Mohamed Ouadou

Efficient deployment quality analysis for intrusion detection in wireless sensor networks

Abstract The intrusion detection in a Wireless Sensor Network is defined as a mechanism to monitor and detect any intruder in a sensing area. The sensor deployment quality is a critical issue since it reflects the cost and detection capability of a wireless sensor network. The quality of deterministic deployment can be determined sufficiently by a rigorous analysis before the deployment. However, when random deployment is required, determining the deployment quality becomes challenging. In the intrusion detection application, it is necessary to define more precise measures of sensing range, transmission range, and node density that impact overall system performance. The major question is centred around the quality of intrusion detection in WSN, how we can guarantee that each point of the sensing area is covered by at least one sensor node, and what a sufficient condition to guarantee the network connectivity? In this paper, we propose an appropriate probabilistic model which provides the coverage and connectivity in k-sensing detection of a wireless sensor network. We have proved the capability of our approach using a geometric analysis and a probabilistic model.

Analysis of the Deployment Quality for Intrusion Detection in Wireless Sensor Networks

The intrusion detection application in a homogeneous wireless sensor network is defined as a mechanism to detect unauthorized intrusions or anomalous moving attackers in a field of interest. The quality of deterministic sensor nodes deployment can be determined sufficiently by a rigorous analysis before the deployment. However, when random deployment is required, determining the deployment quality becomes challenging. An area may require that multiple nodes monitor each point from the sensing area; this constraint is known as k-coverage where k is the number of nodes. The deployment quality of sensor nodes depends directly on node density and sensing range; mainly a random sensor nodes deployment is required. The major question is centred around the problem of network coverage, how can we guarantee that each point of the sensing area is covered by the required number of sensor nodes and what a sufficient condition to guarantee the network coverage? To deal with this, probabilistic intrusion detection models are adopted, called single/multi-sensing detection, and the deployment quality issue is surveyed and analysed in terms of coverage. We evaluate the capability of our probabilistic model in homogeneous wireless sensor network, in terms of sensing range, node density, and intrusion distance.

A Velocity-Aware Handover Trigger in Two-Tier Heterogeneous Networks

The unexpected change in user equipment (UE) velocity is recognized as the primary explanation for poor handover quality. In order to resolve this issue, while limiting ping-pong (PP) events we carefully and dynamically optimized handover parameters for each UE unit according to its velocity and the coverage area of the access point (AP). In order to recognize any variations in velocity, we applied Allan variance (AVAR) to the received signal strength (RSS) from the serving AP. To assess our approach, it was essential to configure a heterogeneous network context (LTE-WiFi) and interconnect Media-Independent Handover (MIH) and Proxy Mobile IPv6 (PMIPv6) for seamless handover. Reproduction demonstrated that our approach does not only result in a gain in relatively accurate velocity but in addition reduces the number of PP and handover failures (HOFs).

Short: Intrusion Detection Quality Analysis for Homogeneous Wireless Sensor Networks

In this paper we analyze the intrusion detection in a homogeneous Wireless Sensor Network that is defined as a mechanism to monitor and detect unauthorized intrusions or anomalous moving attackers in area of interest. The quality of deterministic deployment can be determined sufficiently by analysis, before the deployment. However, when random deployment is required, determining the deployment quality becomes challenging and depends directly on node density. The major question is centered on the network coverage problem, how can we guarantee that each point of the region is covered by the required number of sensors? To deal with this, probabilistic intrusion detection models are adopted, called single and multi sensing probability detection and the deployment quality issue is surveyed and analyzed in terms of coverage. We evaluate our probabilistic model in homogeneous wireless sensor network, in term of sensing range, node density, and intrusion distance.

On the Deployment Quality for Multi-intrusion Detection in Wireless Sensor Networks

The intrusion detection in a Wireless Sensor Network is defined as a mechanism to monitor and detect any intruder in a sensing area. The sensor deployment quality is a critical issue since it reflects the cost and detection capability of a wireless sensor network. When the random deployment is required, which sensor nodes are uniformly randomly distributed over on surface area, determining the deployment quality becomes challenging. In the intrusion detection application, it is necessary to define more precise measures of sensing range and node density that impact overall system performance. To enhance the detection quality for single/multi intrusion, a probabilistic intrusion detection models are adopted, called single and multi sensing probability detection and the deployment quality issue is surveyed and analysed in term of coverage.

Context-Based Query Expansion Method for Short Queries Using Latent Semantic Analyses

Short queries are the key difficulty in information retrieval (IR). A plenty of query expansion techniques has been proposed to solve this problem. In this paper, we propose three different models for query suggestion using the cosine similarity (CS), the Language Models (LM) or their fusion. The expansion terms are selected using the Latent Semantic Analyses method based on the result of the three query suggestion methods. The approaches proposed improve the precision of the user query by adding additional context to it. Experimental results show that expanding short queries by our approaches improves the effectiveness of the IR system by 48,1 % using the CS based model, 19,2 % using the LM model, and 13,5 % using the fusion model.

A Modeling Approach for IT Governance Basics Application on IT Projects and IT Goals

IT governance meets the need of decision making and leads to settling the main preoccupations company leaders have. It aims at developing good practice through the transmission of reliable, structured and intelligible information on the state of the IT (Information Technology) and the development of the effective steering devices. IT Governance is built around notions such as IT project, IT goal and based upon structured frameworks that can be found in the literature. Despite their existence, these notions are seldom developed and there is no common model posing and describing them as classical governance notions. We therefore put forward IT governance modeling as a means to sort out this lack of consideration, laying out a representation template of IT governance concepts build on probabilities and the Monte Carlo simulation. Our approach stands out by setting up a simple way to deal with these concepts based on the analysis of the literature in order to support the various IT governance syntaxes. This approach thus allows opening new IT Governance knowledge modeling and structuring consistent with IT governance activities.

Unsupervised approach data analysis based on fuzzy possibilistic clustering: application to medical image MRI

The analysis and processing of large data are a challenge for researchers. Several approaches have been used to model these complex data, and they are based on some mathematical theories: fuzzy, probabilistic, possibilistic, and evidence theories. In this work, we propose a new unsupervised classification approach that combines the fuzzy and possibilistic theories; our purpose is to overcome the problems of uncertain data in complex systems. We used the membership function of fuzzy c-means (FCM) to initialize the parameters of possibilistic c-means (PCM), in order to solve the problem of coinciding clusters that are generated by PCM and also overcome the weakness of FCM to noise. To validate our approach, we used several validity indexes and we compared them with other conventional classification algorithms: fuzzy c-means, possibilistic c-means, and possibilistic fuzzy c-means. The experiments were realized on different synthetics data sets and real brain MR images.

Enhanced Matching Game for Decoupled Uplink Downlink Context-Aware Handover

In this paper, we address the problem of cell association during a handover performed in a dense heterogeneous network, where the preference of a mobile user’s equipment in terms of uplink traffic is not the same as for the downlink traffic. Therefore, since mobility is an intrinsic element of cellular networks, designing a handover from the perspective of the uplink and downlink is mandatory in the context of 5G cellular networks. Based on this arena, we propose a decoupled uplink-downlink handover scheme while making use of femtocells in order to maximize the overall network entity utilities and avoid overloading macrocells. However, the fact that the handover process is performed in a dense heterogeneous network makes the issue NP-hard. Therefore, taking into account the need for self-organizing solutions, we modeled the handover process as a matching game with externalities. Thus, we will provide an aspect of intelligence for the execution of the handover process to mobile user’s equipment (UE). To make the proposition more efficient, we integrate an assignment step to assist the matching game. Hence, the base stations will be investigated and filtered, keeping only the helpful base stations as the players in terms of the quality of service for the uplink and downlink. The numerical results verify the superiority of the proposed context-aware algorithm over traditional downlink handover and traditional decoupled uplink and downlink handover schemes, by improving the load balancing, increasing rates and reducing delays.

A Seamless Handover Based MIH-Assisted PMIPV6 in Heterogeneous Network(LTE-WIFI)

We consider the user equipment (UE) velocity as a vital trend in association problem in heterogeneous networks (HetNets), since there is a considerable relation between the velocity and the handover failure (HOF) as well as the probability of unnecessary handovers (ping-pong (PP) events). Several works have been carried out, in the context of standards and scientific research to perform the vertical handover process, such as the IEEE 802.21 Media Independent Handover(MIH) framework and Network Mobility Basic Support Protocol as a proxy mobile internet protocol version 6 (PMIPV6). Therefore, in our paper, we found that interconnecting those two frameworks will be effective in terms of handover decision-making. In addition, to solve the impact of velocity in handover process, we need to carefully and dynamically optimize handover parameters for each UE according to his velocity and coverage area of the access point (AP). To detect any variation in the velocity and evaluate if a transfer is necessary: MIH will study periodically the Allan Variance (AVAR) of received signal strength (RSS) from the serving AP and PMIPv6 will take over the control and execute the handover based on the results obtained by MIH. To evaluate our contribution, it was necessary to configure a heterogeneous network environment (LTE-WIFI) and to integrate MIH PMIPv6 for seamless handover. Simulation results show that it can not only gain relatively accurate velocity, but also reduces the number of PP and HOF.