Mitigating the Problem of Packet Dropping & Energy Management in AD-HOC Wireless Network

A mobile ad-hoc network (MANET) is a self-arranged network that consists of mobile routers connected by wireless channels. Anonymity communication is a great challenge in MANET. Though there are many anonymity enhancing techniques that have been introduced. These techniques are based on packet encryption to secure the communication anonymity. Still MANET is vulnerable to passive statistical traffic analysis attacks. There are two features of communication anonymity: end-to-end anonymity and source or destination anonymity. This proposed system is designed to discover the communication pattern without decoding the captured packets. First phase of the proposed system is to search the required node. The search is performed by using a heuristic approach. Second phase is to perform statistical traffic analysis. The purpose of this phase is to discover the data transmission of the searched node to its adjoining nodes. After implementing the statistical traffic analysis whether the searched node plays the role of source or destination is estimated. With the help of this estimation the traffic pattern is discovered. The utility of this proposed system is basically in military environment. In order to track the adversaries attack this system is utilized. The adversaries are not able to know that they have been tracked. This proposed system works passively and perform traffic analysis based on statistical characteristic of captured raw packets

Denial of Service in Web-Domains: Building Defenses Against Next-Generation Attack Behavior

The existing state-of-the-art in the field of application layer Distributed Denial of Service (DDoS) protection is generally designed, and thus effective, only for static web domains. To the best of our knowledge, our work is the first that studies the problem of application layer DDoS defense in web domains of dynamic content and organization, and for next-generation bot behaviour. In the first part of this thesis, we focus on the following research tasks: 1) we identify the main weaknesses of the existing application-layer anti-DDoS solutions as proposed in research literature and in the industry, 2) we obtain a comprehensive picture of the current-day as well as the next-generation application-layer attack behaviour and 3) we propose novel techniques, based on a multidisciplinary approach that combines offline machine learning algorithms and statistical analysis, for detection of suspicious web visitors in static web domains. Then, in the second part of the thesis, we propose and evaluate a novel anti-DDoS system that detects a broad range of application-layer DDoS attacks, both in static and dynamic web domains, through the use of advanced techniques of data mining. The key advantage of our system relative to other systems that resort to the use of challenge-response tests (such as CAPTCHAs) in combating malicious bots is that our system minimizes the number of these tests that are presented to valid human visitors while succeeding in preventing most malicious attackers from accessing the web site. The results of the experimental evaluation of the proposed system demonstrate effective detection of current and future variants of application layer DDoS attacks

Multimedia computer networks quality of service techniques evaluation and development.

The growth in the transmission of time-sensitive applications over computer networks means that Quality of Service (QoS) needs to be managed in an efficient manner. Network QoS management in this thesis refers to evaluation and improvement of QoS provided by integrated wired and wireless computer networks. Evaluation of QoS aims to analyse and quantify network performance with respect of meeting multimedia applications' transmission requirements. QoS improvement involves the ability to take actions to change network performance toward improved operation. Therefore, the main aims of this thesis are: (i) to develop techniques for evaluation QoS in multimedia computer networks, (ii) to develop techniques that uses the information from (i) to manage and improve network performance. Multimedia traffic generates a large amount of data. Collecting this information poses a challenge as it needs to be sufficiently fast and accurate. A contribution of this thesis is that adaptive statistical sampling techniques to sample multimedia traffic were developed and their effectiveness was evaluated. Three different adjustment mechanisms were incorporated into statistical sampling techniques to adjust the traffic sampling rate: simple linear adjustment, quarter adjustment, and Fuzzy Inference System (FIS). The findings indicated that the developed methods outperformed the conventional non-adaptive sampling methods of systematic, stratified and random. The data collected included important QoS parameters, i.e. delay, jitter, throughput, and packet loss that indicated network performance in delivering real-time applications. An issue is that QoS needs evaluation in an informative manner. Therefore, the second contribution of this thesis is that statistical and Artificial Intelligent (AI) techniques were developed to evaluate QoS for multimedia applications. The application's QoS parameters were initially analysed either by Fuzzy C-Means (FCM) clustering algorithm or by Kohonen neural network. The analysed QoS parameters were then used as inputs to a regression model or Multi-Layer Perceptron (MLP) neural network in order to quantify the overall QoS. The proposed QoS evaluation system differentiated the network's QoS into a number of levels (Poor to Good QoS) and based on this information, the overall network's QoS was successfully quantified. In order to facilitate QoS assessment, a portable hand-held device for assessing the QoS in multimedia networks was designed, regression model was implemented on the microcontroller board and its performance was successfully demonstrated.Multimedia applications transmitted over computer networks require a large bandwidth that is a critical issue especially in wireless networks. The challenge is to enable end-to-end QoS by providing different treatments for different classes of traffic and efficient use of network resources. In this thesis, a new QoS enhancement scheme for wireless-wired networks is developed. This scheme consisted of an adaptive traffic allocation algorithm that is incorporated into the network's wireless side to improve the performance of IEEE 802.11e Enhanced Distributed Channel Access (EDCA) protocol, and a Weighted Round Robin (WRR) queuing scheduling mechanism that was incorporated into the wired side. The proposed scheme improved the QoS for Multimedia applications. The average QoS for voice, and video applications were increased from their original values by 72.5%, and 70.3% respectively