Samy El-Tawab

Improving the security of wireless sensor networks in an IoT environmental monitoring system

The Internet of Things (IoT) has become a popular subject in the technology industry and will soon reach the popularity level of smartphones. With the rapid technological advancements of sensors, Wireless Sensor Networks (WSNs) has become the main technology for IoT. We investigated the security of WSNs in an environmental monitoring system with the goal to improve the overall security. We implemented a Secure Temperature Monitoring System (STMS), which served as our investigational environment. Our results revealed a security flaw found in the bootstrap loader (BSL) password used to protect firmware found in the MSP430 MCU. We demonstrated how the BSL password could be brute forced in a matter of days. Furthermore, to our knowledge we illustrated the first sample of how an attacker can reverse engineer firmware and obtain WSN cryptographic keys. Our sample provides a step-by-step procedure on how to reverse engineer MSP430 firmware. We contributed a solution to improve the BSL password and better protect firmware found in the MSP430 chips. The Secure-BSL software we contributed allows the randomization of the BSL password. Our solution guarantees brute force times in a matter of decades. The impractical brute force time assures the security of firmware and prevents future reverse engineering tactics. In addition, our Secure-BSL software supports two-factor authentication, therefore adding another layer of security. The two-factor authentication feature allows developers to specify a user-defined passphrase to further protect the MSP430 MCU. Our research serves as proof that any security implemented in a WSN environment is broken if an attacker has access to firmware found in sensor devices.

Towards Fault-Tolerant Job Assignment in Vehicular Cloud

Statistics show that most vehicles spend many hours per day in a parking garage, parking lot, or driveway. At the moment, the computing resources of these vehicles are untapped. Inspired by the success of conventional cloud services, a group of researchers have recently introduced the concept of a Vehicular Cloud. The defining difference between vehicular and conventional clouds lie in the distributed ownership and, consequently, the unpredictable availability of computational resources. As cars enter and leave the parking lot, new computational resources become available while others depart creating a dynamic environment where the task of efficiently assigning jobs to cars becomes very challenging. Our main contribution is a fault-tolerant job assignment strategy, based on redundancy, that mitigates the effect of resource volatility of resource availability in vehicular clouds. We offer a theoretical analysis of the expected job completion time in the case where cars do not leave during a checkpoint operation and also in the case where cars may leave while check pointing is in progress, leading to system failure. A comprehensive set of simulations have shown that our theoretical predictions are accurate.

Real-time weather notification system using intelligent vehicles and smart sensors

We introduce a real-time weather notification system in which drivers are notified with any bad weather conditions on the road including icy conditions or foggy conditions. Different type of bad weather requires different type of detection. We combine all cases by placing sensors uniformly to the road with an intelligent vehicles that communicate with the surrounding vehicles and the road itself. Our system depends on the spread sensors placed uniformly on the highway to monitor the road traffic. Cat eyes on the road which has been used for years as a reflectors to help drivers over night or at bad weather conditions can be more smart or intelligent by adding sensing capabilities. Intelligent vehicles can help in detecting some types of bad weather conditions and with the help of the sensors over the road using a combination of vehicle-to-vehicle communication and vehicle-to-infrastructure communication, we can reach a system that gives real-time notice for the drivers. Embedded processors are built inside the sensor over the road to allow the node to process these information.

Scheduling in vehicular cloud using mixed integer linear programming

Statistics show that most vehicles spend many hours per day in a parking garage, parking lot, or driveway. At the moment, the computing resources of these vehicles are untapped. Inspired by the success of conventional cloud services, a group of researchers have recently introduced the concept of a Vehicular Cloud. In this model each vehicle is a computation node. The main difference between traditional cloud computing and vehicular cloud computing is in availability of nodes. In vehicular cloud as opposed to traditional cloud nodes are not available all the time. Random arrival and departure of vehicles create a dynamic environment in terms of resources availability. We present a scheduling model for vehicular cloud based on mixed integer linear programming. This model uses migration in order to prevent interruptions that may be caused by random departure of vehicles.

Ticket-based reliable routing in VANET

One of the notoriously difficult problems in vehicular ad-hoc networks is to ensure that established paths do not break before the end of data transmission. This is a difficult problem because the network topology is changing constantly and the routing links are inherently unstable. Inspired by ticket based probing, we propose a scheme to selects a stable routing path in vehicular network environment. On the basis of stability preference, an optimal path (low-cost, low-delay and high-stability) is considered. Our algorithms consider not only the efficiency of path searching but also the balance of stability, delay, and cost metrics to find the optimal routing path. Several possible paths are searched at the same time. The path selection is based on three types of control packets probing routing paths satisfying stability, delay and cost requirements. Extensive simulations show that the proposed algorithm can tolerate the constantly-changing topology in vehicular ad-hoc networks.

Communication protocols in FRIEND: A cyber-physical system for traffic Flow Related Information Aggregation and Dissemination

In this paper, we explain in depth the communication protocols between different components of FRIEND: a cyber-physical system for traffic Flow-Related Information aggrEgatioN and Dissemination. Recall that FRIEND (which has been introduced in pervious work, by integrating resources and capabilities at the nexus between the cyber and physical worlds, FRIEND will contribute to aggregating traffic flow data collected by the huge fleet of vehicles on our roads into a comprehensive, near real-time synopsis of traffic flow conditions). The main goal of this paper is to discuss the communication protocols employed by various entities in FRIEND. We discuss one of the most fundamental issues in computer networking, which is how two entities can reliably communicate. We start by introducing notation and by establishing terminology that will be used. Then, we discuss how the Road Side Units (RSUs) communicate with different other entities in FRIEND. Also, how data exchange occurs between RSUs and other entities. Then, we explain the communication between Smart Cats Eyes (SCEs) and other FRIEND entities.

A modified TC-MAC protocol for multi-hop cluster communications in VANETs

The transmission of safety/update message aims to inform the nearby vehicles about the senders current status and/or a detected dangerous situation. This type of transmission is designed to help in accident and danger avoidance. Moreover, it requires high message generated rate and high reliability. On the other hand, the transmission of non-safety message aims to increase the comfort on vehicles by supporting several non-safety services, from notifications of traffic conditions to file sharing. Unfortunately, the transmission of non-safety message has less priority than safety messages, which may cause shutting down the comfort services. The goal of this paper is to design a MAC protocol in order to provide the ability of the transmission of non-safety message with little impact on the reliability of transmitting safety message even if the traffic and communication densities are high in a multi-hop cluster. Our protocol is based on modifying TC-MAC which uses TDMA technique for slot reservation based on clustering of vehicles.

DriveBlue: Traffic Incident Prediction through Single Site Bluetooth

Transportation authorities, and traffic management aim to have a free-flow traffic on highways as well as in cities. This paper proposes DriveBlue, a real time system that uses Bluetooth adapters in a single site to predict traffic incidents in various conditions (e.g. congestion), and inform the responsible authorities. DriveBlue leverages the capabilities of co-located Bluetooth adapters to monitors vehicles on roads, categorize them, analyze their behavior over time, and reports any suspicious change. Moreover, DriveBlue has a simple design that is scalable using the infrastructure currently deployed by transportation authorities. In our experiments, we collected real data from highways to evaluate the feasibility of using single site Bluetooth adapters for transportation applications. DriveBlue spotted almost 10 devices per minute, and showed an accuracy of approximately 80% in detecting vehicles motion.

Friend: A cyber-physical system for traffic flow related information aggregation and dissemination

The main purpose of this paper is to present the various mechanisms whereby FRIEND - which is a Cyber-Physical System for traffic Flow Related Information aggrEgatioN and Dissemination, that was introduced in previous work - makes decisions about the state of the traffic and also about the possible occurrence of traffic-related incidents. Recall that FRIEND bases most of the inferences it makes about the status of traffic on two perceived parameters of the traffic flow: speed and density. In turn, the instantaneous density of the flow is deduced by sampling the headway distance of the most recently passing cars. A fundamental theoretical question that we address is the extent to which the sample mean of the collected headway distance data is a good approximation of the overall headway distance. In the paper, we also explain our incident detection algorithm and how we classify various types of incident. Our results show that the traffic parameters discussed in this paper along with historical data collected over a reasonable time period (duly adjusted for diurnal and seasonal variations), and with the aggregated traffic information firmly in hand, FRIEND is ready to disseminate to the traveling public a color-coded traffic status report.

Reasoning About Job Completion Time in Vehicular Clouds

In order to enhance dependability and availability, it is common practice in conventional clouds to assign two servers to each job. In this paper, we investigate the effect of such a redundancy-based job assignment strategy on job completion time in vehicular clouds. We offer a heuristic analysis of the expected job completion time under this strategy. A comprehensive set of simulations confirmed the accuracy of our analytical predictions.