RAAC: A bandwidth estimation technique for admission control in MANET

The widespread of wireless mobile network have increased the demand for its applications. Providing a reliable QoS in wireless medium, especially mobile ad-hoc network (MANET), is quite challenging and remains an ongoing research trend. One of the key issues of MANET is its inability to accurately predict the needed and available resources to avoid interference with already transmitting traffic flow. In this work, we propose a resource allocation and admission control (RAAC) solution. RAAC is an admission control scheme that estimates the available bandwidth needed within a network, using a robust and accurate resource estimation technique. Simulation results obtained show that our proposed scheme for MANET can efficiently estimate the available bandwidth and outperforms other existing approaches for admission control with bandwidth estimation

FEATURE SELECTION FOR INTRUSION DETECTION SYSTEM IN A CLUSTER-BASED HETEROGENEOUS WIRELESS SENSOR NETWORK

Wireless sensor network (WSN) has become one of the most promising networking solutions with exciting new applications for the near future. Notwithstanding the resource constrain of WSNs, it has continued to enjoy widespread deployment.  Security in WSN, however, remains an ongoing research trend as the deployed sensor nodes (SNs) are susceptible to various security challenges due to its architecture, hostile deployment environment and insecure routing protocols. In this work, we propose a feature selection method by combining three filter methods; Gain ratio, Chi-squared and ReliefF (triple-filter) in a cluster-based heterogeneous WSN prior to classification. This will increase the classification accuracy and reduce system complexity by extracting 14 important features from the 41 original features in the dataset. An intrusion detection benchmark dataset, NSL-KDD, is used for performance evaluation by considering detection rate, accuracy and the false alarm rate. Results obtained show that our proposed method can effectively reduce the number of features with a high classification accuracy and detection rate in comparison with other filter methods. In addition, this proposed feature selection method tends to reduce the total energy consumed by SNs during intrusion detection as compared with other filter selection methods, thereby extending the network lifetime and functionality for a reasonable period

DDoS defence for service availability in cloud computing

Cloud computing presents a convenient way of accessing services, resources and applications over the Internet by shifting the focus of industries and organizations from the deployment and day-to-day running of their IT facilities, to provide an on-demand, self-service, and pay-as-you-go business model. Despite its increased popularity, ensuring security and availability of data, resources and services remains an ongoing research challenge. Distributed Denial of Service (DDoS) attacks are not a new threat but they remain a major security challenge in achieving a secure and guaranteed service and resources in cloud computing. Mitigating DDoS attack in cloud computing presents a new dimension to the solutions proffered in traditional computing, therefore, this work proposes DDoS defence solutions that identify and classify packet traffic as either legitimate or malicious, based on its attributes. This thesis has three objectives. Firstly, it investigates a major attribute of DDoS attack, the spoofing of source IP address that hides its identity to disallow easy traceback or deceive the cloud provider to enjoy certain services accrued to a trusted host. Secondly, due to the increased number and sophistication of DDoS attacks against cloud services and the magnitude of traffic that needs to be processed, the analysis of feature selection methods and classification techniques was carried out. Feature selection has been identified as a pre-processing phase in cloud DDoS attack defence that could potentially increase the classification accuracy and reduce the computational complexity, by identifying important features from the original dataset, during supervised learning. Finally, this thesis studies the packet inter-arrival time (IAT) feature of traffic traces, in order to determine the presence of an attack using a change-point detection. The DDoS attack pattern is detected by leveraging on the fact that most DDoS attacks are automated, thus exhibiting similar patterns. The main contributions are as follows: (i) This thesis proposes an IP spoofing detection technique that uses a passive and active host-based operating system (OS) fingerprinting to detect the true source of a packet during a spoofed DDoS attack; (ii) this thesis proposes an ensemble-based multi-filter feature selection (EMFFS) method that combines the output of four filter methods to achieve an optimum selection, and a decision-tree classifier to detect DDoS attacks; and (iii) this thesis proposes a change-point monitoring algorithm to detect DDoS flooding attacks against cloud services, by examining the packet IAT. A DDoS attack pattern is distinguished from normal traffic by using cumulative sum algorithm (CUSUM). The results obtained show a high detection rate and classification accuracy, when compared with other classification techniques in the literature

Denial of service (DoS) defence for resource availability in wireless sensor networks

Wireless sensor networks (WSN) over the years have become one of the most promising networking solutions with exciting new applications for the near future. Its deployment has been enhanced by its small, inexpensive and smart sensor nodes, which are easily deployed, depending on its application and coverage area. Common applications include its use for military operations, monitoring environmental conditions (such as volcano detection, agriculture and management), distributed control systems, healthcare and detection of radioactive sources. Notwithstanding its promising attributes, security in WSN is a big challenge and remains an ongoing research trend. Deployed sensor nodes are vulnerable to various security attacks due to its architecture, hostile deployment location and insecure routing protocol. Furthermore, the sensor nodes in WSNs are characterised by their resource constraints, such as, limited energy, low bandwidth, short communication range, limited processing and storage capacity which have made the sensor nodes an easy target. Therefore, in this work, we present a review of DoS attacks that affect resource availability in WSN and their countermeasure by presenting a taxonomy. Future research directions and open research issues are also discussed.This research is funded by the Advanced Sensor Networks SARChI Chair program, co-hosted by University of Pretoria (UP) and Council for Scientific and Industrial Research (CSIR), through the National Research Foundation (NRF) of South Africa.http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639am2018Electrical, Electronic and Computer Engineerin

Evaluating DoS jamming attack on reactive routing protocol in wireless sensor networks

Wireless sensor networks (WSNs) over the years have emerged as the enabling underlining infrastructure for new wireless technology trends such as Internet-of Things (IoT) and Fog Computing. Its application has spread across diverse fields such as agriculture, military, healthcare and home automation. Despite its promising attributes, it is characterized by its extremely limited resources such as battery energy and memory. Additionally, its deployment in hostile and unattended areas make it vulnerable to security attacks. One of such attacks is the denial of service (DoS) jamming attack that is perpetrated by malicious nodes emitting radio frequency signals to disrupt and interfere with the normal functions of the sensor nodes in the network. This eventually causes a denial of service in the network. Different routing protocols have been proposed over the years to guarantee reliable communication and maintain the network lifetime and functionality for a reasonable duration, notwithstanding DoS jamming attack. Therefore, in this work, we evaluate the effect of a constant jamming DoS attack on two key reactive routing protocols in WSN, ad hoc on-demand distance vector (AODV) and dynamic source routing (DSR). Metrics such as packet sending ratio (PSR), packet loss (PL) and transmitted packets are used to measure the impact of constant jamming DoS attack in the network. Simulation results using network simulation 2 (NS2) and trace graph show that, irrespective of the adopted reactive routing protocol, the impact of the jamming attack is the same