Adnan Nadeem

Protection of MANETs from a range of attacks using an intrusion detection and prevention system

Mobile ad hoc networks (MANETs) are well known to be vulnerable to various attacks due to their lack of centralized control, and their dynamic topology and energy-constrained operation. Much research in securing MANETs has focused on proposals which detect and prevent a specific kind of attack such as sleep deprivation, black hole, grey hole, rushing or sybil attacks. In this paper we propose a generalized intrusion detection and prevention mechanism. We use a combination of anomaly-based and knowledge-based intrusion detection to secure MANETs from a wide variety of attacks. This approach also has the capability to detect new unforeseen attacks. Simulation results of a case study shows that our proposed mechanism can successfully detect attacks, including multiple simultaneous different attacks, and identify and isolate the intruders causing a variety of attacks, with an affordable network overhead. We also investigate the impact on the MANET performance of (a) the various attacks and (b) the type of intrusion response, and we demonstrate the need for an adaptive intrusion response.

Application specific study, analysis and classification of body area wireless sensor network applications

The evolution of wearable computing and advances in wearable sensor devices has motivated various applications of Body Area Sensor Networks (BASN). In the last few years body areas sensor networks have emerged as a major type of wireless sensor networks (WSN). This emerging networking technology can be used in various walks of life. A number of surveys have been published on MAC or the physical layer mechanism of BASN but very few have focused on studying it from the application point of view. In this paper, we first review, from literature, existing use of body area sensor network and classify and then its application domain. Within these application domains of BASN, we propose a feasibility of scenarios where BASN can be used for both application and technical aspects. In addition, we classify the use of BASN from literature, based on certain parameters. Finally, we discuss and highlight issues where further research can be conducted in the future.

Evaluating network layer selfish behavior and a method to detect and mitigate its effect in MANETs

A Mobile Ad Hoc Network (MANET) is an infrastructureless network of autonomous devices formed dynamically. At network layer routing protocols in MANETs expect every node to cooperate in routing and data forwarding tasks. However, this cooperation leads towards a state in which nodes consumes their scarce resources for example battery power. Resource constraints of MANET nodes can derive dynamic selfish behavior in terms of not forwarding packets & not cooperating in routing operations. This can lead to degradation in network performance. In this paper, we first perform a simulation based study to evaluate the effects of selfish nodes on network performance. Then in contrast with most of the selfish node detection approaches in literature which are based on fully watchdog methods using promiscuous monitoring. We propose a proactive mechanism that first detects nodes that are exhibiting selfish behavior based on the factors which derives selfish behavior and then mitigate its effect on network performance. Initial simulation results of a case study shows that our method can detect & mitigate the effect of selfish behavior with an affordable overhead on the network.

Illustration, Detection & Prevention of Sleep Deprivation Anomaly in Mobile Ad Hoc Networks

MANETs (Mobile Ad Hoc Networks) have applications in various walks of life from rescue operations to battle fieled operations, personal and commercial. However, routing operations in MANETs are still vulnerable to anomalies and DoS (Denial of Service) attacks such as sleep deprivation. In SD (Sleep Deprivation) attack malicious node exploits the vulnerability in the route discovery function of the reactive routing protocol for example AODV (Ad Hoc On-Demand Distance Vector). In this paper, we first illustrate the SD anomaly in MANETs and then propose a SD detection and prevention algorithm which efficiently deals with this attack. We assess the performance of our proposed approach through simulation, evaluating its successfulness using different network scenarios.