IPTV Service Framework Based on Secure Authentication and Lightweight Content Encryption for Screen-Migration in Cloud Computing

These days, the advancing of smart devices (e.g. smart phones, tablets, PC, etc.) capabilities and the increase of internet bandwidth enables IPTV service provider to extend their services to smart mobile devices. User can just receive their IPTV service using any smart devices by accessing the internet via wireless network from anywhere anytime in the world which is convenience for users. However, wireless network communication has well a known critical security threats and vulnerabilities to user smart devices and IPTV service such as user identity theft, reply attack, MIM attack, and so forth. A secure authentication for user devices and multimedia protection mechanism is necessary to protect both user devices and IPTV services. As result, we proposed framework of IPTV service based on secure authentication mechanism and lightweight content encryption method for screen-migration in Cloud computing. We used cryptographic nonce combined with user ID and password to authenticate user device in any mobile terminal they passes by. In addition we used Lightweight content encryption to protect and reduce the content decode overload at mobile terminals. Our proposed authentication mechanism reduces the computational processing by 30% comparing to other authentication mechanism and our lightweight content encryption reduces encryption delay to 0.259 second

Characterization of bees algorithm into the Mahalanobis-Taguchi system for classification

Mahalanobis-Taguchi System (MTS) is a pattern recognition tool employing Mahalanobis Distance (MD) and Taguchi Robust Engineering philosophy to explore and exploit data in multidimensional systems. In order to improve recognition accuracy of the MTS, features that do not provide useful and beneficial information to the recognition function is removed. A matrix called Orthogonal Array (OA) to search for the useful features is utilized by MTS to accomplished the search. However, the deployment of OA as the feature selection search method is seen as ineffective. The fixed-scheme structure of the OA provides a non-heuristic search nature which leads to suboptimal solution. Therefore, it is the objective of this research to develop an algorithm utilizing Bees Algorithm (BA) to replace the OA. It will act as the alternative feature selection search strategy in order to enhance the search mechanism in a more heuristic manner. To understand the mechanism of the Bees Algorithm, the characteristics of the algorithmic nature of the algorithm is determined. Unlike other research reported in the literature, the proposed characterization framework is similar to Taguchi-sound approach because Larger the Better (LTB) type of signal-to-noise formulation is used as the algorithm’s objective function. The Smallest Position Value (SPV) discretization method is adopted by which the combinations of features are indexed in an enumeration list consisting of all possible feature combinations. The list formed a search landscape for the bee agents in exploring the potential solution. The proposed characterization framework is validated by comparing it against three different case studies, all focused on performance in terms of Signal-to-Noise Ratio gain (SNR gain), classification accuracy and computational speed against the OA. The results from the case studies showed that the characterization of the BA into the MTS framework improved the performance of the MTS particularly on the SNR gain. It recorded more than 50% improvement (on average) and nearly 4% improvement on the classification accuracy (on average) in comparison to the OA. However, the OA on average was found to be 30 times faster than the BA in terms of computational speed. Future research on improving the computational speed aspect of the BA is suggested. This study concludes that the characterization of BA into the MTS optimization methodology effectively improved the performances of the MTS, particularly with respect of the SNR gain performance and the classification accuracy when compared to the OA

Tyre print identification through registration techniques and attribute graphs

Tire tread classification problem is primarily of use in two areas. First and foremost, forensics. It could come of great use in a case involving motor vehicles to be able to at least determine what kind of tire has been in a crime scene, and subsequent analysis of the possible vehicles wearing that same tire. Secondly, it could also be used by tire manufacturers to prevent copyright infringement of a tire tread pattern. We want to think that given a proper use, this technique could be of help to forensic labs around the globe, and perhaps, on some extent, it could also be used on other fields of image recognition.Real world applications are always the highest motivation you can get. Being my first research paper I felt that focusing on a concrete and concise goal was of real help. We looked for a way to provide the user to identify a tire model, given a partial tire tread image from the ground. At least we need a way to guide him along and choose a few of the extensive database with probable solutions to the tire tread he is looking for and not having them to look for in a three hundred or more tire tread images. The concept of a partial tire tread image, is the key to this work, and what it makes it unique amongst other systems. Most existing systems work with a complete tire tread, but in most cases, all you can get is a small part of the complete tread. This is why we focused on proposing a solution able to work with just a part of it. On the other hand this also was also one of the major pitfalls we encountered. Not having the complete information of what we are looking for made all the existing research on tire tread matching unusable, leading us to start from the ground-up. We are looking for tire tread recognition in its full extent. We believe that any step we take to our final goal is welcome. Given that the user should be supervising the software already he could also be the one deciding which option is the best, given a current result presented in a correct fashion for him to do so. An exact matching would definitely be great but, as in most cases on computer vision field, this is nearly impossible

3D surface reconstruction for lower limb prosthetic model using modified radon transform

Computer vision has received increased attention for the research and innovation on three-dimensional surface reconstruction with aim to obtain accurate results. Although many researchers have come up with various novel solutions and feasibility of the findings, most require the use of sophisticated devices which is computationally expensive. Thus, a proper countermeasure is needed to resolve the reconstruction constraints and create an algorithm that is able to do considerably fast reconstruction by giving attention to devices equipped with appropriate specification, performance and practical affordability. This thesis describes the idea to realize three-dimensional surface of the residual limb models by adopting the technique of tomographic imaging coupled with the strategy based on multiple-views from a digital camera and a turntable. The surface of an object is reconstructed from uncalibrated two-dimensional image sequences of thirty-six different projections with the aid of Radon transform algorithm and shape-from-silhouette. The results show that the main objective to reconstruct three-dimensional surface of lower limb model has been successfully achieved with reasonable accuracy as the starting point to reconstruct three-dimensional surface and extract digital reading of an amputated lower limb model where the maximum percent error obtained from the computation is approximately 3.3 % for the height whilst 7.4%, 7.9% and 8.1% for the diameters at three specific heights of the objects. It can be concluded that the reconstruction of three-dimensional surface for the developed method is particularly dependent to the effects the silhouette generated where high contrast two-dimensional images contribute to higher accuracy of the silhouette extraction. The advantage of the concept presented in this thesis is that it can be done with simple experimental setup and the reconstruction of three-dimensional model neither involves expensive equipment nor require any service by an expert to handle sophisticated mechanical scanning system

IMPROVED LICENSE PLATE LOCALIZATION ALGORITHM BASED ON MORPHOLOGICAL OPERATIONS

Automatic License Plate Recognition (ALPR) systems have become an important tool to track stolen cars, access control, and monitor traffic. ALPR system consists of locating the license plate in an image, followed by character detection and recognition. Since the license plate can exist anywhere within an image, localization is the most important part of ALPR and requires greater processing time. Most ALPR systems are computationally intensive and require a high-performance computer. The proposed algorithm differs significantly from those utilized in previous ALPR technologies by offering a fast algorithm, composed of structural elements which more precisely conducts morphological operations within an image, and can be implemented in portable devices with low computation capabilities. The proposed algorithm is able to accurately detect and differentiate license plates in complex images. This method was first tested through MATLAB with an on-line public database of Greek license plates which is a popular benchmark used in previous works. The proposed algorithm was 100% accurate in all clear images, and achieved 98.45% accuracy when using the entire database which included complex backgrounds and license plates obscured by shadow and dirt. Second, the efficiency of the algorithm was tested in devices with low computational processing power, by translating the code to Python, and was 300% faster than previous work

Vision-based Detection of Mobile Device Use While Driving

The aim of this study was to explore the feasibility of an automatic vision-based solution to detect drivers using mobile devices while operating their vehicles. The proposed system comprises of modules for vehicle license plate localisation, driver’s face detection and mobile phone interaction. The system were then implemented and systematically evaluated using suitable image datasets. The strengths and weaknesses of individual modules were analysed and further recommendations made to improve the overall system’s performance

Privacy and confidentiality issues in cloud computing architectures

Cloud computing is a computing paradigm in which organizations can store their data remotely in the cloud (Internet) and access applications, services and infrastructure on-demand from a shared pool of computing resources. It is clear that cloud technologies have proven a major commercial success over recent years (since the appearance of products and cloud offerings like Amazon EC2 and Microsoft Azure). According to Gardner, Cloud Computing will play a large part in the ICT (Information and Communication Technologies) domain over the next 10 years or more, since it provides cost-savings to enterprises thanks to virtualization technologies, opening gates for new business opportunities as well. However, Cloud Computing has to face several challenges and issues. Storing and processing data out of the boundaries of your company raises security and privacy concerns by itself. Nowadays information is the commodity of XXI century, and certain information can mean power and market advantage. As pointed out by Andreas Weiss, Director of the EuroCloud, in an interview we held with him, data is one of the most important and valuable resource any company has. Therefore, security mechanisms to protect this data are necessary to make the right choices and decisions for the company without worrying about data safety. In the paradigm of Cloud Computing we will have to trust a Cloud Service Provider (CSP), creating an extra dependency to a third party which some customers, depending on the value of their data, will inevitably feel uncomfortable. Outsourcing business data in a place not owned by oneself can scare organizations from using the benefits of Cloud Computing in an optimal way