Mouhcine Guennoun

A Survey of Beacon-Enabled IEEE 802.15.4 MAC Protocols in Wireless Sensor Networks

IEEE 802.15.4 is the de facto standard for Wireless Sensor Networks (WSNs) that outlines the specifications of the PHY layer and MAC sub-layer in these networks. The MAC protocol is needed to orchestrate sensor nodes access to the wireless communication medium. Although distinguished by a set of strengths that contributed to its popularity in various WSNs, IEEE 802.15.4 MAC suffers from several limitations that play a role in deteriorating its performance. Also, from a practical perspective, 80.15.4-based networks are usually deployed in the vicinity of other wireless networks that operate in the same ISM band. This means that 802.15.4 MAC should be ready to cope with interference from other networks. These facts have motivated efforts to devise improved IEEE 802.15.4 MAC protocols for WSNs. In this paper we provide a survey for these protocols and highlight the methodologies they follow to enhance the performance of the IEEE 802.15.4 MAC protocol.

Biometric Identification System Based on Electrocardiogram Data

Recent advancements in computing and digital signal processing technologies have made automated identification of people based on their biological, physiological, or behavioral traits a feasible approach for access control. The wide variety of available technologies has also increased the number of traits and features that can be collected and used to more accurately identify people. Systems that use biological, physiological, or behavioral trait to grant access to resources are called biometric systems. In this paper we present a biometric identification system based on the Electrocardiogram (ECG) signal. The system extracts 24 temporal and amplitude features from an ECG signal and after processing, reduces the set of features to the nine most relevant features. Preliminary experimental results indicate that the system is accurate and robust and can achieve a 100% identification rate with the reduced set of features.

WSN Architectures for Intelligent Transportation Systems

The emergence of, and advancement in, integrated digital circuitry technology along with the development of efficient software algorithms made it possible to build small, lightweight wireless nodes equipped with embedded processors, sensors and radio transceivers. By densely deploying these nodes, in a highly distributed manner, we can build a Wireless Sensor Network (WSN). In this network, sensors collaborate in monitoring physical parameters or environmental conditions, such as temperature, sound, vibration, etc. Sensor nodes frequently report the data they capture to a central collection unit that analyses the data and takes appropriate actions if needed. Intelligent Transportation Systems (ITSs) emerged as a potential candidate for benefiting from the unique features and capabilities of WSNs. In ITSs, transportation infrastructure is supported with the ingenious achievements of computer and information technology to resolve severe situations like traffic congestion and cope with emergency conditions like major accidents. In this paper, we study the requirements for an efficient WSN architecture for ITSs, survey the WSN architectures proposed for this type of applications highlighting their strengths and weaknesses, and shed light on future directions in this field of research.

Continuous authentication by electrocardiogram data

Authentication is the process of verifying the claimed identity of a user. Traditional authentication systems suffer from vulnerabilities that can break the security of the system. An example of such vulnerabilities is Replay Attack: An attacker can use a pre-saved password or an authentication credential to log into the system. Another issue with existing authentication systems is that the authentication process is done only at the beginning of a session: once the user is authenticated in the system, her identity is assumed to remain the same during the lifetime of the session. In real world, an attacker can masquerade as a legitimate user by physically controlling an authenticated machine. Therefore, there is a need to continuously monitor the user to determine if the user who is using the computer is the same person that logged onto the system. In this paper, we present a framework for continuous authentication of the user based on the electrocardiogram data collected from the users heart signal. The electrocardiogram (ECG) data is used as a soft biometric to continuously authenticate the identity of the user; Experimental results demonstrate that electrocardiogram biometric trait can guarantee the safety of the system from illegal access.

On the Use of Biometrics to Secure Wireless Biosensor Networks

The fast improvements in a variety of technologies such as microprocessing, sensing material, and most importantly wireless technology resulted in development of the wireless sensor network technology. Wireless sensors that can be either implantable inside the human body or wearable by individuals are called the wireless biosensors. The wireless biosensors are used to gather real time and continuous medical data from different parts of the human beings. This medical data is typically sent to an external sensor and then to its associated destination where data processing and a final decision is carried out. Due to nature of medical data and their usage, ensuring the security of this data is extremely important. There are several limitations associated with biosensor networks such as limitation in power, memory, computation capability, and communication rate which makes the wireless biosensor security a real challenging problem. These security challenges form substantial barriers for the wide adoption of the technology. Biometrics approach is an efficient way to overcome the insecurity of the wireless biosensor networks. In this paper, we will look at how biometrics has helped securing data in wireless biosensor networks, and present the remaining challenges to have a workable biometric-based security framework for wireless biosensor networks.

Adaptive Sleeping Periods in IEEE 802.15.4 for Efficient Energy Savings: Markov-Based Theoretical Analysis

The strict resource-constrained conditions under which Wireless Sensor Networks (WSNs) operate impose primary restrictions on power consumption. Algorithms implemented on sensor nodes should refrain from performing complex computations in order to prolong the lifetime of the overall WSN. The IEEE 802.15.4 standard is the appropriate suite of specifications that conforms to the distinguished characteristics of WSNs. This standard is suited for low data rate, low power, and low radio transmission ranges that are typical in WSNs. This paper proposes a modification to the IEEE 802.15.4 standard that achieves efficient power savings for the sensor nodes, better channel utilization, and improved reliability. The proposal is based on the addition of a sleeping state that allows nodes to save more power while reducing the level of packet collisions. The sleeping periods can be tuned such that the highest level of channel utilization is achieved. A theoretical analysis based on Markov chain is performed to derive a mathematical model for our proposal. Using Matlab software, we show that we can achieve high levels of channel utilization, enhance reliability, and save more power compared to the performance of the original IEEE 802.15.4 standard.

Big Data Analytics: Security and privacy challenges

The digitalization of our day-to-day activities has resulted in a huge volume of data. This data, called Big Data, is used by many organizations to extract valuable information either to take marketing decisions, track specific behaviors or detect threat attacks. The processing of such data is made possible by using multiple techniques, called Big Data Analytics, which allow getting enormous benefits by dealing with any massive volume of unstructured, structured and semi-structured content that is fast changing and impossible to process using conventional database techniques. However, while Big Data represents an immense opportunity for many industries and decisions makers, it also represents a big risk for many users. This risk arises from the fact that these analytics tools consist of storing, managing and efficiently analyzing varied data gathered from all possible and available sources. The consequence is that people become widely vulnerable to exposure because of combining and exploring specific behavioral data. That is, it is possible to collect more data than it should have which leads to many security and privacy violations. Therefore, research community has to consider these issues by proposing strong protection techniques that enable getting benefits from big data without risking privacy. In this paper, we highlight the benefits of Big Data Analytics and then we review challenges of security and privacy in big data environments. Furthermore, we present some available protection techniques and propose some possible tracks that enable security and privacy in a malicious big data context.

Privacy Preserving Scheme for Location-Based Services

Homomorphic encryption schemes make it possible to perform arithmetic operations, like additions and multiplications, over encrypted values. This capability provides enhanced protection for data and offers new research directions, including blind data processing. Using homomorphic encryption schemes, a Location-Based Service (LBS) can process encrypted inputs to retrieve encrypted location-related information. The retrieved encrypted data can only be decrypted by the user who requested the data. The technology still faces two main challenges: the encountered processing time and the upper limit imposed on the allowed number of operations. However, the protection of users’ privacy achieved through this technology makes it attractive for more research and enhancing. In this paper we use homomorphic encryption schemes to build a fully secure system that allows users to benefit from location-based services while preserving the confidentiality and integrity of their data. Our novel system consists of search circuits that allow an executor (i.e. LBS server) to receive encrypted inputs/requests and then perform a blind search to retrieve encrypted records that match the selection criterion. A querier can send the user’s position and the service type he/she is looking for, in encrypted form, to a server and then the server would respond to the request without any knowledge of the contents of the request and the retrieved records. We further propose a prototype that improves the practicality of our system.

Intrusion Detection System for WSN-Based Intelligent Transportation Systems

The application of Wireless Sensor Networks (WSNs) in Intelligent Transportation Systems (ITSs) has been the topic of extensive research in the last decade. Various aspects of WSNs have been addressed in the context of transportation networks. In particular, the different aspects of security (confidentiality, integrity, and availability) strongly enticed the research devoted to ITSs. However, those efforts concentrated on preventive techniques constituting a first line of defense (like cryptography and authentication), which are effective in inhibiting the diverse malicious attacks. Relatively, little attention has been paid for employing a second line of defense that can detect intrusive behavior after successfully penetrating the first one. The latter line of defense is known as the Intrusion Detection System (IDS). While mature in wired and many types of wireless networks, IDSs are envisaged to have more opportunities in WSNs. In this paper, we study the incorporation of IDSs in WSN-based ITSs. We distinguish the characteristics of ITSs that affect the design of effective security measures and propose a novel IDS based on the WITS architecture (proposed in [1]).

Using ECG as a measure in biometric identification systems

Over the last few years, there has been a number of publications suggesting the use of Electrocardiogram (ECG) as a biometric measure. Motivated by the level of sustainability to attacks the ECG provides, it can be combined in a multi-modal biometric identification system or, when the permanence and collectability issues are not an issue and the false positive margin problem is controlled and not critical, used alone for authentication of subjects. Its primary application can be in health care systems where the ECG is used for health measurements. It does furthermore, better than any other biometrics measures, deliver the proof of subjects being alive as extra information which other biometrics cannot deliver as easily. Nevertheless, the proposed feature extraction methods and experiments have not been published with a corresponding theoretical analysis of the maximum possibility of collision in an infinite domain of subjects and thus, as its current status it is best suited for complementing other metrics for a higher level of accuracy and proof of liveliness.