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Multicontroller software-defined networks have been widely adopted to enable management of large-scale networks. However, they are vulnerable to several attacks including false data injection, which creates topology inconsistency among controllers. To deal with this issue, we propose BMC-SDN, a security architecture that integrates blockchain and multicontroller SDN and divides the network into several domains. Each SDN domain is managed by one master controller that communicates through blockchain with the masters of the other domains. The master controller creates blocks of network flow updates, and its redundant controllers validate the new block based on a proposed reputation mechanism. The reputation mechanism rates the controllers, i.e., block creator and voters, after each voting operation using constant and combined adaptive fading reputation strategies. The evaluation results demonstrate a fast and optimal detection of fraudulent flow rule injection.
Abdelouahid Derhab; Mohamed Guerroumi; Mohamed Belaoued; Omar Cheikhrouhou. BMC-SDN: Blockchain-Based Multicontroller Architecture for Secure Software-Defined Networks. Wireless Communications and Mobile Computing 2021, 2021, 1 -12.
AMA StyleAbdelouahid Derhab, Mohamed Guerroumi, Mohamed Belaoued, Omar Cheikhrouhou. BMC-SDN: Blockchain-Based Multicontroller Architecture for Secure Software-Defined Networks. Wireless Communications and Mobile Computing. 2021; 2021 ():1-12.
Chicago/Turabian StyleAbdelouahid Derhab; Mohamed Guerroumi; Mohamed Belaoued; Omar Cheikhrouhou. 2021. "BMC-SDN: Blockchain-Based Multicontroller Architecture for Secure Software-Defined Networks." Wireless Communications and Mobile Computing 2021, no. : 1-12.
The shortage and imbalance of parking spaces have become serious problems in recent years on the roadside. Drivers may park incorrectly, which may take more parking space and disturb other drivers. To mitigate these problems, real-time parking monitoring with a detection system, is very indispensable. In this paper, we propose a classification system of images associated with the parking spaces for vehicles on a roadside based on the convolutional neuron networks (CNN). The image is supposed to be captured by a camera or other visual devices installed on the roadside and sent to a central computer for processing. The treatment is followed by a classification based on DL (deep learning) to determine the occupation of the parking spaces. The proposed classifier model uses fewer calculation parameters that involved a faster model by applying the principle of dilation. The proposed model has been evaluated and compared with the previous models using PKlot dataset, a set of well-known images publicly available. The evaluation results show the reliability of our proposal comparing with the previous works.
Khalfi Ali; Guerroumi Mohamed. Roadside Parking Spaces Image Classification Using Deep Learning. Inventive Computation and Information Technologies 2021, 323 -333.
AMA StyleKhalfi Ali, Guerroumi Mohamed. Roadside Parking Spaces Image Classification Using Deep Learning. Inventive Computation and Information Technologies. 2021; ():323-333.
Chicago/Turabian StyleKhalfi Ali; Guerroumi Mohamed. 2021. "Roadside Parking Spaces Image Classification Using Deep Learning." Inventive Computation and Information Technologies , no. : 323-333.
Security analysts have shown that it is possible to compromise the mobile two-factor authentication applications that employ SMS-based authentication. In this paper, we consider that offloading mobile applications to the cloud, which is resource-rich and provides a more secure environment, represents a good solution when energy limitation and security constraints are raised. To this end, we propose an offloading architecture for the two-factor mutual authentication applications, and a novel two-factor mutual authentication scheme based on a novel mechanism, named virtual smart card. We also propose a decision-making process to offload the authentication application and its virtual smart card, based on three conditions: security, mobile device’s residual energy, and energy cost. We analytically derive from the energy cost formula, the lower-bound on the mobile application running time to perform offloading. We analyze and verify the security properties of the proposed architecture, and provide evaluation results of the two-factor mutual authentication protocol and the offloading decision-making process.
Abdelouahid Derhab; Mohamed Belaoued; Mohamed Guerroumi; Farrukh Aslam Khan. Two-Factor Mutual Authentication Offloading for Mobile Cloud Computing. IEEE Access 2020, 8, 28956 -28969.
AMA StyleAbdelouahid Derhab, Mohamed Belaoued, Mohamed Guerroumi, Farrukh Aslam Khan. Two-Factor Mutual Authentication Offloading for Mobile Cloud Computing. IEEE Access. 2020; 8 (99):28956-28969.
Chicago/Turabian StyleAbdelouahid Derhab; Mohamed Belaoued; Mohamed Guerroumi; Farrukh Aslam Khan. 2020. "Two-Factor Mutual Authentication Offloading for Mobile Cloud Computing." IEEE Access 8, no. 99: 28956-28969.
Today, Vehicular Ad Hoc Network (VANET) is one of the most important smart city system components. VANETs are distinguished by their high mobility, high information storage capacity, available energy, and the environment governed by road infrastructure but there are still many challenges to be faced to achieve good communication between vehicles. In the traditional ad hoc mobile networks, these difficulties have often been overcome by a clustered topology. The clustering in VANETs can reduce the communication problems and makes the network appear smaller and more stable according to the view of each vehicle. In this work, we propose a VANET clustering solution called “QoSCluster”, which aims to maintain the cluster structure while respecting the quality of service requirements as the network involves. We simulate our protocol using the Veins platform, the OMNET simulator, and the realistic mobility model SUMO.
Soumia Bellaouar; Mohamed Guerroumi; Samira Moussaoui. QoS Based Clustering for Vehicular Networks in Smart Cities. Communications in Computer and Information Science 2019, 67 -79.
AMA StyleSoumia Bellaouar, Mohamed Guerroumi, Samira Moussaoui. QoS Based Clustering for Vehicular Networks in Smart Cities. Communications in Computer and Information Science. 2019; ():67-79.
Chicago/Turabian StyleSoumia Bellaouar; Mohamed Guerroumi; Samira Moussaoui. 2019. "QoS Based Clustering for Vehicular Networks in Smart Cities." Communications in Computer and Information Science , no. : 67-79.
Intrusion detection systems are one of the security tools widely deployed in network architectures in order to monitor, detect and eventually respond to any suspicious activity in the network. However, the constantly growing complexity of networks and the virulence of new attacks require more adaptive approaches for optimal responses. In this work, we propose a semi-supervised approach for network anomaly detection inspired from the biological negative selection process. Based on a reduced dataset with a filter/ranking feature selection technique, our algorithm, namely negative selection for network anomaly detection (NSNAD), generates a set of detectors and uses them to classify events as anomaly. Otherwise, they are matched against an Artificial Human Leukocyte Antigen in order to be classified as normal. The accuracy and the computational time of NSNAD are tested under three intrusion detection datasets: NSL-KDD, Kyoto2006+ and UNSW-NB15. We compare the performance of NSNAD against a fully supervised algorithm (Naïve Bayes), an unsupervised clustering algorithm (K-means) and a semi-supervised algorithm (One-class SVM) with respect to multiple accuracy metrics. We also compare the time incurred by each algorithm in training and classification stages.
Naila Belhadj Aissa; Mohamed Guerroumi; Abdelouahid Derhab. NSNAD: negative selection-based network anomaly detection approach with relevant feature subset. Neural Computing and Applications 2019, 32, 3475 -3501.
AMA StyleNaila Belhadj Aissa, Mohamed Guerroumi, Abdelouahid Derhab. NSNAD: negative selection-based network anomaly detection approach with relevant feature subset. Neural Computing and Applications. 2019; 32 (8):3475-3501.
Chicago/Turabian StyleNaila Belhadj Aissa; Mohamed Guerroumi; Abdelouahid Derhab. 2019. "NSNAD: negative selection-based network anomaly detection approach with relevant feature subset." Neural Computing and Applications 32, no. 8: 3475-3501.
The industrial control systems are facing an increasing number of sophisticated cyber attacks that can have very dangerous consequences on humans and their environments. In order to deal with these issues, novel technologies and approaches should be adopted. In this paper, we focus on the security of commands in industrial IoT against forged commands and misrouting of commands. To this end, we propose a security architecture that integrates the Blockchain and the Software-defined network (SDN) technologies. The proposed security architecture is composed of: (a) an intrusion detection system, namely RSL-KNN, which combines the Random Subspace Learning (RSL) and K-Nearest Neighbor (KNN) to defend against the forged commands, which target the industrial control process, and (b) a Blockchain-based Integrity Checking System (BICS), which can prevent the misrouting attack, which tampers with the OpenFlow rules of the SDN-enabled industrial IoT systems. We test the proposed security solution on an Industrial Control System Cyber attack Dataset and on an experimental platform combining software-defined networking and blockchain technologies. The evaluation results demonstrate the effectiveness and efficiency of the proposed security solution.
Abdelouahid Derhab; Mohamed Guerroumi; Abdu Gumaei; Leandros Maglaras; Mohamed Amine Ferrag; Mithun Mukherjee; Farrukh Aslam Khan. Blockchain and Random Subspace Learning-Based IDS for SDN-Enabled Industrial IoT Security. Sensors 2019, 19, 3119 .
AMA StyleAbdelouahid Derhab, Mohamed Guerroumi, Abdu Gumaei, Leandros Maglaras, Mohamed Amine Ferrag, Mithun Mukherjee, Farrukh Aslam Khan. Blockchain and Random Subspace Learning-Based IDS for SDN-Enabled Industrial IoT Security. Sensors. 2019; 19 (14):3119.
Chicago/Turabian StyleAbdelouahid Derhab; Mohamed Guerroumi; Abdu Gumaei; Leandros Maglaras; Mohamed Amine Ferrag; Mithun Mukherjee; Farrukh Aslam Khan. 2019. "Blockchain and Random Subspace Learning-Based IDS for SDN-Enabled Industrial IoT Security." Sensors 19, no. 14: 3119.
Smart cities are increasingly playing a fundamental role in managing the city’s asset. Smart transportation is an important building block of a smart city as it can efficiently resolve many issues related to the traffic on the road. Vehicular ad hoc networks (VANETs) in smart cities may ensure wide inter-vehicle communication and disseminate data and safety-related information. VANETs have their specific characteristics such as long lifetime battery energy, high mobility, and large storage capabilities. In certain circumstances, VANETs may not ensure timely detection of road events and connectivity between vehicles due to their low density, high mobility, or low deployment of roadside unit (RSU) infrastructure. Wireless sensor networks (WSNs) are equipped with low processing and low storage capabilities but they ensure high detection of events. To overcome VANETs limitations, and as VANET and WSN have complementary characteristics, the combination of VANET and wireless sensor network (WSN) technologies into one hybrid architecture enables to identify new aspects and fields of intelligent transportation systems and may offer new services for the smart cities. In this kind of hybrid network, sensor nodes have small size and can be deployed densely inside the road to monitor traffic, roads status, and weather conditions. This chapter describes the hybrid vehicular sensor networks and discusses their deployed applications, communication paradigms, challenges, and existing architectural solutions. Moreover, a heterogeneous VANET-WSN architecture is proposed and open issues and future directions are discussed to help stimulating future studies in this emerging research field.
Soumia Bellaouar; Mohamed Guerroumi; Abdelouahid Derhab; Samira Moussaoui. Towards Heterogeneous Architectures of Hybrid Vehicular Sensor Networks for Smart Cities. Computer Communications and Networks 2018, 51 -70.
AMA StyleSoumia Bellaouar, Mohamed Guerroumi, Abdelouahid Derhab, Samira Moussaoui. Towards Heterogeneous Architectures of Hybrid Vehicular Sensor Networks for Smart Cities. Computer Communications and Networks. 2018; ():51-70.
Chicago/Turabian StyleSoumia Bellaouar; Mohamed Guerroumi; Abdelouahid Derhab; Samira Moussaoui. 2018. "Towards Heterogeneous Architectures of Hybrid Vehicular Sensor Networks for Smart Cities." Computer Communications and Networks , no. : 51-70.
Wireless sensor networks (WSNs) are often used for monitoring environmental conditions. One of the most important tasks in a WSN is to gather sensed data for the users to utilize the network with adequate flexibility. In this process, it is also very important to employ energy-efficient communication protocols since sensor nodes are usually battery-powered and hence their lifetimes are relatively short. Considering these practical aspects of WSN deployment for various types of application scenarios, in this paper, we propose a data query dissemination scheme and data gathering solution. By considering energy conservation and latency, we provide parameterized query which can be adapted according to the user’s profile to collect the required readings from sensor nodes. Simulation results prove that the proposed protocol is more energy-efficient compared to the other alternatives of the same kind.
Mohamed Guerroumi; Al-Sakib Khan Pathan. Hybrid data dissemination protocol (HDDP) for wireless sensor networks. Wireless Networks 2016, 24, 1739 -1754.
AMA StyleMohamed Guerroumi, Al-Sakib Khan Pathan. Hybrid data dissemination protocol (HDDP) for wireless sensor networks. Wireless Networks. 2016; 24 (5):1739-1754.
Chicago/Turabian StyleMohamed Guerroumi; Al-Sakib Khan Pathan. 2016. "Hybrid data dissemination protocol (HDDP) for wireless sensor networks." Wireless Networks 24, no. 5: 1739-1754.
Local vehicle density estimation is an integral part of various applications of Vehicular Ad-hoc Networks (VANETs) such as congestion control and congestion traffic estimation. Currently, many applications use beacons to estimate this density. However, many studies show that the reception rate of these beacons can significantly drop at short distances due to a broadcast storm problem in high-density situations. Therefore, the local vehicle density estimation helps VANETs' applications in giving an estimate of the number of neighbors in their communication range where a vehicle could send and receive correctly packets. Indeed, an accuracy local density estimation considerably enhances the performance of these applications and makes them adaptable to different road scenarios. Our aim in this work is to extend more the local density to be segmented and within the maximum transmission range. This potential gives VANETs' application the ability to estimate at different ranges depending on their requirements. To this goal, this paper proposes a segment-based approach that ensures high accuracy with low overhead over the maximum vehicles transmission range. Performance results show that the proposed strategy reaches a mean error ratio of approximately 3% with limited overhead over 1000m of range.
Noureddine Haouari; Samira Moussaoui; Mohamed Guerroumi; Sidi Mohammed Senouci. Local density estimation for VANETs. 2016 Global Information Infrastructure and Networking Symposium (GIIS) 2016, 1 -6.
AMA StyleNoureddine Haouari, Samira Moussaoui, Mohamed Guerroumi, Sidi Mohammed Senouci. Local density estimation for VANETs. 2016 Global Information Infrastructure and Networking Symposium (GIIS). 2016; ():1-6.
Chicago/Turabian StyleNoureddine Haouari; Samira Moussaoui; Mohamed Guerroumi; Sidi Mohammed Senouci. 2016. "Local density estimation for VANETs." 2016 Global Information Infrastructure and Networking Symposium (GIIS) , no. : 1-6.
Medium Access Control (MAC) protocols must perform the functionality required by the application while utilizing the limited resources available on sensor nodes. Limited energy resources place strict limits on the operations that a sensor node may accomplish and differentiate sensor networks from other networks. Application and protocol designers must utilize the hardware resources of the sensor nodes judiciously to conserve energy and prolong the network lifetime. Especially, when the sensors network becomes accessible from internet, where the end users can monitor, configure and send special requests to the sensors nodes. In this paper we present a new solution to improve collision avoidance and optimize the energy consumption. The simulation results show that the life time of sensor node has been improved.
Mohamed Guerroumi; Nadjib Badache; Samira Moussaoui. MAC Protocol with Low Energy Consumption in Wireless Sensors Network. 2010 Second International Conference on Advances in Future Internet 2010, 31 -36.
AMA StyleMohamed Guerroumi, Nadjib Badache, Samira Moussaoui. MAC Protocol with Low Energy Consumption in Wireless Sensors Network. 2010 Second International Conference on Advances in Future Internet. 2010; ():31-36.
Chicago/Turabian StyleMohamed Guerroumi; Nadjib Badache; Samira Moussaoui. 2010. "MAC Protocol with Low Energy Consumption in Wireless Sensors Network." 2010 Second International Conference on Advances in Future Internet , no. : 31-36.
Data replication is suitable to improve the response time, the global traffic, and the sharing of data since even in the case of disconnection of a server. The nodes can continue to have access to replicas of data. On an Ad hoc mobile network, the frequent partition of the network and the lack of fixed infrastructures complicate the data access and the sharing task. In this paper, we propose a method of data replication in a mobile ad hoc network. The method is composed of two main phases. The first phase aims at creating replicas from new data in the network and at realizing the first distribution of these replicas. The second phase is devoted to the redistribution of replicas in order to overcome the impact of dynamic changes of topology and to satisfy the evolution of users’ needs.
Samira Moussaoui; Mohamed. Guerroumi; Nadjib Badache. Data Replication in Mobile Ad Hoc Networks. Computer Vision 2006, 4325, 685 -697.
AMA StyleSamira Moussaoui, Mohamed. Guerroumi, Nadjib Badache. Data Replication in Mobile Ad Hoc Networks. Computer Vision. 2006; 4325 ():685-697.
Chicago/Turabian StyleSamira Moussaoui; Mohamed. Guerroumi; Nadjib Badache. 2006. "Data Replication in Mobile Ad Hoc Networks." Computer Vision 4325, no. : 685-697.