Mohammad Essaaidi

Wireless sensor network in smart grid technology: Challenges and opportunities

The collaborative and low-cost nature of wireless sensor networks (WSNs) brings significant advantages over traditional communication technologies used in todays electric power systems. Recently, WSNs have been widely recognized as a promising technology that can enhance various aspects of todays electric power systems, including generation, delivery, and utilization, making them a vital component of the next-generation electric power system, the smart grid. However, harsh and complex electric- power-system environments pose great challenges in the reliability of WSN communications in smart grid applications. This paper starts with an overview of the application of WSNs for electric power systems along with their opportunities and challenges and opens up future work in many unexploited research areas in diverse smart-grid applications.

Mobile phones security: the spread of malware via MMS and Bluetooth, prevention methods

The work presented in this paper describes the evolution impact of mobile devices operating systems features through its increasing use for internet navigation. And thus, the growing risks of getting contaminated by hostile programs, which exploit the vulnerabilities of these systems and spreading to a large scale via services such as Bluetooth and MMS.n Following the description of the spreading and infection methods of these equipments via Bluetooth and MMS, two solutions from the industrial and academic world are exposed. Moreover, a solution based on the use of telecom providers online services to scan and disinfect these mobile devices is proposed at the end.

Collaborative learning and wiki

This paper aims to develop access for students and teachers in an activity via a wiki collaboration website. To this end, it proposes using XWiki for the implementation of a collaborative learning environment. It allows the involvement of users, collaboration, social interaction and knowledge sharing. No doubt, this tool fits well with the most current pedagogical trends that actively focus, in a real context, specifically on collaboration, participation and knowledge construction. This paper describes the proposed system and the pedagogical environment of the project, including the concept of collaborative learning scenario. Finally, it describes the processes involved in achieving our collaborative learning website TENSWiki.

Compromised Resources Tolerance in Grid Computing Systems

In the past ten years, grid computing has been heavily researched and developed. At the present, grid technology has matured enough to enable the realization of workable and commercial infrastructures, platforms and tools, ready to be used in production environments ranging from scientific to commercial application domains. As grid resources are used outside of organizational boundaries, it becomes increasingly difficult to guarantee that a resource being used is not malicious in some way. However, the critical grid application domains require many protections against malicious entities or massive attacks. It is then necessary to detect and tolerate malicious behavior of grid resources (or resources provider) in order to enhance the efficiency of grid security architecture. In this paper, we will propose and discuss an attack-tolerance mechanism based on sabotage tolerance technique. The grid broker service will build the reputation of all resources provider, by observing their trustworthiness from their previous results. The reputation value can be used in the validation process of job result by using majority voting technique.

An Efficient Approach to Improve Security for MapReduce Computation in Cloud System

Running MapReduce computation in public cloud raises a series of security challenges since the service providers may not be properly protected. Due to the fact that the MapReduce applications are long-running, which increases the chance of an attacker to massively perform malicious attacks by exploiting the workers vulnerability, many workers may be compromised. Those workers could misbehave and thereby tamper the results integrity of all computations assigned to them. To tackle this challenge, this paper proposes an effective Result Verification Mechanism (RVM) using a reputation threshold-based voting method to ensure the result integrity of MapReduce on the map and reduce phases. Therefore, render the MapReduce computation accurate. Another major contribution of this paper is that we implement RVM based on Apache Hadoop and perform a series of experiments. The evaluation study of the experimental results demonstrate that RVM can significantly reduce computation overhead and guarantee a low error rate as compared to the simple voting method like m-first voting.

Classification of Cloud Systems Cyber-security Threats and Solutions Directives

Cloud computing cyber security is a subject that has been in top flight for a long period and even in near future. However, cloud computing permit to stock up a huge number of data in the cloud stockage, and allow the user to pay per utilization from anywhere via any terminal equipment. Among the major issues related to Cloud Computing security, we can mention data security, denial of service attacks, confidentiality, availability, and data integrity. This paper is dedicated to a taxonomic classification study of cloud computing cyber-security. With the main objective to identify the main challenges and issues in this field, the different approaches and solutions proposed to address them and the open problems that need to be addressed.

A new mechanism to ensure integrity for MapReduce in cloud computing

MapReduce has been widely used as a powerful parallel data processing model and is adopted by most cloud providers to built cloud computing framework. However, in open cloud systems, security of computation becomes a great challenge. Moreover, MapReduce data-processing services are long-running, which increase the opportunity that an adversary launches attack to the workers and make them behave maliciously and, then tamper with the computation integrity of user tasks where their executions are generally performed in different administration domains out of the user control. Thus, the results of the computation might be erroneous and dishonest. In this paper, we propose a new mechanism based on weighted t-first voting method for ensuring the integrity of MapReduce in open cloud computing environment. Our mechanism can defeat both collusive and non-collusive malicious entities and thus guarantee high computation accuracy.

A new approach of e-learning-adaptive based on ant colonies optimisation algorithm

Adaptive E-learning, refers to a training concept in which technology is introduced step by step in all aspects of the business of training. A technique, inspired by the Ant Colony Optimization (ACO), is proposed to optimize the learning path. The proposed platform is modeled by a graph where nodes represent the educational elements (lessons or exercises), and arcs link navigation between them. Each of the arcs is also a value that describes its importance in relation to teaching neighboring arcs. Students are represented by virtual agents (ants) who use these links.