A Bio Inspired Smart Security Model For Pervasive Smart Environment

Location-aware computing is a technology that uses the location (provides granular geographical information) of people and objects to derive contextual information. Today, one can obtain this location information free of cost through smartphones. Smartphones with location enabled applications have revolutionized the ways in which people perform their activities and get benefits from the automated services. It especially helps to get details of services in less time; wherever the user may be and whenever they want. The need for smartphones and location enabled applications has been growing year after year. Nowadays no one can leave without their phone; the phone seemingly becomes one of the parts of the human body. The individual can now be predicted by their phone and the identity of the phone becomes the person’s identity. Though there is a tremendous need for location-enabled applications with smartphones, the debate on privacy and security related to location data has also been growing. Privacy and Security Challenges in Location Aware Computing provides the latest research on privacy enhanced location-based applications development and exposes the necessity of location privacy preservation, as well as issues and challenges related to protecting the location data. It also suggests solutions for enhancing the protection of location privacy and therefore users’ privacy as well. The chapters highlight important topic areas such as video surveillance in human tracking/detection, geographical information system design, cyberspace attacks and warfare, and location aware security systems. The culmination of these topics creates a book that is ideal for security analysts, mobile application developers, practitioners, academicians, students, and researchers.

This book constitutes the refereed proceedings of the 7th International Conference on Distributed, Ambient and Pervasive Interactions, DAPI 2019, held as part of the 21st International Conference on Human-Computer Interaction, HCII 2019, in Orlando, Florida, USA, in July 2019. A total of 1274 papers and 209 posters have been accepted for publication in the HCII 2019 proceedings from a total of 5029 submissions. The 36 papers included in this volume were organized in topical sections on IoT and big data; smart cities and built environments; perception and emotion in DAPI; and DAPI for health and learning.

A guide to intelligent decision and pervasive computing paradigms for healthcare analytics systems with a focus on the use of bio-sensors Intelligent Pervasive Computing Systems for Smarter Healthcare describes the innovations in healthcare made possible by computing through bio-sensors. The pervasive computing paradigm offers tremendous advantages in diversified areas of healthcare research and technology. The authors—noted experts in the field—provide the state-of-the-art intelligence paradigm that enables optimization of medical assessment for a healthy, authentic, safer, and more productive environment. Today’s computers are integrated through bio-sensors and generate a huge amount of information that can enhance our ability to process enormous bio-informatics data that can be transformed into meaningful medical knowledge and help with diagnosis, monitoring and tracking health issues, clinical decision making, early detection of infectious disease prevention, and rapid analysis of health hazards. The text examines a wealth of topics such as the design and development of pervasive healthcare technologies, data modeling and information management, wearable biosensors and their systems, and more. This important resource: Explores the recent trends and developments in computing through bio-sensors and its technological applications Contains a review of biosensors and sensor systems and networks for mobile health monitoring Offers an opportunity for readers to examine the concepts and future outlook of intelligence on healthcare systems incorporating biosensor applications Includes information on privacy and security issues on wireless body area network for remote healthcare monitoring Written for scientists and application developers and professionals in related fields, Intelligent Pervasive Computing Systems for Smarter Healthcare is a guide to the most recent developments in intelligent computer systems that are applicable to the healthcare industry.

Minimize Power Consumption and Enhance User ExperienceEssential for high-speed fifth-generation mobile networks, mobile cloud computing (MCC) integrates the power of cloud data centers with the portability of mobile computing devices. Mobile Cloud Computing: Architectures, Algorithms and Applications covers the latest technological and architectura

This comprehensive book focuses on better big-data security for healthcare organizations. Following an extensive introduction to the Internet of Things (IoT) in healthcare including challenging topics and scenarios, it offers an in-depth analysis of medical body area networks with the 5th generation of IoT communication technology along with its nanotechnology. It also describes a novel strategic framework and computationally intelligent model to measure possible security vulnerabilities in the context of e-health. Moreover, the book addresses healthcare systems that handle large volumes of data driven by patients’ records and health/personal information, including big-data-based knowledge management systems to support clinical decisions. Several of the issues faced in storing/processing big data are presented along with the available tools, technologies and algorithms to deal with those problems as well as a case study in healthcare analytics. Addressing trust, privacy, and security issues as well as the IoT and big-data challenges, the book highlights the advances in the field to guide engineers developing different IoT devices and evaluating the performance of different IoT techniques. Additionally, it explores the impact of such technologies on public, private, community, and hybrid scenarios in healthcare. This book offers professionals, scientists and engineers the latest technologies, techniques, and strategies for IoT and big data.

This book constitutes the refereed proceedings of the First International Workshop on Engineering Multi-Agent Systems, EMAS 2013, held in St. Paul, MN, USA, in May 2013. The 19 full papers were carefully reviewed and selected from 30 submissions. The focus of the papers is on following topics: agent-oriented software engineering, declarative agent languages and technologies, and programming multi-agent systems.

A new era of complexity science is emerging, in which nature- and bio-inspired principles are being applied to provide solutions. At the same time, the complexity of systems is increasing due to such models like the Internet of Things (IoT) and fog computing. Will complexity science, applying the principles of nature, be able to tackle the challenges posed by highly complex networked systems? Bio-Inspired Optimization in Fog and Edge Computing: Principles, Algorithms, and Systems is an attempt to answer this question. It presents innovative, bio-inspired solutions for fog and edge computing and highlights the role of machine learning and informatics. Nature- or biological-inspired techniques are successful tools to understand and analyze a collective behavior. As this book demonstrates, algorithms, and mechanisms of self-organization of complex natural systems have been used to solve optimization problems, particularly in complex systems that are adaptive, ever-evolving, and distributed in nature. The chapters look at ways of enhancingto enhance the performance of fog networks in real-world applications using nature-based optimization techniques. They discuss challenges and provide solutions to the concerns of security, privacy, and power consumption in cloud data center nodes and fog computing networks. The book also examines how: The existing fog and edge architecture is used to provide solutions to future challenges. A geographical information system (GIS) can be used with fog computing to help users in an urban region access prime healthcare. An optimization framework helps in cloud resource management. Fog computing can improve the quality, quantity, long-term viability, and cost-effectiveness in agricultural production. Virtualization can support fog computing, increase resources to be allocated, and be applied to different network layers. The combination of fog computing and IoT or cloud computing can help healthcare workers predict and analyze diseases in patients.