rahmoun abdellatif | École Supérieure en Informatique 08 Mai 1945 – Sidi Bel Abbes – (original) (raw)

Papers by rahmoun abdellatif

Rist, 2004

L'objectif de cet article consiste a implementer et etudier le fonctionnement et les performa... more L'objectif de cet article consiste a implementer et etudier le fonctionnement et les performances comparees des algorithmes suivants : DES « Data Encryption Standard » qui signifie standard de chiffrement de donnees, l'un des algorithmes les plus connus du monde de la cryptographie. C'est un algorithme a clef secrete . RSA « RIVEST SHAMIR ADELLMAN » sans doute l'algorithme a clef publique [DIF 88] le plus populaire. Il peut aussi bien etre utilisee pour le chiffrement que pour la signature numerique (...)

International Journal of Computer Applications, 2011

of matching scores of multiple biometric traits is becoming more and more popular and is a very p... more of matching scores of multiple biometric traits is becoming more and more popular and is a very promising approach to enhance the system's accuracy. This paper presents a comparative study of several advanced artificial intelligence techniques (e.g. Particle Swarm Optimization, Genetic Algorithm, Adaptive Neuro Fuzzy Systems, etc...) as to fuse matching scores in a multimodal biometric system. The fusion was performed under three data conditions: clean, varied and degraded. Some normalization techniques are also performed prior fusion so to enhance verification performance. Moreover; it is shown that regardless the type of biometric modality , when fusing scores genetic algorithms and Particle Swarm Optimization techniques outperform other well-known techniques in a multimodal biometric system verification/identification.

Machine Learning and Cognitive Science Applications in Cyber Security, 2019

WSNs have recently been extensively investigated due to their numerous applications where process... more WSNs have recently been extensively investigated due to their numerous applications where processes have to be spread over a large area. One of the important challenges in WSNs is secure node localization. Its main objective is to protect the circulated information in WSN for any attack with low energy. For this reason, recent approaches relying on swarm intelligence techniques are called and the node localization is seen as an optimization problem in a multi-dimensional space. In this chapter, the authors present an improvement to the original bat algorithm for information protecting during the localization task. Hence, the proposed approach computes iteratively the position of the nodes and studied the scalability of the algorithm on a large WSN with hundreds of sensors that shows pretty good performance. Moreover, the parameters are simulated in different scenarios of simulation. In addition, a comparative study is conducted to give more performance to the proposed algorithm.

International Journal of Distributed Systems and Technologies

Recently developments in wireless sensor networks (WSNs) have raised numerous challenges, node lo... more Recently developments in wireless sensor networks (WSNs) have raised numerous challenges, node localization is one of these issues. The main goal in of node localization is to find accurate position of sensors with low cost. Moreover, very few works in the literature addressed this issue. Recent approaches for localization issues rely on swarm intelligence techniques for optimization in a multi-dimensional space. In this article, we propose an algorithm for node localization, namely Moth Flame Optimization Algorithm (MFOA). Nodes are located using Euclidean distance, thus set as a fitness function in the optimization algorithm. Deploying this algorithm on a large WSN with hundreds of sensors shows pretty good performance in terms of node localization. Computer simulations show that MFOA converge rapidly to an optimal node position. Moreover, compared to other swarm intelligence techniques such as Bat algorithm (BAT), particle swarm optimization (PSO), Differential Evolution (DE) and...

International Journal of Computer Applications, Nov 29, 2011

Fusion of matching scores of multiple biometric traits is becoming more and more popular and is a... more Fusion of matching scores of multiple biometric traits is becoming more and more popular and is a very promising approach to enhance the system's accuracy. This paper presents a comparative study of several advanced artificial intelligence techniques (e.g. Particle Swarm Optimization, Genetic Algorithm, Adaptive Neuro Fuzzy Systems, etc...) as to fuse matching scores in a multimodal biometric system. The fusion was performed under three data conditions: clean, varied and degraded. Some normalization techniques are also performed prior fusion so to enhance verification performance. Moreover; it is shown that regardless the type of biometric modality , when fusing scores genetic algorithms and Particle Swarm Optimization techniques outperform other well-known techniques in a multimodal biometric system verification/identification.

Wireless sensor networks are provided with a limited source of power. The lifetime of such networ... more Wireless sensor networks are provided with a limited source of power. The lifetime of such networks is an overwhelming matter in most network applications. This lifetime depends strongly on how efficiently such energy is distributed over the nodes especially during transmitting and receiving data. Each node may route messages to destination nodes either through short hops or long hops. Optimizing the length of these hops may save energy, and therefore extend the lifetime of WSNs. In this paper, we propose a theorem to optimize the hop's length so to make WSN power consumption minimal. The theorem establishes a simple condition on hop's length range. Computer simulation when performing such condition on Mica2 sensors and Mica2dot sensors reveals good performance regarding WSNs energy consumption.

Sensor networks consist of miniaturized wireless sensor nodes with limited capacity and energy so... more Sensor networks consist of miniaturized wireless sensor nodes with limited capacity and energy source. As sensors may be deployed in a large area, radio transceivers are the most energy consumer in sensor nodes, so their usage need to be very efficient in order to maximize network's life. A node can route it's messages towards destination either by using small or large hops, so optimizing the hop length can extend significantly the lifetime of the network. This paper provides a simple condition, to verify, which makes the energy consumption minimal by choosing ideal hop's length.

IFIP Advances in Information and Communication Technology, 2015

Wireless Sensor Network, 2014

Design and Applications, 2014

Intensive efforts are made in the Web services selection literature by these days mainly because ... more Intensive efforts are made in the Web services selection literature by these days mainly because of the overwhelming interest of the community in the services provided over the Web. In selecting best services, the non functional properties of such services are proven to be more and more important; these describe the Quality of service that is the key factor in the selection process.In this paper, we discuss a Web service selection based on both the context and the QoS ontology. We propose an architecture that makes an automatic selection of best service provider that is based on mixed context and QoS ontology for a given set of parameters of QoS. The key idea is to rely on multi dimensional QoS. Finally, some experiments are run so to demonstrate consistency and effectiveness of the proposed method.

Algeria.Tel(213)48-577750 Abstract Parallelism has generated new concepts and approaches making i... more Algeria.Tel(213)48-577750 Abstract Parallelism has generated new concepts and approaches making it possible to conceive competitive systems and parallel architectural configurations. These two concepts are hard to bring altogether and require a precise definition of the structural elements of algorithm and their projection on suitable parallel architectures. The work described in this paper, tries to concretize this merge of concepts for a class of architectures called: " systolic " .

Iee Proceedings-control Theory and Applications, 1998

This paper is concemed with the design of new generation of intelligent systems. These systems or... more This paper is concemed with the design of new generation of intelligent systems. These systems or machines are intelligent if they are able to improve their performance or maintain an acceptable level of performance in the presence of uncertainty. The ability of these systems to examine and modifr their behaviors in a limited sense is usually achieved by using techniques such as knowledge-based systems (KBS), Artificial Neural Networks (Mvs), Fuuy systems (FSs), and Genetic Algorithms (GAS). In thispaper we propose a novel technique called NEFGEN or Neuro-Fuzzy Generator. This Hybrid Neuro-Fuuy generator is based on the Knowledge Oriented Design (KOD) concept, Cooperative Neuro-Fuuy systems and Genetic Algorithms. A classification through a competitive neural network of data examples of the application to be performed provides eficient inference rules as well as adequate fuu;y partitions of the input/output variable domains. The resulting fuzzy system is then optimized using random techniques and genetic algorithm techniques. NEFGEN is proved to be very eficient in designing poweijkl fuur expert systems (FESs) especially in classification and approximation. It is also shown that NEFGEN performance exceed those of known hybrid neuro-fuuy systems such as ANFIS, NEFPROX, and NEFCLASS.

The International Arab Journal of Information Technology, 2007

Evolutionary Engineering (EE) is defined to be "the art of using evolutionary algorithms approach... more Evolutionary Engineering (EE) is defined to be "the art of using evolutionary algorithms approach such as genetic algorithms to build complex systems". This paper deals with a neural net based system. It analyses ability of genetically trained neural nets to control Simulated robot arm, witch tries to track a moving object. In difference from classical Approaches neural network learning is performed on line, i.e., in real time. Usually systems are built/evolved, i.e., genetically trained separately of their utilization. That is how it is commonly done. It's a fact that evolution process is heavy on time; that's why Real-Time approach is rarely taken into consideration. The results presented in this paper show that such approach (Real-Time EE) is possible. These successful results are essentially due to the "continuity" of the target's trajectory. In EE terms, we express this by the Neighbourhood Hypothesis (NH) concept.

By these days, most companies are more aware of than ever in providing quality of services over t... more By these days, most companies are more aware of than ever in providing quality of services over the web for reasons of economy, reliability, interoperability, flexibility, and universality. Enterprise application integration may rely on B2B scenarios where several candidate services with similar capabilities are provided by different service providers. The question is, how upon a request over a B2B integration scenario, the system chooses a service among several candidate services offering a capability satisfying its requests? This paper proposes a model that makes an automatic selection of best service provider that is based on mixed context and QoS ontology for a given set of parameters of QoS. We particularly show how this approach can be made to support an e-business framework and how it can add dynamics to B2B interactions by automating selection among heterogeneous services. We emphasize here on one dimensional quality of services. The approach is illustrated through a purchasing scenario to demonstrate consistency and effectiveness of the proposed method.

The International Arab Journal of Information Technology, 2008

The advance of the Web has significantly and rapidly changed the way of information organization,... more The advance of the Web has significantly and rapidly changed the way of information organization, sharing and distribution. However, most of the information that is available has to be interpreted by humans; machine support is rather limited. The next generation of the web, the semantic web, seeks to make information more usable by machines by introducing a more rigorous structure based on ontology. In this context we try to propose a novel and integrated approach for migrating data-intensive web into ontology-based semantic web and thus, make the web content machine-understandable. Our approach is based on the idea that semantics can be extracted from the structures and the instances of HTML forms which are the most convenient interface to communicate with relational databases on the current Web. This semantics is exploited to help build ontology.