Cooperative Trust Framework for Cloud Computing Based on Mobile Agents

Cloud computing opens doors to the multiple, unlimited venues from elastic computing to on demand provisioning to dynamic storage, reduce the potential costs through optimized and efficient computing. To provide secure and reliable services in cloud computing environment is an important issue. One of the security issues is how to reduce the impact of for any type of intrusion in this environment. To counter these kinds of attacks, a framework of cooperative Hybrid intrusion detection system (Hy-IDS) and Mobile Agents is proposed. This framework allows protection against the intrusion attacks. Our Hybrid IDS is based on two types of IDS, the first for the detection of attacks at the level of virtual machines (VMs), the second for the network attack detection and Mobile Agents. Then, this framework unfolds in three phases: the first, detection intrusion in a virtual environment using mobile agents for collected malicious data. The second, generating new signatures from malicious data, which were collected in the first phase. The third, dynamic deployment of updates between clusters in a cloud computing, using the newest signatures previously created. By this type of close-loop control, the collaborative network security management system can identify and address new distributed attacks more quickly and effectively. In this paper, we develop a collaborative approach based on Hy-IDS and Mobile Agents in Cloud Environment, to define a dynamic context which enables the detection of new attacks, with much detail as possible

Use Trust Management Framework to Achieve Effective Security Mechanisms in Cloud Environment

Cloud Computing is an Internet based Computing where virtual shared servers provide software, infrastructure, platform and other resources to the customer on pay-as-you-use basis. Cloud Computing is increasingly becoming popular as many enterprise applications and data are moving into cloud platforms. However, with the enormous use of Cloud, the probability of occurring intrusion also increases. There is a major need of bringing security, transparency and reliability in cloud model for client satisfaction. One of the security issues is how to reduce the impact of any type of intrusion in this environment. To address this issue, a security solution is proposed in this paper. We provide a collaborative framework between our Hybrid Intrusion Detection System (Hy-IDS) based on Mobile Agents and virtual firewalls. Therefore, our hybrid intrusion detection system consists of three types of IDS namely IDS-C, IDS-Cr and IDS-M, which are dispatched over three layer of cloud computing. In the first layer, we use IDS-C over our framework to collect, analyze and detect malicious data using Mobile Agents. In case of attack, we collect at the level of the second layer all the malicious data detected in the first layer for the generation of new signatures using IDS-Cr, which is based on a Signature Generation Algorithm (SGA) and network intrusion detection system (NIDS). Finally, through an IDS-M placed in the third layer, the new signatures will be used to update the database NIDS belonging to IDS-Cr, then the database to NIDS belonging of IDS-Cr the cluster neighboring and also their IDS-C. Hardware firewall is unable to control communication between virtual machines on the same hypervisor. Moreover, they are blind to virtual traffic. Mostly, they are deployed at Virtual Machine Monitor- level (VMM) under Cloud provider’s control. Equally, the mobile agents play an important role in this collaboration. They are used in our framework for investigation of hosts, transfer data malicious and transfer update of a database of neighboring IDS in the cloud. With this technique, the neighboring IDS will use these new signatures to protect their area of control against the same type of attack. By this type of close-loop control, the collaborative network security management framework can identify and address new distributed attacks more quickly and effectively

Image-Based Lateral Position, Steering Behavior Estimation, and Road Curvature Prediction for Motorcycles

International audienceThis letter presents an image-based approach to simultaneously estimate the lateral position of a powered-two-wheeled vehicle on the road, its steering behavior and predict the road curvature ahead of the motorcycle. This letter is based on the inverse perspective mapping technique combined with a road lanes detection algorithm capable of detecting straight and curved lanes. Then, a clothoid model is used to extract pertinent information from the detected road markers. Finally, the performance of the proposed approach is illustrated through simulations carried out with the well-known motorcycle simulator “BikeSim.” The results are very promising since the algorithm is capable of estimating, in real time, the road geometry and the vehicle location with a better accuracy than the one given by the commercial GPS

Inverse Perspective Mapping Roll Angle Estimation for Motorcycles

International audienceThis paper presents an image-based approach to estimate the motorcycle roll angle. The algorithm estimates directly the absolute roll to the road plane by means of a basic monocular camera. This means that the estimated roll angle is not affected by the road bank which is often a problem for vehicle observation and control purposes. For each captured image, the algorithm uses a numeric roll loop based on some simple knowledge of the road geometry. For each iteration, a bird-eye-view of the road is generated with the inverse perspective mapping technique. Then, a road marker filter associated with the well-known clothoid model are used respectively to track the road separation lanes and approximate them with mathematical functions. Finally, the algorithm computes two distinct areas between the two-road separation lanes. Its performances are tested by means of the motorcycle simulator BikeSim. This approach is very promising since it does not require any vehicle or tire model and is free of restrictive assumptions on the dynamics

Powered Two-Wheeled Vehicles Steering Behavior Study: Vision-Based Approach

International audienceThis paper presents a vision-based approach to prevent dangerous steering situations when riding a motorcycle in turn. In other words, the proposed algorithm is capable of detecting under, neutral or over-steering behavior using only a conventional camera and an inertial measurement unit. The inverse perspective mapping technique is used to reconstruct a bird-eye-view of the road image. Then, filters are applied to keep only the road markers which are, afterwards, approximated with the well-known clothoid model. That allows to predict the road geometry such that the curvature ahead of the motorcycle. Finally, from the predicted road curvature, the measures of the Euler angles and the vehicle speed, the proposed algorithm is able to characterize the steering behavior. To that end, we propose to estimate the steering ratio and we introduce new pertinent indicators such that the vehicle relative position dynamics to the road. The method is validated on the advanced simulator BikeSim during a steady turn

IOT et Cloud Computing : état de l'art

International audienceInternet of things (IOT) rend les objets simples des objets intelligents capables de transférer des données sur un réseau sans interaction humaine. Les données générées par ces objets sont en temps réel et non structurées, ce qui nécessite une structure décentralisée permettant le stockage et l’analyse de cette grande quantité de données. L’intégration du Cloud Computing et IOT devient importante pour plusieurs raison : quantité de données générées, besoin d'avoir le privilège d'utilisation des ressources virtuelles et la capacité de stockage, aussi la possibilité de créer plus d'utilité à partir des données générées par IoT et le développement des applications intelligentes pour les utilisateurs. Dans cet article nous présentons une revue de littérature sur l’intégration de l’internet of things et le Cloud Computing et les défis de cette intégration

Hydrochemical and isotopic characterization of a complex aquifer system

A methodology was developed and applied to the Tindouf basin (south-western Algeria) to understand the hydrogeology of a complex aquifer system with a limited number of data, to identify the favorable areas for the design and building of new wells, and to know whether there is still current recharge of these aquifers. The principal components analysis (PCA), diagram of deuterium versus oxygen-18, and equilibrium diagrams Mg/Na and Ca/Na were the techniques used to combine different datasets in order to identify chemical and isotopic groups, which were in turn used to define the groundwater flow paths. In addition, on the basis of thermodynamic equilibrium, it is possible to define the chemical evolution of the Tindouf basin aquifer. The results of this study are consistent with the generally accepted hydrogeological conceptual model. The combination of the different methods made possible to define and and to characterise the main groundwater flow paths from their sources to the discharge zones. These flow paths are defined by water categories, which are represented by salinity and groundwater origin. This approach can be used to analyze aquifers characterized by a lack of data and can also be useful for studying other complex groundwater basins

Use Trust Management Framework to Achieve Effective Security Mechanisms in Cloud Environment

Cloud Computing is an Internet based Computing where virtual shared servers provide software, infrastructure, platform and other resources to the customer on pay-as-you-use basis. Cloud Computing is increasingly becoming popular as many enterprise applications and data are moving into cloud platforms. However, with the enormous use of Cloud, the probability of occurring intrusion also increases. There is a major need of bringing security, transparency and reliability in cloud model for client satisfaction. One of the security issues is how to reduce the impact of any type of intrusion in this environment. To address this issue, a security solution is proposed in this paper. We provide a collaborative framework between our Hybrid Intrusion Detection System (Hy-IDS) based on Mobile Agents and virtual firewalls. Therefore, our hybrid intrusion detection system consists of three types of IDS namely IDS-C, IDS-Cr and IDS-M, which are dispatched over three layer of cloud computing. In the first layer, we use IDS-C over our framework to collect, analyze and detect malicious data using Mobile Agents. In case of attack, we collect at the level of the second layer all the malicious data detected in the first layer for the generation of new signatures using IDS-Cr, which is based on a Signature Generation Algorithm (SGA) and network intrusion detection system (NIDS). Finally, through an IDS-M placed in the third layer, the new signatures will be used to update the database NIDS belonging to IDS-Cr, then the database to NIDS belonging of IDS-Cr the cluster neighboring and also their IDS-C. Hardware firewall is unable to control communication between virtual machines on the same hypervisor. Moreover, they are blind to virtual traffic. Mostly, they are deployed at Virtual Machine Monitor- level (VMM) under Cloud provider’s control. Equally, the mobile agents play an important role in this collaboration. They are used in our framework for investigation of hosts, transfer data malicious and transfer update of a database of neighboring IDS in the cloud. With this technique, the neighboring IDS will use these new signatures to protect their area of control against the same type of attack. By this type of close-loop control, the collaborative network security management framework can identify and address new distributed attacks more quickly and effectively

Inverse Perspective Mapping Roll Angle Estimation for Motorcycles

© 2018 IEEE. This paper presents an image-based approach to estimate the motorcycle roll angle. The algorithm estimates directly the absolute roll to the road plane by means of a basic monocular camera. This means that the estimated roll angle is not affected by the road bank which is often a problem for vehicle observation and control purposes. For each captured image, the algorithm uses a numeric roll loop based on some simple knowledge of the road geometry. For each iteration, a bird-eye-view of the road is generated with the inverse perspective mapping technique. Then, a road marker filter associated with the well-known clothoid model are used respectively to track the road separation lanes and approximate them with mathematical functions. Finally, the algorithm computes two distinct areas between the two-road separation lanes. Its performances are tested by means of the motorcycle simulator BikeSim. This approach is very promising since it does not require any vehicle or tire model and is free of restrictive assumptions on the dynamics

Powered Two-Wheeled Vehicles Steering Behavior Study: Vision-Based Approach

© 2018 IEEE. This paper presents a vision-based approach to prevent dangerous steering situations when riding a motorcycle in turns. The proposed algorithm is capable of detecting under, neutral or over-steering behavior using only a conventional camera and an inertial measurement unit. The inverse perspective mapping technique is used to reconstruct a bird-eye-view of the road image. Then, filters are applied to keep only the road markers which are, afterwards, approximated with the well-known clothoid model. This allows the prediction of the road geometry such as the curvature ahead of the motorcycle. Finally, from the predicted road curvature, the measurements of the Euler angles and the vehicle speed, the proposed algorithm is able to characterize the steering behavior. To that end, we propose to estimate the steering ratio and we introduce new pertinent indicators such as the vehicle relative position dynamics to the road. The method is validated using the advanced simulator BikeSim during a steady turn