An expert on computer privacy and security shows how we can build privacy into the design of systems from the start. We are tethered to our devices all day, every day, leaving data trails of our searches, posts, clicks, and communications. Meanwhile, governments and businesses collect our data and use it to monitor us without our knowledge. So we have resigned ourselves to the belief that privacy is hard--choosing to believe that websites do not share our information, for example, and declaring that we have nothing to hide anyway. In this informative and illuminating book, a computer privacy and security expert argues that privacy is not that hard if we build it into the design of systems from the start. Along the way, Jaap-Henk Hoepman debunks eight persistent myths surrounding computer privacy. The website that claims it doesn't collect personal data, for example; Hoepman explains that most data is personal, capturing location, preferences, and other information. You don't have anything to hide? There's nothing wrong with wanting to keep personal information--even if it's not incriminating or embarrassing--private. Hoepman shows that just as technology can be used to invade our privacy, it can be used to protect it, when we apply privacy by design. Hoepman suggests technical fixes, discussing pseudonyms, leaky design, encryption, metadata, and the benefits of keeping your data local (on your own device only), and outlines privacy design strategies that system designers can apply now.

This book constitutes the refereed proceedings of the First International Conference on Human Aspects of Information Security, Privacy and Trust, HAS 2013, held as part of the 15th International Conference on Human-Computer Interaction, HCII 2013, held in Las Vegas, USA in July 2013, jointly with 12 other thematically similar conferences. The total of 1666 papers and 303 posters presented at the HCII 2013 conferences was carefully reviewed and selected from 5210 submissions. These papers address the latest research and development efforts and highlight the human aspects of design and use of computing systems. The papers accepted for presentation thoroughly cover the entire field of human-computer interaction, addressing major advances in knowledge and effective use of computers in a variety of application areas. The total of 39 contributions was carefully reviewed and selected for inclusion in the HAS proceedings. The papers are organized in the following topical sections: novel authentication systems; human factors in security; security and privacy policies; and user centric security and privacy.

Global Perspectives in Information Security, compiled by renowned expert and professor Hossein Bidgoli, offers an expansive view of current issues in information security. Written by leading academics and practitioners from around the world, this thorough resource explores and examines a wide range of issues and perspectives in this rapidly expanding field. Perfect for students, researchers, and practitioners alike, Professor Bidgoli's book offers definitive coverage of established and cutting-edge theory and application in information security.

Discusses such electronic privacy concerns as what privacy is, how it relates to individuals, laws and regulations, identity theft, monitoring devices, and how to protect Internet transactions.

Security, privacy, and trust in the Internet of Things (IoT) and CPS (Cyber-Physical Systems) are different from conventional security as concerns revolve around the collection and aggregation of data or transmission of data over the network. Analysis of cyber-attack vectors and the provision of appropriate mitigation techniques are essential research areas for these systems. Adoption of best practices and maintaining a balance between ease of use and security are, again, crucial for the effective performance of these systems. Recent Advances in Security, Privacy and Trust for Internet of Things (IoT) and Cyber-Physical Systems (CPS) discusses and presents techniques and methodologies, as well as a wide range of examples and illustrations, to effectively show the principles, algorithms, challenges, and applications of security, privacy, and trust for IoT and CPS. Book features: Introduces new directions for research, development, and engineering security, privacy, and trust of IoT and CPS Includes a wealth of examples and illustrations to effectively demonstrate the principles, algorithms, challenges, and applications Covers most of the important security aspects and current trends not present in other reference books This book will also serve as an excellent reference in security, privacy, and trust of IoT and CPS for professionals in this fast-evolving and critical field. The chapters present high-quality contributions from researchers, academics, and practitioners from various national and international organizations and universities.

The increase in connected devices in the internet of things (IoT) is leading to an exponential increase in the data that an organization is required to manage. To successfully utilize IoT in businesses, big data analytics are necessary in order to efficiently sort through the increased data. The combination of big data and IoT can thus enable new monitoring services and powerful processing of sensory data streams. The Handbook of Research on Big Data and the IoT is a pivotal reference source that provides vital research on emerging trends and recent innovative applications of big data and IoT, challenges facing organizations and the implications of these technologies on society, and best practices for their implementation. While highlighting topics such as bootstrapping, data fusion, and graph mining, this publication is ideally designed for IT specialists, managers, policymakers, analysts, software engineers, academicians, and researchers.

Big Data: Principles and Paradigms captures the state-of-the-art research on the architectural aspects, technologies, and applications of Big Data. The book identifies potential future directions and technologies that facilitate insight into numerous scientific, business, and consumer applications. To help realize Big Data's full potential, the book addresses numerous challenges, offering the conceptual and technological solutions for tackling them. These challenges include life-cycle data management, large-scale storage, flexible processing infrastructure, data modeling, scalable machine learning, data analysis algorithms, sampling techniques, and privacy and ethical issues. - Covers computational platforms supporting Big Data applications - Addresses key principles underlying Big Data computing - Examines key developments supporting next generation Big Data platforms - Explores the challenges in Big Data computing and ways to overcome them - Contains expert contributors from both academia and industry