniques of preventing intrusion like firewalls, anti-virus, encryption-decryption, access control etc. But all are not effective in protecting network from increasing attacks. The network traffic can be categories into normal and intrusive traffic using Machine Learning (ML) algorithms. Here, the preliminary comparative study regarding which type of machine learning algorithm performs better in identifying the attacks namely Denial of Service, Probe, User to Root and Remote to Local. The NSL-KDD dataset is used to study features and behavior of malicious attacker using machine learning techniques. This study can be taken as reference for mechanical engineers for developing a safe automation in industrial atmosphere and automation in automobile.
The cellular network keeps the vast capacity of queue space at eNodeBs (base stations) to reduce the queue overflow during the burst in data traffic. However, this adversely affects the delay sensitive applications and user quality of experience. Recently, few researchers have focused on reducing the packet delay, but it has a negative impact on the utilization of network resource by the users. Further, it fails to maintain fairness among the users, when competing for a shared resource in coexistence with conventional TCP or UDP users. Therefore, in this paper, the adaptive receiver-window adjustment (ARWA) algorithm is proposed to efficiently utilize the network resources and ensure fairness among the users in resource competitive environment, which requires slight modification of TCP at both the sender and receiver. The proposed mechanism dynamically varies the receiver window size based on the data rate and delay information of the packets, to enhance the performance of the system. Based on extensive experiments, the results illustrate that the ARWA algorithm reduces the delay of TCP packet and increases fairness among the users. In addition to that, it enhances the packet delivery fraction (PDF) and maintains the throughput of the system. Moreover, it competes with other conventional TCP users for the shared network resources in a fair manner.
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