Tarek R. Sheltami

EAACK—A Secure Intrusion-Detection System for MANETs

The migration to wireless network from wired network has been a global trend in the past few decades. The mobility and scalability brought by wireless network made it possible in many applications. Among all the contemporary wireless networks, Mobile Ad hoc NETwork (MANET) is one of the most important and unique applications. On the contrary to traditional network architecture, MANET does not require a fixed network infrastructure; every single node works as both a transmitter and a receiver. Nodes communicate directly with each other when they are both within the same communication range. Otherwise, they rely on their neighbors to relay messages. The self-configuring ability of nodes in MANET made it popular among critical mission applications like military use or emergency recovery. However, the open medium and wide distribution of nodes make MANET vulnerable to malicious attackers. In this case, it is crucial to develop efficient intrusion-detection mechanisms to protect MANET from attacks. With the improvements of the technology and cut in hardware costs, we are witnessing a current trend of expanding MANETs into industrial applications. To adjust to such trend, we strongly believe that it is vital to address its potential security issues. In this paper, we propose and implement a new intrusion-detection system named Enhanced Adaptive ACKnowledgment (EAACK) specially designed for MANETs. Compared to contemporary approaches, EAACK demonstrates higher malicious-behavior-detection rates in certain circumstances while does not greatly affect the network performances.

Video transmission enhancement in presence of misbehaving nodes in MANETs

Mobile Ad-hoc NETworks (MANET) are infrastructureless networks where self-configuring mobile nodes are connected by wireless links. Because of its decentralized operation, these nodes rely on each other to store and forward packets. Video transmission over MANETs is more challenging than over conventional wireless networks due to rapid topology changes and lack of central administration. Most of the proposed MANET protocols assume that all nodes are working within a cooperative and friendly network context. However, misbehaving nodes that exhibit abnormal behaviors can disrupt the network operation and affect the network availability by refusing to cooperate to route packets due to their selfish or malicious behavior. In this paper, we examine the effect of packet dropping attacks on video transmission over MANETs. We also study the effects of mitigation using intrusion detection systems to MANET in presence of video traffic. To the best of our knowledge, this is the first attempt to study multimedia over such environments. We propose a novel intrusion detection system, which is an adaptive acknowledgment scheme (AACK) with the ability to detect misbehaved nodes and avoid them in other transmissions. The aim of AACK scheme is to overcome watchdog weaknesses due to collisions and limited transmission power and also to improve TWOACK scheme. To demonstrate the performance of our proposed scheme, simulation experiments are performed. The results of our experiments show that MPEG4 is more suitable for our simulation environment than H264 video traffic. The simulation results show that AACK scheme provides better network performance with less overhead than other schemes; it also shows that AACK outperforms both TWOACK and watchdog in video transmission applications in the presence of misbehaving nodes.

Detecting misbehaving nodes in MANETs

There has been a tremendous growth in the use of wireless communication in the past few decades. Mobile Ad hoc NETwork (MANET) is one of the most important one among various wireless communication mechanisms. In MANET, each node in a network performs as both a transmitter and a receiver. They rely on each other to store and forward packets. Its unique infrastructureless network and self-configuring capability makes it ideal for many mission critical applications, including military use and remote exploration. However, these characteristics also make MANET vulnerable to passive and active attacks due to its open medium, changing topology and lack of centralized monitoring. To address the new security challenges, Intrusion Detection System (IDS) is required to detect the malicious attackers before they can accomplish any significant damages to the network. Many existing IDSs for MANETs are based upon Watchdog mechanism. In this paper, we propose a new IDS called Enhanced Adaptive ACKnowledgement (EAACK) that solves four significant problems of Watchdog mechanism, which are ambiguous collisions, receiver collisions, limited transmission power and false misbehavior report. We use Network Simulator 2 to simulate the proposed mechanism and compare the results with existing mechanisms.

Mobility Prediction in Mobile Ad Hoc Networks Using Extreme Learning Machines

Abstract Recent advances in wireless technology and computing have paved the way to the unprecedented rapid growth in de- mand and availability of mobile networking and services coupled with diverse system/network applications. Such advances triggered the emergence of future generation wireless networks and services to address the increasingly strin- gent requirements of quality-of-service (QoS) at various levels. The expected growth in wireless network activity and the number of wireless users will enable similar growth in bandwidth-crunching wireless applications to meet the QoS requirements. Mobility prediction of wireless users and units plays a major role in efficient planning and manage- ment of the bandwidth resources available in wireless networks. In return, this efficiency will allow better planning and improved overall QoS in terms of continuous service availability and efficient power management. In this paper, we propose extreme learning machines (ELMs), known for universal approximation, to model and predict mobility of arbitrary nodes in a mobile ad hoc network (MANET). MANETs use mobility prediction in location-aided routing and mobility aware topology control protocols. In these protocols, each mobile node is assumed to know its current mobility information (position, speed and movement direction angle). In this way, future node positions are predicted along with future distances between neighboring nodes. Unlike multilayer perceptrons (MLPs), ELMs capture better the existing interaction/correlation between the cartesian coordinates of the arbitrary nodes leading to more realistic and accurate mobility prediction based on several standard mobility models. Simulation results using standard mobility models illustrate how the proposed prediction method can lead to a significant improvement over conventional methods based on MLPs. Moreover, the proposed solution circumvents the prediction accuracy limitations in current algorithms when predicting future distances between neighboring nodes. The latter prediction is required by some applications like mobility aware topology control protocols.

RTSP: An Accurate and Energy-Efficient Protocol for Clock Synchronization in WSNs

Wireless sensor networks need accurate time synchronization for data consistency and coordination. Although the existing algorithms for time synchronization offer very good accuracy, their energy consumption is high, and distant nodes are poorly synchronized. We propose a Recursive Time Synchronization Protocol (RTSP) which accurately synchronizes all the nodes in a network to a global clock using multi-hop architecture in an energy-efficient way. It achieves better performance due to the MAC-layer time-stamping based on Start of Frame Delimiter byte, infrequent broadcasts by a dynamically elected reference node, compensation of the propagation delay and adjustment of the timestamps at each hop, estimation of the relative skew and offset using least square linear regression on two data points (2LR), adaptive re-synchronization interval, aggregation of the synchronization requests, and energy awareness. A detailed analysis of the sources of errors is also provided. Simulation results show that the RTSP can achieve an average accuracy of 0.3 microseconds in a large multi-hop flat network while using five-times lesser energy than that of FTSP in the long run and performs even better in a clustered network where it can achieve an average accuracy of 0.23 microseconds while using seven-times lesser energy.

Detecting Forged Acknowledgements in MANETs

Over the past few years, with the trend of mobile computing, Mobile Ad hoc Network (MANET) has become one of the most important wireless communication mechanisms among all. Unlike traditional network, MANET does not have a fixed infrastructure, every single node in the network works as both a receiver and a transmitter. Nodes directly communicate with each other when they are both within their communication ranges. Otherwise, they rely on their neighbors to store and forward packets. As MANET does not require any fixed infrastructure and it is capable of self configuring, these unique characteristics made MANET ideal to be deployed in a remote or mission critical area like military use or remote exploration. However, the open medium and wide distribution of nodes in MANET leave it vulnerable to various means of attacks. It is crucial to develop suitable intrusion detection scheme to protect MANET from malicious attackers. In our previous research, we have proposed a mechanism called Enhanced Adaptive Acknowledgement (EAACK) scheme. Nevertheless, it suffers from the threat that it fails to detect misbehaving node when the attackers are smart enough to forge the acknowledgement packets. In this paper, we introduce Digital Signature Algorithm (DSA) into the EAACK scheme, and investigate the performance of DSA in MANET. The purpose of this paper is to present an improved version of EAACK called EAACK2 that performs better in the presence of false misbehavior and partial dropping.

An efficient energy aware clusterhead formation infrastructure protocol for MANETs

In this paper, we propose a novel cluster-based infrastructure creation protocol, namely: warning energy aware clusterhead (WEAC). WEAC establishes a dynamic wireless mobile infrastructure. As in all cluster-based infrastructure protocols, in the WEAC protocol, a mobile node is elected from a set of nominees to act as a temporary base station for a period of time within its zone. We study the characteristics and performance of the WEAC protocol by means of simulation. It is shown that the WEAC protocol scales well to large networks of mobile stations, and it outperforms other routing energy saving amongst the network. The WEAC protocol would facilitate the development of a comprehensive and promising framework for quality of service (QoS) management in wireless mobile ad hoc networks once the proper integration of the MAC protocol with the routing and call admission control mechanisms is established. At that time, it would lay the groundwork for assigning bandwidth, and/or implementing priorities, and hence for QoS-based routing by conveying the quality of a path prior to call setup.

AACK: Adaptive Acknowledgment Intrusion Detection for MANET with Node Detection Enhancement

A Mobile Ad-hoc NETwork (MANET) is an infrastructureless network consisting of self-configuring mobile nodes connected by wireless links. Nodes rely on each other to store and forward packets. Most of the proposed MANET protocols assume cooperative and friendly network context, and do not address security issues. Furthermore, MANETs are highly vulnerable for passive and active attacks because of their open medium, rapidly changing topology, lack of centralized monitoring. Encryption and authentication solutions, which are considered as the first line of defense, are not sufficient to protect MANETs from packet dropping attacks. Most of the current Intrusion Detection Systems (IDSs) for MANETS rely on the Watchdog technique. In this research we study the behavior of this technique and propose a novel mechanism, named: Adaptive ACKnowledgment (AACK), for solving two significant problems: the limited transmission power and receiver collision. This mechanism is an enhancement to the TWOACK scheme where its detection overhead is reduced while the detection efficiency is increased. NS2 is used to simulate and evaluate the proposed scheme and compare it against the TWOACK and Watchdog methods. The obtained results show that the new AACK scheme outperforms both of the TWOACK and Watchdog methods in terms of network packet delivery ratio and routing overhead.

A review of techniques and technologies for sand and dust storm detection

Sand and dust storms (SDSs) are common phenomena in many parts of the world, which offer serious hazards to the environment, economy and health. An early warning of the approaching SDS would allow people to take precautionary measures and help minimize its terrible effects on the daily life. This requires continuous monitoring of the fugitive dust, sandstorms and movements of sandbanks in a certain area. Several technologies for monitoring of the dust and other environmental changes are available, such as lookout-tower, video-surveillance, sensory information, satellite imagery, unmanned aerial vehicle and hybrid approaches. A particular technology is suitable only for detecting the certain types of SDS, but a hybrid approach can detect many types of SDS. In this paper, we provide a quick review of the techniques and technologies for SDS monitoring. We provide an overview of the data requirements, dust modeling and techniques for SDS detection and prediction. We also summarize, classify and compare different technologies for SDS detection and prediction, and propose that a hybrid approach consisting of satellite imagery and wireless sensor networks is best suitable for detecting and predicting SDSs of all types.

Multi-agent-based clustering approach to wireless sensor networks

This paper presents a multi-agent system for hierarchical routing in a Wireless Sensor Network (WSN). The agents communicate and collaborate with each other and benefit from learning techniques, more specifically genetic algorithms. The proposed system consists of four types of agents, including regional, interface, cluster and query agents. The regional agent resides on the base-station and performs genetic algorithm intense computing. The interface agent interacts with the users to fulfil their interests. The cluster agents manage all agents within clusters for query dissemination and efficiency in network. The query agents reside in each sensor and acquire, aggregate, process the useful data, and transmit the desired results. A prototype of all agents is simulated. For a given radio model our test results revealed that our multi-agent-based approach for hierarchical routing not only outperforms other routing protocols such as LEACH, but also determines the set of optimum clusters for various topologies.