International Journal Papers
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Item Privacy-preserving remote deep-learning-based inference under constrained client-side environment(Springer, 2023) Boulemtafes, Amine; Derhab, Abdelouahid; Ait Ali Braham, Nassim; Challal , YacineRemote deep learning paradigm raises important privacy concerns related to clients sensitive data and deep learning models. However, dealing with such concerns may come at the expense of more client-side overhead, which does not fit applications relying on constrained environments. In this paper, we propose a privacy-preserving solution for deep-learning-based inference, which ensures effectiveness and privacy, while meeting efficiency requirements of constrained client-side environments. The solution adopts the non-colluding two-server architecture, which prevents accuracy loss as it avoids using approximation of activation functions, and copes with constrained client-side due to low overhead cost. The solution also ensures privacy by leveraging two reversible perturbation techniques in combination with paillier homomorphic encryption scheme. Client-side overhead evaluation compared to the conventional homomorphic encryption approach, achieves up to more than two thousands times improvement in terms of execution time, and up to more than thirty times improvement in terms of the transmitted data size.Item Privacy-preserving deep learning for pervasive health monitoring: a study of environment requirements and existing solutions adequacy(Elsevier, 2022-03) Boulemtafes, Amine; Derhab, Abdelouahid; Challal , YacineIn recent years, deep learning in healthcare applications has attracted considerable attention from research community. They are deployed on powerful cloud infrastructures to process big health data. However, privacy issue arises when sensitive data are offloaded to the remote cloud. In this paper, we focus on pervasive health monitoring applications that allow anywhere and anytime monitoring of patients, such as heart diseases diagnosis, sleep apnea detection, and more recently, early detection of Covid-19. As pervasive health monitoring applications generally operate on constrained client-side environment, it is important to take into consideration these constraints when designing privacy-preserving solutions. This paper aims therefore to review the adequacy of existing privacy-preserving solutions for deep learning in pervasive health monitoring environment. To this end, we identify the privacy-preserving learning scenarios and their corresponding tasks and requirements. Furthermore, we define the evaluation criteria of the reviewed solutions, we discuss them, and highlight open issues for future research.Item PRIviLY: Private Remote Inference over fulLY connected deep networks for pervasive health monitoring with constrained client-side(Elsevier, 2023-09) Boulemtafes, Amine; Derhab, Abdelouahid; Challal, YacineRemote deep learning paradigm enables to better leverage the power of deep neural networks in pervasive health monitoring (PHM) applications, especially by addressing the constrained client-side environment. However, remote deep learning in the context of PHM requires to ensure three properties: (1) meet the high accuracy requirement of the healthcare domain, (2) satisfy the client-side constraints, and (3) cope with the privacy requirements related to the high sensitivity of health data. Different privacy-preserving solutions for remote deep learning exit in the literature but many of them fail to fully address the PHM requirements especially with respect to constrained client-side environments. To that end, we propose PRIviLY, a novel privacy-preserving remote inference solution, designed specifically for the popular Fully Connected Deep Networks (FCDNs). PRIviLY avoids the use of encryption for privacy preservation of sensitive information, in order to fully prevent accuracy loss, and to alleviate the server-side hardware requirements. Besides, PRIviLY adopts a non-colluding two-server architecture, and leverages the linear computations of FCDNs along with reversible random perturbation and permutation techniques in order to preserve privacy of sensitive information, while meeting low overhead requirement of constrained client-sides. At the cloud server, efficiency evaluation shows that PRIviLY achieves an improvement ratio of 4 to more than 15 times for communication, and a minimum improvement ratio of 135 times for computation overhead. At the intermediate server, the minimum improvement ratio is at least more than 10,900 for computation, while for communication, the improvement ratio varies from 5 to more than 21 times. As for the client-side, PRIviLY incurs an additional overhead of about 27% in terms of communication, and between 16% and at most 27% in terms of computation.Item TriDroid: a triage and classification framework for fast detection of mobile threats in android markets(Springer-Verlag, 2021) Amira, Abdelouahab; Derhab, Abdelouahid; Karbab, ElMouatez Billah; Nouali, Omar; Aslam Khan , FarrukhThe Android platform is highly targeted by malware developers, which aim to infect the maximum number of mobile devices by uploading their malicious applications to different app markets. In order to keep a healthy Android ecosystem, app-markets check the maliciousness of newly submitted apps. These markets need to (a) correctly detect malicious app, and (b) speed up the detection process of the most likely dangerous applications among an overwhelming flow of submitted apps, to quickly mitigate their potential damages. To address these challenges, we propose TriDroid, a market-scale triage and classification system for Android apps. TriDroid prioritizes apps analysis according to their risk likelihood. To this end, we categorize the submitted apps as: botnet, general malware, and benign. TriDroid starts by performing a (1) Triage process, which applies a fast coarse-grained and less-accurate analysis on a continuous stream of the submitted apps to identify their corresponding queue in a three-class priority queuing system. Then, (2) the Classification process extracts fine-grained static features from the apps in the priority queue, and applies three-class machine learning classifiers to confirm with high accuracy the classification decisions of the triage process. In addition to the priority queuing model, we also propose a multi-server queuing model where the classification of each app category is run on a different server. Experiments on a dataset with more than 24K malicious and 3K benign applications show that the priority model offers a trade-off between waiting time and processing overhead, as it requires only one server compared to the multi-server model. Also it successfully prioritizes malicious apps analysis, which allows a short waiting time for dangerous applications compared to the FIFO policy.Item Distributed Low-Latency Data Aggregation Scheduling in Wireless Sensor Networks(ACM, 2015-04) Bagaa, Miloud; Younis, Mohamed; Djenouri, Djamel; Derhab, Abdelouahid; Badache, NadjibThis article considers the data aggregation scheduling problem, where a collision-free schedule is determined in a distributed way to route the aggregated data from all the sensor nodes to the base station within the least time duration. The algorithm proposed in this article (Distributed algorithm for Integrated tree Construction and data Aggregation (DICA)) intertwines the tree formation and node scheduling to reduce the time latency. Furthermore, while forming the aggregation tree, DICA maximizes the available choices for parent selection at every node, where a parent may have the same, lower, or higher hop count to the base station. The correctness of the DICA is formally proven, and upper bounds for time and communication overhead are derived. Its performance is evaluated through simulation and compared with six delay-aware aggregation algorithms. The results show that DICA outperforms competing schemes. The article also presents a general hardware-in-the-loop framework (DAF) for validating data aggregation schemes on Wireless Sensor Networks (WSNs). The framework factors in practical issues such as clock synchronization and the sensor node hardware. DICA is implemented and validated using this framework on a test bed of sensor motes that runs TinyOS 2.x, and it is compared with a distributed protocol (DAS) that is also implemented using the proposed framework.Item Intertwined path formation and MAC scheduling for fast delivery of aggregated data in WSN(Elsevier, 2014-12-24) Bagaa, Miloud; Younis, Mohamed; Derhab, Abdelouahid; Badache, NadjibThis paper studies the problem of data aggregation scheduling in wireless sensor networks (WSNs) to minimize time latency. In prior work on this problem, a node is assigned a parent from the set of unscheduled nodes in order to prevent the creation of cycles. However, using such a strategy reduces the time-slot reuse and consequently has a negative impact on the time latency. To address these shortcomings, we propose IPS (Interwined Path formation and MAC Scheduling) , a novel cross-layer scheme for data aggregation scheduling that allows selecting a parent from all the node’s neighbors including the scheduled ones. IPS achieves reduced data delivery latency through three key design features, namely, (1) intertwining aggregation tree formation and scheduling, (2) for each node, a parent can be selected from already scheduled nodes so that the time latency is reduced and the cycles are prevented and (3) applying parent selection criteria that maximize the time slot reuse. We prove that the data delivery latency for IPS is upper-bounded by , where R is the network radius, Δ is the maximum node degree, and 0.05<∊⩽1. The simulation results show that IPS outperforms seven competing state-of-the-art aggregation scheduling algorithms in terms of latency and network lifetimeItem A distributed mutual exclusion algorithm over multi-routing protocol for mobile ad hoc networks(Taylor et Francis, 2008-04-15) Derhab, Abdelouahid; Badache, NadjibIn this paper, we propose a new architecture to solve the problem of mutual exclusion in mobile ad hoc networks (MANET). The architecture is composed of two layers: (i) a middleware layer that contains a token-based distributed mutual exclusion algorithm (DMEA) and (ii) a network layer that includes two routing forwarding strategies: one to route request messages and the other to route the token message. We also propose a request ordering policy that ensures the usual mutual exclusion properties and reduces the number of hops traversed per critical section (CS) access. The paper also addresses the problem of network partitioning and unreachable nodes. The proposed mutual exclusion algorithm is further enhanced to provide fault tolerance by preventing the loss of the token and generating a new token if the token loss event occurs. The performance complexity as well as the experimental results show that the proposed algorithm experiences low number of hops per CS access.Item Balancing the tradeoffs between scalability and availability in mobile ad hoc networks with a flat hashing-based location service(2008-06) Derhab, Abdelouahid; Badache, NadjibIn this paper, we propose FSLS (Flat-based Some-for-some Location Service), a new location service for ad hoc mobile networks. The location service is based on the hash-based sets system that can offer a high location information availability. The network area is divided into non-overlapping zones. A node identifier is mapped to a set of home zones, each of which contains a unique location server, which makes FSLS works as a some-for-some approach. Using cross-layer design, the service can tolerate server mobility and server failures, and last for a long time period. We analyze FSLS and six other existing location services. The theoretical analysis as well as simulation results show that FSLS offers a good trade-off between location availability and scalability. It comes second after a quorum-based location service in terms of location availability and it is the closest competitor to a hierarchical location service in terms of scalability.Item Self-stabilizing algorithm for high service availability in spite of concurrent topology changes in ad hoc mobile networks(Elsevier, 2008-06) Derhab, Abdelouahid; Badache, NadjibMobile nodes in ad hoc networks move freely and run out of battery power so quickly, which leads to frequent network partitioning. Network partitioning considerably reduces service availability when the server node is not in the same partition as the client nodes. In order to provide a continuous service availability for all mobile nodes, we propose a self-stabilizing algorithm that can tolerate multiple concurrent topological changes and can incur a cost of one server per long-lived connected component. By using (1) the time interval-based computations concept that distinguishes between disjoint and concurrent computations, and (2) Markov chain model, the proposed algorithm can within a finite time converge to a legitimate state even if topological changes occur during the convergence time. Our simulation results show that the algorithm can ensure very high service availability, and each node has a strong path to the server of its network component over 98% of the time.Item Enabling ad-hoc collaboration between mobile users in the MESSENGER project(Kluwer Academic Publishers-Plenum, 2007-03) Maamar, Zakaria; Mahmoud, Qusay H.; Derhab, AbdelouahidThis paper discusses how ad-hoc collaboration boosts the operation of a set of messengers. This discussion continues the research we earlier initiated in the MESSENGER project, which develops data management mechanisms for UDDI registries of Web services using mobile users and software agents. In the current operation mode of messengers, descriptions of Web services are first, collected from UDDI registries and later, submitted to other UDDI registries. This submission mode of Web services descriptions does not foster the tremendous opportunities that both wireless technologies and mobile devices offer. When mobile devices are “close” to each other, they can form a mobile ad-hoc network that permits the exchange of data between these devices without any pre-existing communication infrastructure. By authorizing messengers to engage in ad-hoc collaboration, collecting additional descriptions of Web services from other messengers can happen, too. This has several advantages, but at the same time poses several challenges, which in fact highlight the complexity of ad-hoc networks.