The world has become a small village. The internet has played an important role in the communications revolution. It facilitates the management of institutions and organizations in many countries. Due to advances in using multimedia streaming (especially video), it becomes important to secure real time video transmission.
Securing video depends on many factors. The key two factors are: the complexity of encryption algorithm and time to break the encryption by hackers or competitors.
There are two main components for securing multimedia transmissions: security protocols and text encryption algorithms. Security protocols have been used to provide security and data integrity for communications over IP networks. Text encryption algorithms have been used for encrypting and decrypting video frames.
This thesis proposed a security scheme for streamed video frames over IP network. We used Datagram Transport Layer Security (DTLS) protocol. We applied the most four famous text encryption algorithms on video frames. These algorithms are Advanced Encryption Standard (AES), Data Encryption Standard (DES), Triple Data Encryption Standard (3DES) and Blowfish. They were used to determine the most suitable one to be selected to secure video frames. We compared our results with previous results on video frames encryption. We also modified the Real-time Transport Protocol (RTP) to adapt the proposed security scheme. RTP is used as a standardized packet format for delivering video over the IP networks. Our proposed scheme would be feasible for real time applications without any extra dedicated hardware.
After determining the most suitable encryption algorithm, we compared the proposed security scheme with normal video transmission scheme according to the following parameters: Frame Loss, Packet Loss and Data Rate. We evaluated the overheads of the proposed scheme. We also studied the impact of frame rate on securing real time video transmission over IP networks.
We used JAVA programming language to develop the proposed scheme. We found that the secured connection setup needed more time than normal one. The secured setup time is an offline process, so it does not affect the transmission of video frames in the real time. Using random generated keys for encryption process for every connection makes attacks harder to happen. The AES algorithm is considered the most suitable text encryption algorithm to be used in video, as it achieves less encryption time per frame. We found that the size of the overhead was very small compared to video original size.
Finally, we studied the impact of frame rate on securing real time video streaming. We determined the best frame rate needed to achieve fewer frame, packet loss and best quality on video.

Beyond human knowledge and reach, robotics is strongly involved in tackling challenges of new emerging multidisciplinary fields. Together with humans, robots are busy exploring and working on the new generation of ideas and problems whose solution is otherwise impossible to find. The future is near when robots will sense, smell and touch people and their lives. Behind this practical aspect of human-robotics, there is a half a century spanned robotics research, which transformed robotics into a modern science. The Advances in Robotics and Virtual Reality is a compilation of emerging application areas of robotics. The book covers robotics role in medicine, space exploration and also explains the role of virtual reality as a non-destructive test bed which constitutes a premise of further advances towards new challenges in robotics. This book, edited by two famous scientists with the support of an outstanding team of fifteen authors, is a well suited reference for robotics researchers and scholars from related disciplines such as computer graphics, virtual simulation, surgery, biomechanics and neuroscience.

In recent years, the development of distributed systems, in particular the Internet, has been influenced heavily by three paradigms: peer-to-peer, autonomous agents, and service orientation. Developing Advanced Web Services through P2P Computing and Autonomous Agents: Trends and Innovations establishes an understanding of autonomous peer-to-peer Web Service models and developments as well as extends growing literature on emerging technologies. This scholarly publication is an important reference for researchers and academics working in the fields of peer-to-peer computing, Web and grid services, and agent technologies.

Social networks provide a powerful abstraction of the structure and dynamics of diverse kinds of people or people-to-technology interaction. Web 2.0 has enabled a new generation of web-based communities, social networks, and folksonomies to facilitate collaboration among different communities. This unique text/reference compares and contrasts the ethological approach to social behavior in animals with web-based evidence of social interaction, perceptual learning, information granulation, the behavior of humans and affinities between web-based social networks. An international team of leading experts present the latest advances of various topics in intelligent-social-networks and illustrates how organizations can gain competitive advantages by applying the different emergent techniques in real-world scenarios. The work incorporates experience reports, survey articles, and intelligence techniques and theories with specific network technology problems.

This book presents cutting-edge research in the field of semantic technologies. Its seventeen chapters are arranged into four parts and identify interdisciplinary challenges in the areas of the Semantic Web, artificial intelligence, and knowledge-based services. The chapters provide analysis and insight into semantic Web techniques and are authored by reputable scientists in the field. All articles are self-contained to provide the greatest reading flexibility and aim to serve as a reference for researchers in the Semantic Web community.

World Wide Web (WWW) provides interlinked hypertext documents (Web pages) that may contain text, images, videos, and other multimedia. WWW is growing at a remarkable rate and finding appropriate information can therefore be challenging. Web information retrieval deals with the search for documents, for information within documents and for metadata about documents, as well as that of searching databases in the WWW. Web information retrieval is an interdisciplinary science and deals with this challenge by exploiting various information technologies and computational intelligence approaches to design the next generation of web-information retrieval technologies. This Volume provides reviews of cutting-edge technologies and insights into various topics related to XML-based and multimedia information access and retrieval under the umbrella of Web Intelligence, it also illustrates how organizations can gain competitive advantages by applying new techniques in real-world scenarios. The 18 chapters are arranged in three parts and have identified several important problem formulations in the area of Web and multimedia information querying, modelling user interactions and advanced information security and access control models. Chapters are authored by reputed scientists in the field and all articles are self-contained to provide the greatest reading flexibility.

Learning methods and approximation algorithms are fundamental tools that deal with computationally hard problems and problems in which the input is gradually disclosed over time. Both kinds of problems have a large number of applications arising from a variety of fields, such as algorithmic game theory, approximation classes, coloring and partitioning, competitive analysis, computational finance, cuts and connectivity, geometric problems, inapproximability results, mechanism design, network design, packing and covering, paradigms for design and analysis of approximation and online algorithms, randomization techniques, real-world applications, scheduling problems and so on. The past years have witnessed a large number of interesting applications using various techniques of Computational Intelligence such as rough sets, connectionist learning; fuzzy logic; evolutionary computing; artificial immune systems; swarm intelligence; reinforcement learning, intelligent multimedia processing etc.. In spite of numerous successful applications of Computational Intelligence in business and industry, it is sometimes difficult to explain the performance of these techniques and algorithms from a theoretical perspective. Therefore, we encouraged authors to present original ideas dealing with the incorporation of different mechanisms of Computational Intelligent dealing with Learning and Approximation algorithms and underlying processes.

Human reasoning usually is very approximate and involves various types of uncertainties. Approximate reasoning is the computational modelling of any part of the process used by humans to reason about natural phenomena or to solve real world problems. The scope of this book includes fuzzy sets, Dempster-Shafer theory, multi-valued logic, probability, random sets, and rough set, near set and hybrid intelligent systems. Besides research articles and expository papers on theory and algorithms of approximation reasoning, papers on numerical experiments and real world applications were also encouraged. This Volume comprises of 12 chapters including an overview chapter providing an up-to-date and state-of-the research on the applications of Computational Intelligence techniques for approximation reasoning. The Volume is divided into 2 parts: Part-I: Approximate Reasoning – Theoretical Foundations and Part-II: Approximate Reasoning – Success Stories and Real World Applications

Global optimization is a branch of applied mathematics and numerical analysis that deals with the task of finding the absolutely best set of admissible conditions to satisfy certain criteria / objective function(s), formulated in mathematical terms. Global optimization includes nonlinear, stochastic and combinatorial programming, multiobjective programming, control, games, geometry, approximation, algorithms for parallel architectures and so on. Due to its wide usage and applications, it has gained the attention of researchers and practitioners from a plethora of scientific domains. Typical practical examples of global optimization applications include: Traveling salesman problem and electrical circuit design (minimize the path length); safety engineering (building and mechanical structures); mathematical problems (Kepler conjecture); Protein structure prediction (minimize the energy function) etc.

Computational tools or solutions based on intelligent systems are being used with great success in Data Mining applications. Nature has been very successful in providing clever and efficient solutions to different sorts of challenges and problems posed to organisms by ever-changing and unpredictable environments. It is easy to observe that strong scientific advances have been made when issues from different research areas are integrated. A particularly fertile integration combines biology and computing. Computational tools inspired on biological process can be found in a large number of applications. One of these applications is Data Mining, where computing techniques inspired on nervous systems; swarms, genetics, natural selection, immune systems and molecular biology have provided new efficient alternatives to obtain new, valid, meaningful and useful patterns in large datasets.