Data Confidentiality in Mobile Ad hoc Networks

Mobile ad hoc networks (MANETs) are self-configuring infrastructure-less networks comprised of mobile nodes that communicate over wireless links without any central control on a peer-to-peer basis. These individual nodes act as routers to forward both their own data and also their neighbours' data by sending and receiving packets to and from other nodes in the network. The relatively easy configuration and the quick deployment make ad hoc networks suitable the emergency situations (such as human or natural disasters) and for military units in enemy territory. Securing data dissemination between these nodes in such networks, however, is a very challenging task. Exposing such information to anyone else other than the intended nodes could cause a privacy and confidentiality breach, particularly in military scenarios. In this paper we present a novel framework to enhance the privacy and data confidentiality in mobile ad hoc networks by attaching the originator policies to the messages as they are sent between nodes. We evaluate our framework using the Network Simulator (NS-2) to check whether the privacy and confidentiality of the originator are met. For this we implemented the Policy Enforcement Points (PEPs), as NS-2 agents that manage and enforce the policies attached to packets at every node in the MANET.Comment: 12 page

QoS-aware Storage Virtualization: A Framework for Multi-tier Infrastructures in Cloud Storage Systems

The emergence of the relatively modern phenomenon of cloud computing has manifested a different approach to the availability and storage of software and data on a remote online server ‘in the cloud’, which can be accessed by pre-determined users through the Internet, even allowing sharing of data in certain scenarios. Data availability, reliability, and access performance are three important factors that need to be taken into consideration by cloud providers when designing a high-performance storage system for any organization. Due to the high costs of maintaining and managing multiple local storage systems, it is now considered more applicable to design a virtualized multi-tier storage infrastructure, yet, the existing Quality of Service (QoS) must be guaranteed on the application level within the cloud without ongoing human intervention. Such interference seems necessary since the delivered QoS can vary widely both across and within storage tiers, depending on the access profile of the data. This survey paper encompasses a general framework for the optimal design of a distributed system in order to attain efficient data availability and reliability. To this extent, numerous state-of-the-art technologies and methods have been revised, especially for multi-tiered distributed cloud systems. Moreover, several critical aspects that must be taken into consideration for getting optimal performance of QoS-aware cloud systems are discussed, highlighting some solutions to handle failure situations, and the possible advantages and benefits of QoS. Finally, this papers attempts to argue the possible improvements that have been developed on QoS-aware cloud systems like Q-cloud since 2010, such as any extra attempts been carried forward to make the Q-cloud more adaptable and secure

Cassini-Huygens mission images classification framework by deep learning advanced approach

Developing a deep learning (DL) model for image classification commonly demands a crucial architecture organization. Planetary expeditions produce a massive quantity of data and images. However, manually analyzing and classifying flight missions image databases with hundreds of thousands of images is ungainly and yield weak accuracy. In this paper, we speculate an essential topic related to the classification of remotely sensed images, in which the process of feature coding and extraction are decisive procedures. Diverse feature extraction techniques are intended to stimulate a discriminative image classifier. Features extraction is the primary engagement in raw data processing with the purpose of data classification; when it comes across the task of analysis of vast and varied data, these kinds of tasks are considered as time-consuming and hard to be treated with. Most of these classifiers are either, in principle, quite intricate or virtually unattainable to calculate for massive datasets. Stimulated by this perception, we put forward a straightforward, efficient classifier based on feature extraction by analyzing the cell of tensors via layered MapReduce framework beside meta-learning LSTM followed by a SoftMax classifier. Experiment results show that the provided model attains a classification accuracy of 96.7%, which makes the provided model quite valid for diverse image databases with varying sizes

Securing Data Dissemination in Vehicular ad hoc Networks

Vehicular ad hoc networks (VANETs) are a subclass of mobile ad hoc networks (MANETs) in which the mobile nodes are vehicles; these vehicles are autonomous systems connected by wireless communication on a peer-to-peer basis. They are self-organized, self-configured and self-controlled infrastructure-less networks. This kind of network has the advantage of being able to be set-up and deployed anywhere and anytime because it has no infrastructure set-up and no central administration. Distributing information between these vehicles over long ranges in such networks, however, is a very challenging task, since sharing information always has a risk attached to it especially when the information is confidential. The disclosure of such information to anyone else other than the intended parties could be extremely damaging, particularly in military applications where controlling the dissemination of messages is essential. This thesis therefore provides a review of the issue of security in VANET and MANET; it also surveys existing solutions for dissemination control. It highlights a particular area not adequately addressed until now: controlling information flow in VANETs. This thesis contributes a policy-based framework to control the dissemination of messages communicated between nodes in order to ensure that message remains confidential not only during transmission, but also after it has been communicated to another peer, and to keep the message contents private to an originator-defined subset of nodes in the VANET. This thesis presents a novel framework to control data dissemination in vehicle ad hoc networks in which policies are attached to messages as they are sent between peers. This is done by automatically attaching policies along with messages to specify how the information can be used by the receiver, so as to prevent disclosure of the messages other than consistent with the requirements of the originator. These requirements are represented as a set of policy rules that explicitly instructs recipients how the information contained in messages can be disseminated to other nodes in order to avoid unintended disclosure. This thesis describes the data dissemination policy language used in this work; and further describes the policy rules in order to be a suitable and understandable language for the framework to ensure the confidentiality requirement of the originator. This thesis also contributes a policy conflict resolution that allows the originator to be asked for up-to-date policies and preferences. The framework was evaluated using the Network Simulator (NS-2) to provide and check whether the privacy and confidentiality of the originators’ messages were met. A policy-based agent protocol and a new packet structure were implemented in this work to manage and enforce the policies attached to packets at every node in the VANET. Some case studies are presented in this thesis to show how data dissemination can be controlled based on the policy of the originator. The results of these case studies show the feasibility of our research to control the data dissemination between nodes in VANETs. NS-2 is also used to test the performance of the proposed policy-based agent protocol and demonstrate its effectiveness using various network performance metrics (average delay and overhead)

The impact of population migrations in contemporary Amman city architecture

This research addresses the evolution stages of the city of Amman through the influence of the diverse population migrations in the city. The diverse styles were highlighted which accompanied the arrival of these immigrants from different places through the study of design trends and facades forms and architectural elements in terms of architectural patterns, architectural and interior distributions or construction techniques characterized by each stage. Amman had gone through periods of stability and turbulence throughout its long history, as Amman has embraced, the city of valleys and mountains, and springs of water, residential communities since the stone ages, but it has witnessed discontinuity spanned nearly four centuries. Hence, modern Amman has been formed by the advent of Circassians, and as a result of its falling under the rule of the Ottoman Empire, and with the establishment of the Hejaz Railway, which made Amman a station to attract immigrants from neighboring areas, all this gradually led to the formation of a modern image of Amman different from that prevailing before the end of the nineteenth century. Amman received many cultures and population assets, each one in turn led to leaving a trace in Amman architecture of its residential and public buildings alike, leading to the formation of a diverse Ammani's architectural identity. The study of it will determine whether Amman architecture is the result of the experiences and local cultures or the external factors have affected significantly in the formation of architectural fabric and the typical architecture. Keywords: history of Amman architecture, traditional architecture, contemporary architecture, the city of Amman

Finding the adequate location scenario after the merger of fire brigades thanks to Multiple Criteria Decision Analysis Methods

This paper addresses the issue of selecting a suitable location for a fire station in canton of Fribourg, as a result of a fire brigades’merger, by applying Multiple Criteria Decision Analysis (MCDA) methods. Solving the problem of determining fire station locations through various methods has been analyzed in-­‐depth by researchers. However, a different approach, based on application of methods like ELECTRE and PROMETHEE is advanced in this paper. The selection of the most suitable fire station site is obtained by applying the designated methods to five distinctive alternatives (called scenarios), taking into consideration the relatively limited information and specifics, and the extensive number of relevant criteria that summed up to seventy-­‐ eight. Taking the merger of the three local fire departments as an example, the proposed methods for selecting a suitable location for the fire station demonstrate and justify the reason behind this choice. Research shows that the applied methods have been proven to be useful and powerful tools that exhibited acceptable levels of consistency when selecting the best project. The main finding is that one scenario in particular proved to be strongly dominant over the others and most suitable in determining the fire station location

Applying HEC-RAS Software to Propose a Dam Site Along the Tigris River Between Mosul and Tikrit, Iraq

Tigris River is an important water body in Iraq for drinking, agricultural, industrial, and livestock uses. The river flows from Turkey to the Iraqi land at Fiesh-khabour district in the northern part of Iraq and flows into Mosul city. Therefore, this study aims to simulate the flow in the Tigris River using the latest version of the HEC-RAS model (v5.0.7). The calibration and verification of the model showed that the final Manning’s roughness coefficients (n) of the main channels for the Tigris River were 0.036 and 0.026 for Mosul and Tikrit sites respectively. The Results illustrated a very good agreement between the simulated and measured stages. The Root Mean Square Error RMSE, MAE, and Nash-Sutcliffe Efficiency Criteria NSE, tests were used for calibrating the unsteady state flow model where it served as a comparison of calculated water levels by the model for each of the Manning index values ‘n’ with the observed water levels as a function. The final Manning’s roughness coefficients (n) of the main channels for the Mosul and Tikrit sites were 0.036 and 0.026 respectively. It's suggested to construct of hydraulic structures such as a dam with a reservoir beside this area to operate water stations and electric turbinate’s and other projects built next to the river, such as irrigation projects. Recommended using the simulation of the present study in the future to study the effect of constructing a dam in the Tikrit region. In addition, the current simulation can be used in the future to study the TDS, transportation of sediment loads, or pollution along the river

Deep learning-based approach for detecting trajectory modifications of cassini-huygens spacecraft

There were necessary trajectory modifications of Cassini spacecraft during its last 14 years movement cycle of the interplanetary research project. In the scale 1.3 hour of signal propagation time and 1.4-billion-kilometer size of Earth-Cassini channel, complex event detection in the orbit modifications requires special investigation and analysis of the collected big data. The technologies for space exploration warrant a high standard of nuanced and detailed research. The Cassini mission has accumulated quite huge volumes of science records. This generated a curiosity derives mainly from a need to use machine learning to analyze deep space missions. For energy saving considerations, the communication between the Earth and Cassini was executed in non-periodic mode. This paper provides a sophisticated in-depth learning approach for detecting Cassini spacecraft trajectory modifications in post-processing mode. The proposed model utilizes the ability of Long Short Term Memory (LSTM) neural networks for drawing out useful data and learning the time series inner data pattern, along with the forcefulness of LSTM layers for distinguishing dependencies among the long-short term. Our research study exploited the statistical rates, Matthews correlation coefficient, and F1 score to evaluate our models. We carried out multiple tests and evaluated the provided approach against several advanced models. The preparatory analysis showed that exploiting the LSTM layer provides a notable boost in rising the detection process performance. The proposed model achieved a number of 232 trajectory modification detections with 99.98% accuracy among the last 13.35 years of the Cassini spacecraft life. © 2013 IEEE

Adopting E-Commerce to users’ needs

The objectives of this paper are to identify and analyse the extent to which the site is fulfilling all the user’s requirements and needs. The related works comprise the history of interactive design and the benefits of user-centered development, which is the methodology followed in this survey. Moreover, there is a brief comparison between Waterfall and User-centered methodology in terms of addressing the issues of time saving and addressing fulfilment of users’ needs. The data required to conduct this study was acquired using two research methods; the questionnaire and direct user observation, in order to address all the performance related attributes in the usability stage of the evaluation. An evaluation of the website, based on statements of usability goals and criteria, was undertaken in relation to the implementation and testing of the new design. JARIR bookstore website was chosen as a case study in this paper to investigate the usability and interactivity of the website design. The analysis section includes needs, users and tasks and data analysis, whereas the design phase covers the user interface and database design. At the end of this paper, some recommendations are presented regarding JARIR website that can be taken into account when developing the website in the future