Improving Data Transmission Rate with Self Healing Activation Model for Intrusion Detection with Enhanced Quality of Service

Several types of attacks can easily compromise a Wireless Sensor Network (WSN). Although not all intrusions can be predicted, they may cause significant damage to the network and its nodes before being discovered. Due to its explosive growth and the infinite scope in terms of applications and processing brought about by 5G, WSN is becoming more and more deeply embedded in daily life. Security breaches, downed services, faulty hardware, and buggy software can all cripple these enormous systems. As a result, the platform becomes unmaintainable when there are a million or more interconnected devices. When it comes to network security, intrusion detection technology plays a crucial role, with its primary function being to constantly monitor the health of a network and, if any aberrant behavior is detected, to issue a timely warning to network administrators. The current network's availability and dependability are directly tied to the efficacy and timeliness of the Intrusion Detection System (IDS). An Intrusion-Tolerant system would incorporate self-healing mechanisms to restore compromised data. System attributes such as readiness for accurate service, supply identical and correct data, confidentiality, and availability are necessary for a system to merit trust. In this research, self-healing methods are considered that can detect intrusions and can remove with intellectual strategies that can make a system fully autonomous and fix any problems it encounters. In this study, a new architecture for an Intrusion Tolerant Self Healing Activation Model for Improved Data Transmission Rate (ITSHAM-IDTR) is proposed for accurate detection of intrusions and self repairing the network for better performance, which boosts the server's performance quality and enables it to mend itself without any intervention from the administrator. When compared to the existing paradigm, the proposed model performs in both self-healing and increased data transmission rates.

Applying mobile agents in an immune-system-based intrusion detection system

Nearly all present-day commercial intrusion detection systems are based on a hierarchical architecture. In such an architecture, the root node is responsible for detecting intrusions and for issuing responses. However, an intrusion detection system (IDS) based on a hierarchical architecture has many single points of failure. For example, by disabling the root node, the intrusion-detection function of the IDS will also be disabled. To solve this problem, an IDS inspired by the human immune system is proposed. The proposed IDS has no single component that is responsible for detecting intrusions. Instead, the intrusion-detection function is divided and placed within mobile agents. Mobile agents act similarly to white blood cells of the human immune system and travel from host to host in the network to detect intrusions. The IDS is fault-tolerant because it can continue to detect intrusions even when most of its components have been disabled.Computer Science (School of Computing)M. Sc. (Computer Science

Performance of Vehicular Delay Tolerant Network (VDTN) Based on Intrusion Detection System (IDS)

Security is a fundamental issue to achieve desired QoS on Vehicular Delay Tolerant Network (VDTN). VDTN network are prone from specific attacks such as malicious nodes, one of malicious nodes is a blackhole attack which is one a kind of DoS attack where blackhole is simply dropping the packets or not forwarding the packets. This research was implemented the IDS algorithm that previously researched on the MANET network with some improvement, the IDS on MANET is based on the node collaboration, collection and analysis of system and network audit data. Vehicle nodes run the IDS independently and will be observing the behavior of neighbor nodes, look for intrusion signs locally, and making decision to protect the system from attack or it can also requesting for data from neighboring nodes. ONESim tool is used on the simulation to represent the vehicles mobility on real geographical map with vehicle speed clustering scenario. Meanwhile blackhole and IDS implementation is using Network Simulator (NS-2) tool to measure the key metrics performance, which consist of Throughput, Packet Loss, End to End Delay and Normalized Routing Load (NRL). The simulation shown that the IDS algorithm can improve all performance metrics significantly. The throughput are increased by 112% in average for each cluster, the packet loss are decreased by 20% in average for each cluster, the end to end delay are increased with 46% in average, and finally the NRL has improved 118% in average. This simulation results indicating a promising performance of Vehicle to Vehicle (V2V) communication in future development

FOREVER: Fault/intrusiOn REmoVal through Evolution & Recovery

The goal of the FOREVER project is to develop a service for Fault/intrusiOn REmoVal through Evolution & Recovery. In order to achieve this goal, our work addresses three main tasks: the definition of the FOREVER service architecture; the analysis of how diversity techniques can improve resilience; and the evaluation of the FOREVER service. The FOREVER service is an important contribution to intrustion-tolerant replication middleware and significantly enhances the resilience