Parameterized Hash Functions

In this paper we describe a family of highly parameterized hash functions. This parameterization results in great flexibility between performance and security of the algorithm. The three basic functions, HaF-256, HaF-512 and HaF-1024 constitute this hash function family. Lengths of message digests are 256, 512 and 1024 bits respectively. The paper discusses the details of functions structure. The method used to generate function S-box is also described in detail

Energy harvesting towards self-powered iot devices

The internet of things (IoT) manages a large infrastructure of web-enabled smart devices, small devices that use embedded systems, such as processors, sensors, and communication hardware to collect, send, and elaborate on data acquired from their environment. Thus, from a practical point of view, such devices are composed of power-efficient storage, scalable, and lightweight nodes needing power and batteries to operate. From the above reason, it appears clear that energy harvesting plays an important role in increasing the efficiency and lifetime of IoT devices. Moreover, from acquiring energy by the surrounding operational environment, energy harvesting is important to make the IoT device network more sustainable from the environmental point of view. Different state-of-the-art energy harvesters based on mechanical, aeroelastic, wind, solar, radiofrequency, and pyroelectric mechanisms are discussed in this review article. To reduce the power consumption of the batteries, a vital role is played by power management integrated circuits (PMICs), which help to enhance the system's life span. Moreover, PMICs from different manufacturers that provide power management to IoT devices have been discussed in this paper. Furthermore, the energy harvesting networks can expose themselves to prominent security issues putting the secrecy of the system to risk. These possible attacks are also discussed in this review article

ID-Based Key Agreement for WANETs

2013 - 2014The increasing interest about wireless ad hoc networks (WANETs) is due to some key features not owned by traditional networks such as nodes mobility, network self-organization and the ability to rely on infrastructure-less setup. WANETs can be used in many application scenarios such as health care, environmental monitoring, military and many others commercial applications. Unfortunately, the open nature of the communication channel exposes WANETs to a great number of security threats (e.g. jamming, eavesdropping, node replication, unfairness, wormhole, packet injection). The security of WANETs hinges on node authentication, which by mean of Cryptography can be obtained through key distribution mechanisms. Moreover, WANET applications often require the establishment of session keys, that will be used for encryption, message authentication and others cryptographic purposes. In this thesis we present a cryptographic framework for WANETs, named JIKA (Java framework for ID-based key agreement) which simulates a key generation center (KGC) and offers an ID-based key distribution service for signature schemes and key agreement protocols. Moreover, JIKA makes use of elliptic curve cryptography (ECC) which allows fast computations, small key size and short signatures of messages. It includes two new ID-based signature schemes (IBS-1 and IBS-2) which get shorter signatures, an ID-based two-party key agreement protocol (eFG) and two new group key agreement protocols (GKA v1 and GKA v2). GKA protocols are full-contributory and offer implicit key authentication through the ID-based signature schemes described above, at the cost of just two rounds... [edited by Author]XIII n.s

Spatial Statistical Data Fusion on Java-enabled Machines in Ubiquitous Sensor Networks

Wireless Sensor Networks (WSN) consist of small, cheap devices that have a combination of sensing, computing and communication capabilities. They must be able to communicate and process data efficiently using minimum amount of energy and cover an area of interest with the minimum number of sensors. This thesis proposes the use of techniques that were designed for Geostatistics and applies them to WSN field. Kriging and Cokriging interpolation that can be considered as Information Fusion algorithms were tested to prove the feasibility of the methods to increase coverage. To reduce energy consumption, a compression method that models correlations based on variograms was developed. A second challenge is to establish the communication to the external networks and to react to unexpected events. A demonstrator that uses commercial Java-enabled devices was implemented. It is able to perform remote monitoring, send SMS alarms and deploy remote updates

Interference mitigation in wideband radios using spectrum correlation and neural network

Technologies such as cognitive radio and dynamic spectrum access rely on spectrum sensing which provides wireless devices with information about the radio spectrum in the surrounding environment. One of the main challenges in wireless communications is the interference caused by malicious users on the shared spectrum. In this manuscript, an artificial intelligence enabled cognitive radio framework is proposed at system-level as part of a cyclic spectrum intelligence algorithm for interference mitigation in wideband radios. It exploits the cyclostationary feature of signals to differentiate users with different modulation schemes and an artificial neural network as classifier to detect potential malicious users. A dataset consisting of experimental modulated and dynamic signals is recorded by spectrum measurements with an in-house software defined radio testbed and then processed. Cyclostationary features are extracted for each detected signal and fed to a neural network classifier as training and testing data in a complex and dynamic scenario. Results highlight a classification rate of $3c1$ 1 in most of cases, even at low transmission power. A comparison with two previous works with hand-crafted features, which employ an energy detector-based classifier and a naive Bayes-based classifier, respectively, is discussed

Wideband cyclostationary spectrum sensing and characterization for cognitive radios

Motivated by the spectrum scarcity problem, Cognitive Radios (CRs) have been proposed as a solution to opportunistically communicate over unused spectrum licensed to Primary users (PUs). In this context, the unlicensed Secondary users (SUs) sense the spectrum to detect the presence or absence of PUs, and use the unoccupied bands without causing interference to PUs. CRs are equipped with capabilities such as, learning, adaptability, and recongurability, and are spectrum aware. Spectrum awareness comes from spectrum sensing, and it can be performed using different techniques

Developing sustainable business models for institutions’ provision of open educational resources: Learning from OpenLearn users’ motivations and experiences

Universities across the globe have, for some time, been exploring the possibilities for achieving public benefit and generating business and visibility through releasing and sharing open educational resources (OER). Many have written about the need to develop sustainable and profitable business models around the production and release of OER. Downes (2006), for example, has questioned the financial sustainability of OER production at scale. Many of the proposed business models focus on OER’s value in generating revenue and detractors of OER have questioned whether they are in competition with formal education. This paper reports on a study intended to broaden the conversation about OER business models to consider the motivations and experiences of OER users as the basis for making a better informed decision about whether OER and formal learning are competitive or complementary with each other. The study focused on OpenLearn - the Open University’s (OU) web-based platform for OER, which hosts hundreds of online courses and videos and is accessed by over 3,000,000 users a year. A large scale survey and follow-up interviews with OpenLearn users worldwide revealed that university provided OER can offer learners a bridge to formal education, allowing them to try out a subject before registering on a formal course and to build confidence in their abilities as learners. In addition, it was found that using OER during formal paid-for study can improve learners’ performance and self-reliance, leading to increased retention and satisfaction with the learning experience

Open educational resources for all? Comparing user motivations and characteristics across The Open University’s iTunes U channel and OpenLearn platform.

With the rise in access to mobile multimedia devices, educational institutions have exploited the iTunes U platform as an additional channel to provide free educational resources with the aim of profile-raising and breaking down barriers to education. For those prepared to invest in content preparation, it is possible to produce interactive, portable material that can be made available globally. Commentators have questioned both the financial implications for platform-specific content production, and the availability of devices for learners to access it (Osborne, 2012). The Open University (OU) makes its free educational resources available on iTunes U and via its web-based open educational resources (OER) platform, OpenLearn. The OU’s OER on iTunes U reached the 60 million download mark in 2013; its OpenLearn platform boasts 27 million unique visitors since 2006. This paper reports the results of a large-scale study of users of the OU’s iTunes U channel and OpenLearn platform. A survey of several thousand users revealed key differences in demographics between those accessing OER via the web and via iTunes U. In addition, the data allowed comparison between three groups: formal learners, informal learners and educators. The study raises questions about whether university-provided OER meet the needs of users and makes recommendations for how content can be modified to suit their needs. As the publishing of OER becomes core to business, we reflect on reasons why understanding users’ motivations and demographics is vital, allowing for needs-led resource provision and content that is adapted to best achieve learner satisfaction, and to deliver institutions’ social mission

The Key Factors in Physical Activity Type Detection Using Real-Life Data: A Systematic Review

Background: Physical activity (PA) is paramount for human health and well-being. However, there is a lack of information regarding the types of PA and the way they can exert an influence on functional and mental health as well as quality of life. Studies have measured and classified PA type in controlled conditions, but only provided limited insight into the validity of classifiers under real-life conditions. The advantage of utilizing the type dimension and the significance of real-life study designs for PA monitoring brought us to conduct a systematic literature review on PA type detection (PATD) under real-life conditions focused on three main criteria: methods for detecting PA types, using accelerometer data collected by portable devices, and real-life settings.Method: The search of the databases, Web of Science, Scopus, PsycINFO, and PubMed, identified 1,170 publications. After screening of titles, abstracts and full texts using the above selection criteria, 21 publications were included in this review.Results: This review is organized according to the three key elements constituting the PATD process using real-life datasets, including data collection, preprocessing, and PATD methods. Recommendations regarding these key elements are proposed, particularly regarding two important PA classes, i.e., posture and motion activities. Existing studies generally reported high to near-perfect classification accuracies. However, the data collection protocols and performance reporting schemes used varied significantly between studies, hindering a transparent performance comparison across methods.Conclusion: Generally, considerably less studies focused on PA types, compared to other measures of PA assessment, such as PA intensity, and even less focused on real-life settings. To reliably differentiate the basic postures and motion activities in real life, two 3D accelerometers (thigh and hip) sampling at 20 Hz were found to provide the minimal sensor configuration. Decision trees are the most common classifier used in practical applications with real-life data. Despite the significant progress made over the past year in assessing PA in real-life settings, it remains difficult, if not impossible, to compare the performance of the various proposed methods. Thus, there is an urgent need for labeled, fully documented, and openly available reference datasets including a common evaluation framework

Contribution au domaine de la conception d’objets communicants embarqués basse consommation et autonomes en énergie

This report proposes a synthesis of my research and teaching activities. Since 2008, as associate professor at the University of Nice Sophia Antipolis, I did my research into the MCSOC team from the LEAT laboratory. For nearly 15 years, my activity is focused on the design of embedded communicating objects, with a strong emphasis for high level approach allowing, early in the design flow, to model and optimize the performance as well as the consumed energy. Those system-level approaches are more and more relevant over the last few years and become a must-have solution for designing efficient embedded systems. My activity on energy harvesting for autonomous systems brings an original contribution to this domain and has a national and international impact. This document is organized in two parts: the first part is a synthesis of my research and teaching activity, while the second one presents in details my research work, putting in evidence my contributions and innovative aspects. The manuscript ends with a scientific overview as well as some perspectives.Ce manuscrit présente une synthèse de mes travaux de recherche. Depuis septembre 2008, date de ma nomination en tant que Maître de Conférences à l’Université de Nice Sophia Antipolis, j’ai effectué mes travaux de recherche au sein de la thématique MCSOC (Modélisation, Conception Système d’Objets Communicants) du laboratoire LEAT (Université de Nice Sophia Antipolis, UMR CNRS 7248). Depuis maintenant près de 15 ans, mes travaux de recherche s’intéressent au domaine de la conception d’objets communicants embarqués avec une évolution forte vers des approches de haut niveau d’abstraction permettant tôt dans le flot de conception, de modéliser et d’optimiser les performances et la consommation d’énergie. Ces approches de niveau système n’ont cessé de prendre de l’ampleur ces dernières années et s’installent aujourd’hui comme une solution incontournable du domaine de la conception de systèmes embarqués. Mes travaux plus spécifiques sur l’autonomie énergétique de ces systèmes apportent une contribution originale au domaine et ont un rayonnement national et international. Ce document est organisé en deux parties : la première partie propose une synthèse des travaux de recherche et d’enseignement ; la seconde présente de manière détaillée mes travaux de recherche en mettant en avant toutes ses contributions et originalités. Le manuscrit s’achève par un bilan scientifique ainsi que quelques perspectives de recherche