International Conference Papers

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    DIAG a diagnostic web application based on lung CT Scan images and deep learning
    (IOS Press Ebooks, 2021-05-29) Hadj Bouzid, Amel Imene; Yahiaoui, Saïd; Lounis, Anis; Berrani, Sid-Ahmed; Belbachir, Hacène; Naili, Qaid; Abdi, Mohamed El Hafedh; Bensalah, Kawthar; Belazzougui, Djamal
    Coronavirus disease is a pandemic that has infected millions of people around the world. Lung CT-scans are effective diagnostic tools, but radiologists can quickly become overwhelmed by the flow of infected patients. Therefore, automated image interpretation needs to be achieved. Deep learning (DL) can support critical medical tasks including diagnostics, and DL algorithms have successfully been applied to the classification and detection of many diseases. This work aims to use deep learning methods that can classify patients between Covid-19 positive and healthy patient. We collected 4 available datasets, and tested our convolutional neural networks (CNNs) on different distributions to investigate the generalizability of our models. In order to clearly explain the predictions, Grad-CAM and Fast-CAM visualization methods were used. Our approach reaches more than 92% accuracy on 2 different distributions. In addition, we propose a computer aided diagnosis web application for Covid-19 diagnosis. The results suggest that our proposed deep learning tool can be integrated to the Covid-19 detection process and be useful for a rapid patient management.
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    Side Channel Attack using Machine Learning
    (IEEE, 2022-12-15) Amrouche, Amina; Boubchir, Larbi; Yahiaoui, Saïd
    The overwhelming majority of significant security threats are hardware-based, where the attackers attempt to steal information straight from the hardware that our secure and encrypted software operates on. Unquestionably, side-channel attacks are one of the most severe risks to hardware security. Rather than depending on bugs in the program itself, a side-channel attack exploits information leaked from the program implementation in order to exfiltrate sensitive secret information such as cryptographic keys. A side channel assault could manifest in different ways including electromagnetic radiation, power consumption, timing data, or even acoustic emanation. Ever since the side-channel attacks were introduced in the 1990s, a number of significant attacks on cryptographic implementations utilizing side-channel analysis have emerged, such as template attacks, and attacks based on power analysis and electromagnetic analysis. However, Artificial Intelligence has become more prevalent. Attackers are now more interested in machine learning and deep learning technologies that enable them to interpret the extracted raw data. The aim of this paper is to highlight the main methods of machine learning and deep learning that are used in the most recent studies that deal with different types of side-channel attacks.
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    A Graph Approach for Enhancing Process Models Matchmaking
    (IEEE, 2015-06-27) Belhoul, Yacine; Yahiaoui, Saïd; Haddad, Mohammed; Gater, Ahmed; Kheddouci, Hamamache; Bouzeghoub, Mokrane
    Recent attempts have been done to measure similarity of process models based on graph matching. This problem is known to be difficult and its computational complexity is exponential. Thus, heuristics should be proposed to obtain approximations. Spectral graph matching methods, in particular eigenvalue-based projections, are know to be fast but they lost some quality in the obtained matchmaking. In this paper, we propose a graph approach for the problem of inexact matching of process models. Our approach combines a spectral graph matching method and a string comparator based algorithm in order to improve the quality of process models matchmaking. The proposed method performs the matchmaking at both structural and semantic levels. Experimentation is provided to show the performance of our method to rank a collection of process models according to a particular user query, compared to previous work.
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    Graph Edit Distance Compacted Search Tree
    (Springer, Cham, 2022) Chegrane, Ibrahim; Hocine, Imane; Yahiaoui, Saïd; Bendjoudi, Ahcene; Nouali_Taboudjemat, Nadia
    We propose two methods to compact the used search tree during the graph edit distance (GED) computation. The first maps the node information and encodes the different edit operations by numbers and the needed remaining vertices and edges by BitSets. The second represents the tree succinctly by bit-vectors. The proposed methods require 24 to 250 times less memory than traditional versions without negatively influencing the running time.
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    Towards a Dynamic Evacuation System for Disaster Situations
    (IEEE, 2014-03) Benssam, Ali; Bendjoudi, Ahcène; Yahiaoui, Saïd; Nouali-Taboudjemat, Nadia; Nouali, Omar
    Medical evacuation is one of the most important modules in the emergency plans activated during disaster situations. It aims at evacuating victims to the most appropriate health-care facilities. Evacuation plans were for a long time performed approximatively and passively rather than optimally and proactively between the disposal site and the targeted hospital and they often lacked visibility on the evolution of the events that may change data and leading to a revision of the plans. However, thanks to the proliferation of information and communication technologies (ICTs) in all aspects of life, the evacuation operations in disaster situations had known a great enhancement. In fact, critical operations such as real-time monitoring of the state of resources used during the evacuation process, detecting the occurring changes and reflecting them on the global process to provide dynamic and optimal evacuation plans become possible. In this paper, we propose a framework for dynamic evacuation operations in disaster situations. We design a system that takes into consideration the above challenges such as detecting changes and using them in an intelligent way to enable dynamic, optimal and up-to-date evacuation plans. The provided prototype is called DEvacuS (Dynamic Evacuation System).
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    AdSIP: Decentralized SIP for Mobile Ad Hoc Networks
    (IEEE, 2012-03) Yahiaoui, Saïd; Belhoul, Yacine; Nouali-Taboudjemat, Nadia; Kheddouci, Hamamache
    SIP signaling protocol relies on centralized SIP servers deployed on the infrastructure of the network to route SIP messages in order to enable user endpoints to discover each other. However, the lack of the infrastructure in ad hoc networks requires that the network nodes support the tasks of participants discovery and SIP messages routing. In this paper, we propose AdSIP protocol which is a completely distributed architecture for SIP that implements SIP servers in selected nodes. The SIP servers are selected using a distributed algorithm constructing a connected minimal global offensive alliance. AdSIP is implemented and compared under NS-2 with TCA protocol which uses a cluster based approach. The simulation results show the advantages of AdSIP and confirm that it is adapted to mobile ad hoc networks by giving low session establishment time, low control overhead and high service availability.
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    TopCoF: A Topology Control Framework for Wireless Ad hoc Networks
    (IEEE, 2010-12) Yahiaoui, Saïd; Belhoul, Yacine; Faoudi, Farid; Kheddouci, Hamamache
    Topology Control (TC) is a well known technique used in wireless ad hoc and sensor networks to reduce energy consumption. This technique coordinates the decisions of network nodes about their transmission power to save energy, prolong network lifetime, and mitigate MAC-level medium contention, while maintaining network connectivity. In order to ease the implementation and the study in systematic way of proposed TC protocols, in terms of energy usage and network graph properties, we propose a new framework based on NS-2 simulator. The framework is named TopCoF and composed of two main parts. The first one consists of a set of NS-2 extensions to support TC, while the second is a graphical user interface for statistical analysis and visualization of simulation results traced by the first part. TopCoF is modular and generic since it implements a set of basic components used by TC protocols.