Department of Computer Engineering and Computational Sciences
Permanent URI for this collection
Browse
Browsing Department of Computer Engineering and Computational Sciences by Title
Now showing 1 - 20 of 111
Results Per Page
Sort Options
Item A 3G/WiFi-enabled 6LoWPAN-based U-healthcare system for ubiquitous real-time monitoring and data logging(IEEE Computer Society, 2014) Tabish, Rohan; Ghaleb, Abdulaziz M.; Hussein, Rima; Touati, Farid; Mnaouer, Adel Ben; Khriji, Lazhar; Rasid, Mohd Fadlee A.Ubiquitous healthcare (U-healthcare) systems are expected to offer flexible and resilient high-end technological solutions enabling remote monitoring of patients health status in real-time and provisioning of feedback and remote actions by healthcare providers. In this paper, we present a 6LowPAN based U-healthcare platform that contributes to the realization of the above expectation. The proposed system comprises two sensor nodes sending temperature data and ECG signals to a remote processing unit. These sensors are being assigned an IPv6 address to enable the Internet-of-Things (IoT) functionality. A 6LowPAN-enabled edge router, connected to a PC, is serving as a base station through a serial interface, to collect data from the sensor nodes. Furthermore, a program interfacing through a Serial-Line-Internet-Protocol (SLIP) and running on the PC provides a network interface that receives IPv6 packets from the edge router. The above system is enhanced by having the application save readings from the sensors into a file that can be downloaded by a remote server using a free Cloud service such as UbuntuOne. This enhancement makes the system robust against data loss especially for outdoor healthcare services, where the 3G/4G connectivity may get lost because of signal quality fluctuations. The system provided a proof of concept of successful remote U-healthcare monitoring illustrating the IoT functionality and involving 3G/4G connectivity while being enhanced by a cloud-based backup. © 2014 IEEE.Item A Comparative Study of Post-Quantum Cryptographic Algorithm Implementations for Secure and Efficient Energy Systems Monitoring(Multidisciplinary Digital Publishing Institute (MDPI), 2023-09) Satrya, Gandeva Bayu; Agus, Yosafat Marselino; Mnaouer, Adel BenThe Internet of Things (IoT) has assumed a pivotal role in the advancement of communication technology and in our daily lives. However, an IoT system such as a smart grid with poorly designed topology and weak security protocols might be vulnerable to cybercrimes. Exploits may arise from sensor data interception en route to the intended consumer within an IoT system. The increasing integration of electronic devices interconnected via the internet has galvanized the acceptance of this technology. Nonetheless, as the number of users of this technology surges, there must be an aligned concern to ensure that security measures are diligently enforced within IoT communication systems, such as in smart homes, smart cities, smart factories, smart hospitals, and smart grids. This research addresses security lacunae in the topology and configuration of IoT energy monitoring systems using post-quantum cryptographic techniques. We propose tailored implementations of the Rivest–Shamir–Adleman (RSA), N-th degree Truncated Polynomial Ring Units (NTRU), and a suite of cryptographic primitives based on Module Learning With Rounding (Saber) as post-quantum cryptographic candidate algorithms for IoT devices. These aim to secure publisher–subscriber end-to-end communication in energy system monitoring. Additionally, we offer a comparative analysis of these tailored implementations on low-resource devices, such as the Raspberry Pi, during data transmission using the Message Queuing Telemetry Transport (MQTT) protocol. Results indicate that the customized implementation of NTRU outperforms both SABER and RSA in terms of CPU and memory usage, while Light SABER emerges as the front-runner when considering encryption and decryption delays. © 2023 by the authors.Item A survey of blockchain-based solutions for IoTs, VANETs, and FANETs(IGI Global, 2021-06-11) Abdelhafidh, Maroua; Charef, Nadia; Mnaouer, Adel Ben; Chaari, LamiaRecently, the internet of things (IoT) has gained popularity as an enabling technology for wireless connectivity of mobile and/or stationary devices providing useful services for the general public in a collaborative manner. Mobile ad-hoc networks (MANETs) are regarded as a legacy enabling technology for various IoT applications. Vehicular ad-hoc networks (VANETs) and flying ad-hoc networks (FANETs) are specific extensions of MANETs that are drivers of IoT applications. However, IoT is prone to diverse attacks, being branded as the weakest link in the networking chain requiring effective solutions for achieving an acceptable level of security. Blockchain (BC) technology has been identified as an efficient method to remedy IoT security concerns. Therefore, this chapter classifies the attacks targeting IoT, VANETs, and FANETs systems based on their vulnerabilities. This chapter explores a selection of blockchain-based solutions for securing IoT, VANETs, and FANETs and presents open research directions compiled out of the presented solutions as useful guidelines for the readers. © 2021, IGI Global.Item A survey of blockchain-based solutions for IoTs, VANETs, and FANETs(IGI Global, 2022-07-08) Abdelhafidh, Maroua; Charef, Nadia; Mnaouer, Adel Ben; Chaari, LamiaRecently, the internet of things (IoT) has gained popularity as an enabling technology for wireless connectivity of mobile and/or stationary devices providing useful services for the general public in a collaborative manner. Mobile ad-hoc networks (MANETs) are regarded as a legacy enabling technology for various IoT applications. Vehicular ad-hoc networks (VANETs) and flying ad-hoc networks (FANETs) are specific extensions of MANETs that are drivers of IoT applications. However, IoT is prone to diverse attacks, being branded as the weakest link in the networking chain requiring effective solutions for achieving an acceptable level of security. Blockchain (BC) technology has been identified as an efficient method to remedy IoT security concerns. Therefore, this chapter classifies the attacks targeting IoT, VANETs, and FANETs systems based on their vulnerabilities. This chapter explores a selection of blockchain-based solutions for securing IoT, VANETs, and FANETs and presents open research directions compiled out of the presented solutions as useful guidelines for the readers. © 2023, IGI Global. All rights reserved.Item Advanced key distribuation center algorithm (AKDC)(2010) Abuazab, Hussam Hussein; Dahmane, Adel Omar; Hamam, HabibItem AI-based Energy Model for Adaptive Duty Cycle Scheduling in Wireless Networks(Institute of Electrical and Electronics Engineers Inc., 2021) Charef, Nadia; Mnaouer, Adel Ben; Bouachir, OunsThe vast distribution of low-power devices in IoT applications requires robust communication technologies that ensure high-performance level in terms of QoS, light-weight computation, and security. Advanced wireless technologies (i.e. 5G and 6G) are playing an increasing role in facilitating the deployment of IoT applications. To prolong the network lifetime, energy harvesting is an essential technology in wireless networks. Nevertheless, maintaining energy sustainability is difficult when considering high QoS requirements in IoT. Therefore, an energy management technique that ensures energy efficiency and meets QoS is needed. Energy efficiency in duty cycling solutions needs novel energy management techniques to address these challenges and achieve a trade-off between energy efficiency and delay. Predictive models (i.e., based on AI and ML techniques) represent useful tools that encapsulate the stochastic nature of harvested energy in duty cycle scheduling. The conventional predictive model relies on environmental parameters to estimate the harvested energy. Instead, Artificial Intelligence (AI) allows for recursive prediction models that rely on past behavior of harvested and consumed energy. This is useful to achieve better precision in energy estimation and extend the limit beyond predictive models directed solely for energy sources that exhibit periodic behavior. In this paper, we explore the usage of a ML model to enhance the performance of duty cycle scheduling. The aim is to improve the QoS performance of the proposed solution. To assess the performance of the proposed model, it was simulated using the INET framework of the OMNet++ simulation environment. The results are compared to an enhanced IEEE 802.15.4 MAC protocol from the literature. The results of the comparative study show clear superiority of the proposed AI-based protocol that testified to better use of energy estimation for better management of the duty cycling at the MAC sublayer. © 2021 IEEE.Item Artificial intelligence implication on energy sustainability in Internet of Things: A survey(Elsevier Ltd, 2023-03) Charef, Nadia; Ben Mnaouer, Adel; Aloqaily, Moayad; Bouachir, Ouns; Guizani, MohsenItem An Autonomous Multi-Variable Outdoor Air Quality Mapping Wireless Sensors IoT Node for Qatar(Institute of Electrical and Electronics Engineers Inc., 2020-06) Tariq, Hasan; Abdaoui, Abderrazak; Touati, Farid; Al-Hitmi, Mohammed Abdulla E; Crescini, Damiano; Mnaouer, Adel BenIn all outdoor long haul air quality monitoring and mapping applications, sensing accuracy, the sustainability of telemetry, and resilience in node systems and operation are major challenges. The severity of these challenges varies depending on the moderateness and harshness of the climate of observation. In this work, an autonomous environmentally powered, sensors self-diagnostic/calibration, and context-aware IoT-based telemetry for multi-variable sensing node is being proposed. In this node, photo-voltaic and piezoelectric energy harvesters contributed to self-calibration and sustainable measurement of temperature (in °C), humidity (in %), pressure (in bar), geo-position (in NMEA format), volatile organic compounds-VOC (in ppm), particulate matter PM (in ppm), ozone (in Dobson Unit), Carbon mono-oxide (in ppm), Nitrogen dioxide (in ppm), and Sulphur dioxide (in ppm). Results have shown that the proposed system worked autonomously for days and optimized the real-time air quality mapping for the chosen geo-spatial cluster, i.e. Qatar University. © 2020 IEEE.Item An autoregressive time delay neural network for speech steganalysis(Institute of Electrical and Electronics Engineers Inc., 2012) Rekik, Siwar; Selouani, Sid-Ahmed; Guerchi, Driss; Hamam, HabibHiding a secret message in speech signal, called steganography, is used to provide secure communication. The detection of hidden information in the transmitted message called steganalysis. The purpose of steganalysis is to identify the presence of embedded information, and does not actually attempt to extract or decode the hidden data. An automated method is required for detecting the existence of hidden message, since the huge amount of channeled information. However, the development and evaluation of steganalysis algorithms is a challenging task. In this paper we advocate a new steganalysis technique to classify a speech as having hidden information or not, using a powerful and sophisticated classifier called Autoregressive Time Delay Neural Network (AR-TDNN). The originality of this AR-TDNN is its quite ability to detect secret messages hidden with different steganographic algorithms, although the variation of detection rate depends on the particular hiding techniques and amount of hidden information. © 2012 IEEE.Item Blockchain-Based Key Management Solution for Clustered Flying Ad-Hoc Network(Institute of Electrical and Electronics Engineers Inc., 2023) Abdelhafidh, Maroua; Zaghdoud, Nesrine; Charef, Nadia; Ben Mnaouer, AdelItem Cognitive internet of things for smart water pipeline monitoring system(Institute of Electrical and Electronics Engineers Inc., 2018-07-02) Abdelhafidh, Maroua; Mohamed, Fourati; Fourati, Lamia Chaari; Mnaouer, Adel Ben; Mokhtar, Zid; Permission to reuse the abstract has been secured from the Publisher.Water Pipeline Monitoring System (WPMS) is extremely important considering the several pipeline damages and the various hydraulic failures that cause a critical water loss. In this context, Cognitive Water Distribution System integrates Internet of Things (IoT) technology, based on smart sensors, actuators and connected objects, with a reliable Big Data processing for smart and robust Structural Health Monitoring (SHM) of pipelines. In this paper, we propose a cognitive IoT-based architecture where we used Apache Spark framework to maintain a real time processing of the large amount of collected data. This efficient processing of measured data and its correspondent calculated values simplify the transient simulations and leak detection and make it faster and easier. © 2018 IEEE.Item A comparative analysis of BLE and 6LoWPAN for U-HealthCare applications(Institute of Electrical and Electronics Engineers Inc., 2013) Tabish, Rohan; Mnaouer, Adel Ben; Touati, Farid; Ghaleb, Abdulaziz M.For decades, there exist a variety of low-power wireless technologies deployed for healthcare applications such as Zigbee/IEEE802.15.4, Bluetooth, ANT, NFC, IrDA. However, the recently announced Bluetooth Low Energy (BLE) technology claims to offer many new compelling features and is expected to get wide adoption by many mobile manufacturers around the world and hence be included in daily life mobile devices. Therefore, it is important to provide future adopters with a thorough yet insightful evaluation of this technology as contrasted to competing ones in the market today. In this paper, we present such evaluation from an experimental point of view as well as referring to technical specifications from manufacturers. The discussion is geared toward assessing the extent to which theses technologies can meet the stringent requirements for u-healthcare applicability. BLE and 6LoWPAN showed greater potentials for such applicability in terms of power demand, bit rate and latency. Nevertheless, BLE was found to be most robust to obstacles and was operable using single coin cell. © 2013 IEEE.Item Cyber Security Strategies While Safeguarding Information Systems in Public/Private Sectors(Springer Science and Business Media Deutschland GmbH, 2022) Al Mehairi, Alya; Zgheib, Rita; Abdellatif, Tamer Mohamed; Conchon, EmmanuelMany private and public organizations in the UAE and around the world are facing challenges in protecting their information and systems from external cyber-attacks due to the increase in the usage of computer networks within worldwide businesses. The objective of this research study is to explore the strategies that are implemented by the public and private sectors in the UAE to safeguard their data and information systems from cyber-attacks. The findings of the study indicated that public organizations in the UAE do have effective strategies in place to safeguard their information and systems against any cyber-attacks. These strategies include providing adequate training to their employees to create awareness among them and developing robust cyber security strategies in line with the UAE National Cyber Security strategy framework. Public and some private organizations are vigilant in assessing, identifying, and mitigating cyber security risks and threats through well-designed organizational strategies. The research also concludes that protecting the information system can reduce cyber threats and can lead to improved business practices. The findings of this study will lay the foundations for other private and public sectors to use them in their organizational practices, which will help them to decrease the data breaches, and protect their company and customers’ confidential data, thereby reducing the cost and risk of cyber-attacks. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.Item A Data-based Guiding Framework for Digital Transformation(CEUR-WS, 2021) Maamar, Zakaria; Cheikhrouhou, Saoussen; Elnaffar, SaidThis paper presents a framework for guiding organizations initiate and sustain digital transformation initiatives. Digital transformation is a long-term journey that an organization embarks on when it decides to question its practices in light of management, operation, and technology challenges. The guiding framework stresses out the importance of data in any digital transformation initiative by suggesting 4 stages referred to as collection, processing, storage, and dissemination. Because digital transformation could impact different areas of an organization for instance, business processes and business models, each stage suggests techniques to expose data. 2 case studies are adopted in the paper to illustrate how the guiding framework is put into action. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).Item Data-driven stability of stochastic mean-field type games via noncooperative neural network adversarial training(John Wiley and Sons Inc, 2024-03) Barreiro-Gomez, Julian; Choutri, Salah E.Item Delay Analysis of Routing Protocols for WSN(Institute of Electrical and Electronics Engineers Inc., 2023) Bensaid, Rahil; Mnaouer, Adel Ben; Boujemaa, HatemItem Design and Implementation of Cadastral Geo-spatial IoT Network Gateway Analyzer for Urban Scale Infrastructure Health Monitoring(Institute of Electrical and Electronics Engineers Inc., 2020-01) Tariq, Hasan; Abdaoui, Abderrazak; Touati, Farid; Al-Hitmi, Mohammed Abdulla E; Crescini, Damiano; Mnaouer, Adel BenUrban and global scale health monitoring systems have gained significance in digital ecosystems. Every stakeholder is striving for efficiency through performance analysis of digital infrastructure health monitoring (IHM) solutions. In this work, a geospatial network analyzer (GNA) is designed and implemented in python using the synergic strengths of Plotly, NetworkX, Scipy, Numpy, MatplotLib, Network2tikz, Pysocks, and PyPing. The GNA uses as a case study a utility computing model (UCM) to make structural health monitoring (SHM) that is based on analysis of geographical area network (GAN). A geo-distributed SHM deployment is assessed from a network performance perspective and verified from geo-spatial packet processing in GNA. The results have shown that this work can lead to standardizing the future of global-scale IoT networks analytics. © 2020 IEEE.Item Design and implementation of information centered protocol for long haul SHM monitoring(Institute of Electrical and Electronics Engineers Inc., 2019) Tariq, Hasan; Touati, Farid; Al-Hitmi, Mohammed Abdulla E.; Crescini, Damiano; Mnaouer, Adel BenIn structural health monitoring systems (SHM), robust data transmission is the fundamental constraint. In this work, an information centered protocol is being proposed for multi-sensor and multi-variable communication channels in (SHM). The core objective is communication traffic optimization, data streams compression, bottleneck compensation for seamless information system. A novel SHM hierarchical information model has been designed and implemented using addressing taxonomy and domain definitions accumulated with data segments, beacons and flags-handshaking. On both ends of an SHM channel, a SQLite based encoding and decoding preprocessor is implemented, which requires the use of serial protocols such as CANopen, UART, 12C and SPI. Results have shown that the proposed system optimizes traffic monitoring in handling critical situations of dynamic baud rate switching. © 2019 IEEE.Item Design and Implementation of Multi-Protocol Data Networks Interface Detector in Heterogeneous IoTs(Institute of Electrical and Electronics Engineers Inc., 2020-02) Tariq, Hasan; Abdaoui, Abderrazak; Touati, Farid; Al-Hitmi, Mohammed Abdulla E; Crescini, Damiano; Manouer, Adel BenIn Internet of Everything (IoE) or heterogeneous IoTs, there exist a plethora of protocols and inter-connected Internet of Things. For every network protocol, the complexity of communication and wiring at the physical interface becomes more and more challenging. In this work, an automated interface detector (or gateway) is proposed using a novel port, that scans the physical layer parameters, interpolates with Electronic Industry Association/Telecommunication Industry Association (EIA/TIA) standards specification parameters and compares packet format initiates communication. In this approach, line impedance, voltage, current, SNR, power, and network capacity are used as the coefficients of merit for physical layer detection by interpolation and averaging methods. Standard packet architectures are the key parameters for communication initiation and network fastening at both ends of the data line. The serial protocols such as CANopen, Ethernet, UART, I2C, and SPI are tested and verified. Results have shown that the proposed system can detect any physical layer interface and initiate a data network regardless of connector pinouts and interface wiring complexities. The implementation results exhibit a fertile resource for redundancy handling in-line parameters of data networks. © 2020 IEEE.Item Design and implementation of programmable multi-parametric 4-degrees of freedom seismic waves ground motion simulation IoT platform(Institute of Electrical and Electronics Engineers Inc., 2019) Tariq, Hasan; Touati, Farid; Al-Hitmi, Mohammed Abdulla E.; Crescini, Damiano; Mnaouer, Adel BenThe early warning and disaster management agencies spend billions of dollars to counter and cater earthquakes but it has always been unique accident. In this work, a programmable four degrees of freedom electromechanical seismic wave events simulation platform design is being proposed to study and experiment seismic waves and earthquakes realization in form of ground motions. The platform can be programmed and interfaced through an IoT cloud-based Web application. The rig has been tested in the range of frequencies of extreme seismic waves from 0.1Hz to 178Hz and terrestrial inclinations from -5.000° to 5.000°, which is key contribution of this work. This would be an enabler for a variety of applications such as training self-balancing and calibrating seismic resistant designs and structures in addition to studying and testing seismic detection devices. Nevertheless, it serves as an adequate training colossus for machine learning algorithms and event management expert systems. © 2019 IEEE.