Iman Almomani

Ubiquitous GPS vehicle tracking and management system

Global Positioning System (GPS) is becoming widely used for tracking and monitoring vehicles. Many systems have been created to provide such services which make them popular and needed more than ever before. In this paper a “GPS vehicle tracking system” is proposed. This system is useful for fleet operators in monitoring driving behavior of employees or parents monitoring their teen drivers. Moreover, this system can be used in theft prevention as a retrieval device in addition of working as a security system combined with car alarms. The main contribution of this paper is providing two types of end user applications, a web application and a mobile application. This way the proposed system provides a ubiquitous vehicle tracking system with maximum accessibility for the user anytime and anywhere. The systems tracking services includes acquiring the location and ground speed of a given vehicle in the current moment or on any previous date. It also monitors the vehicle by setting speed and geographical limits and therefore receiving SMS alerts when the vehicle exceeds these pre-defined limits. Additionally, all the movements and stops of a given vehicle can also be monitored. Tracking vehicles in our system uses a wide range of new technologies and communication networks including General Packet Radio Service (GPRS), Global System for Mobile Communication (GSM), the Internet or the World Wide Web and Global Positioning System (GPS).

Non-intrusive speech quality prediction in VoIP networks using a neural network approach

Measuring speech quality in Voice over Internet Protocol (VoIP) networks is an increasingly important application for legal, commercial and technical reasons. Any proposed solution for measuring the quality should be applicable in monitoring live-traffic non-intrusively. The E-Model proposed by the International Telecommunication Union-Telecommunication Standardisation Sector (ITU-T) achieves this, but it requires subjective tests to calibrate its parameters. In this paper a solution is proposed to extend the E-Model to any new network conditions and for newly emerging speech codecs without the need for the time-consuming, expensive, hard to conduct subjective tests. The proposed solution is based on an artificial neural network model and is compared against the E-Model to check its prediction accuracy.

FEAR: Fuzzy-Based Energy Aware Routing Protocol for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are used in different civilian, military, and industrial applications. Recently, many routing protocols have been proposed attempting to find suitable routes to transmit data. In this paper we propose a Fuzzy Energy Aware tree-based Routing (FEAR) protocol that aims to enhance existing tree-based routing protocols and prolong the network’s life time by considering sensors’ limited energy. The design and implementation of the new protocol is based on cross-layer structure where information from different layers are utilized to achieve the best power saving. Each node maintains a list of its neighbors in order to use neighbors’links in addition to the parent-child links. The protocol is tested and compared with other tree-based protocols and the simulation results show that FEAR protocol is more energy-efficient than comparable protocols. According to the results FEAR protocol saves up to 70.5% in the number of generated control messages and up to 55.08% in the consumed power.

Security Model for Tree-based Routing in Wireless Sensor Networks: Structure and Evaluation

The need for securing Wireless Sensor Networks (WSNs) is essential especially in mission critical fields such as military and medical applications. Security techniques that are used to secure any network depend on the security requirements that should be achieved to protect the network from different types of attacks. Furthermore, the characteristics of wireless networks should be taken into consideration when applying security techniques to these networks. In this paper, energy efficient Security Model for Tree-based Routing protocols (SMTR) is proposed. In SMTR, different attacks that could face any tree-based routing protocol in WSNs are studied to design a security reference model that achieves authentication and data integrity using either Message Authentication Code (MAC) or Digital Signature (DS) techniques. The SMTR communication and processing costs are mathematically analyzed. Moreover, SMTR evaluation is performed by firstly, evaluating several MAC and DS techniques by applying them to tree-based routing protocol and assess their efficiency in terms of their power requirements. Secondly, the results of this assessment are utilized to evaluate SMTR phases in terms of energy saving, packet delivery success ratio and network life time.

WSN-DS: A Dataset for Intrusion Detection Systems in Wireless Sensor Networks

Wireless Sensor Networks (WSN) have become increasingly one of the hottest research areas in computer science due to their wide range of applications including critical military and civilian applications. Such applications have created various security threats, especially in unattended environments. To ensure the security and dependability of WSN services, an Intrusion Detection System (IDS) should be in place. This IDS has to be compatible with the characteristics of WSNs and capable of detecting the largest possible number of security threats. In this paper a specialized dataset for WSN is developed to help better detect and classify four types of Denial of Service (DoS) attacks: Blackhole, Grayhole, Flooding, and Scheduling attacks. This paper considers the use of LEACH protocol which is one of the most popular hierarchical routing protocols in WSNs. A scheme has been defined to collect data from Network Simulator 2 (NS-2) and then processed to produce 23 features. The collected dataset is called WSN-DS. Artificial Neural Network (ANN) has been trained on the dataset to detect and classify different DoS attacks. The results show that WSN-DS improved the ability of IDS to achieve higher classification accuracy rate. WEKA toolbox was used with holdout and 10-Fold Cross Validation methods. The best results were achieved with 10-Fold Cross Validation with one hidden layer. The classification accuracies of attacks were 92.8%, 99.4%, 92.2%, 75.6%, and 99.8% for Blackhole, Flooding, Scheduling, and Grayhole attacks, in addition to the normal case (without attacks), respectively.

Dynamic Load Balancing Protocol (DLBP) for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are resource-constrained networks that have been applied in many applications. Many researchers have presented routing protocols to prolong the lifetime of WSNs. In this paper we present a Dynamic Load Balancing Protocol (DLBP) that exploits all network nodes to achieve load balancing and prolong the lifetime of WSN. DLBP has succeeded to build a load balanced tree, eliminate the need for control messages during data routing, keep the load of the WSN balanced during data routing, send messages to next hops without route-discovery delay, quickly maintain and fix network errors and failures. Simulation results show that the network success ratio has reached 97%. Routing overhead has decreased by 72% and network lifetime has increased by 20% comparing to other tested algorithms.

Secure cluster-based SIP service over Ad hoc networks

Session Initiation Protocol (SIP) is the dominant protocol used for VoIP signaling. SIP is required to be adapted for use over decentralized environment instead of the overlay infrastructure-based networks. This research proposes a secure cluster-based SIP service over Ad hoc network to protect the adapted SIP service from several types of attacks. It eliminates the shortcomings of centralized approaches such as single point of failure. Additionally., it cuts off the overhead presented by fully distributed approaches. We conducted sets of simulation experiments to evaluate the proposed solution through different metrics. The advantage of using secure solution versus the non-secure solution has been studied. Secure solution overcomes the use of the non-secure one. It maintains higher call signaling success ratio than non-secure by 58% under high black hole attacker ratio. Non-secure solution, under Denial of Service (DoS) attack, suffers overhead that can reach up to 13.5 times the overhead resulted from the use of the secure solution.

Logic-Based Security Architecture for Systems Providing Multihop Communication

Security is a basic element of distributed systems such as ad hoc and sensor communication networks. Several standards define security requirements and enforcers, such as ITU-T Recommendations X.800 and X.805. It is essential to specify and analyze protocols to know which security requirements they achieve. This paper presents a logic-based security architecture (LBSA). LBSA is a systematic way to test if a protocol is secure by checking what security requirements are achieved. Different rules, actions, and sets which fit into the proposed LBSA are included, new ones are also added to complete the architecture. The key advantage of LBSA is that it enables a security protocol to prove its correctness mathematically. Mathematical proofs provided by LBSA cover more cases that usually cannot be covered exhaustively by simulation tools. This paper also specifies and analyzes several security enforcers and protocols and mathematically proves which security requirements they achieve. Mapping between security requirements and inference rules/actions is also provided to facilitate the use of LBSA. Some enforcers are analyzed using LBSA to demonstrate how they achieve security requirements. Finally, we take Ariadne protocol as a case study and show how to use the proposed LBSA architecture to prove that this protocol is secure.

An Improved E-Model Using Artificial Neural Network VoIP Quality Predictor

Voice over Internet Protocol (VoIP) networks are an increasingly im- portant fleld in the world of telecommunication due to many involved advantages and potential revenue. Measuring speech quality in VoIP networks is an important aspect of such networks for legal, commercial and technical reasons. The E-model is a widely used objective approach for measuring the quality as it is applicable to monitoring live-tra-c, automatically and non-intrusively. The E-model sufiers from several drawbacks. Firstly, it considers the efiect of packet loss on the speech quality collectively without looking at the content of the speech signal to check whether the loss occurred in voiced or unvoiced parts of the signal. Secondly, it depends on subjective tests to calibrate its parameters, which makes it applicable to limited conditions corresponding to speciflc subjective experiments. In this pa- per, a solution is proposed to overcome these two problems. The proposed solution improves the accuracy of the E-model by difierentiating between packet loss dur- ing speech and silence periods. It also avoids the need for subjective tests, which makes it extendable to new network conditions. The proposed solution is based on an Artiflcial Neural Networks (ANN) approach and is compared with the accurate Perceptual Evaluation of Speech Quality (PESQ) model and the original E-model to conflrm its accuracy. Several experiments are conducted to test the efiectiveness of the proposed solution on two well-known ITU-T speech codecs; namely, G.723.1 and G.729.