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Author: Jiadi Yu
Publisher: Springer Nature
ISBN: 9819959144
Category : Computers
Languages : en
Pages : 105
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Book Description
As a privacy-preserving and illumination-robust manner, WiFi signal-based user authentication has become a new direction for ubiquitous user authentication to protect user privacy and security. It gradually turns into an important option for addressing the security concern of IoT environment. However, due to the limited sensing capability of WiFi signals and wide application scenarios, WiFi signal-based user authentication suffers from practical issues of diversified behaviors and complex scenarios. Therefore, it is necessary to address the issues and build integrated systems for user authentication using WiFi signals. In this book, the development and progress of WiFi signal-based user authentication systems in extensive scenarios are presented, which provides a new direction and solution for ubiquitous security and privacy protection. This book gives strong motivation of leveraging WiFi signals to sense human activities for user authentication, and presents the key issues of WiFi-based user authentication in diversified behaviors and complex scenarios. This book provides the approaches for digging WiFi signals to sense human activities and extract features, realizing user authentication under fine-grained finger gestures, undefined body gestures, and multi-user scenarios. State-of-the-art researches and future directions involved with WiFi signal-based user authentication are presented and discussed as well. This book will benefit researchers and practitioners in the related field.
Author: Jiadi Yu
Publisher: Springer Nature
ISBN: 9819959144
Category : Computers
Languages : en
Pages : 105
Get Book Here
Book Description
As a privacy-preserving and illumination-robust manner, WiFi signal-based user authentication has become a new direction for ubiquitous user authentication to protect user privacy and security. It gradually turns into an important option for addressing the security concern of IoT environment. However, due to the limited sensing capability of WiFi signals and wide application scenarios, WiFi signal-based user authentication suffers from practical issues of diversified behaviors and complex scenarios. Therefore, it is necessary to address the issues and build integrated systems for user authentication using WiFi signals. In this book, the development and progress of WiFi signal-based user authentication systems in extensive scenarios are presented, which provides a new direction and solution for ubiquitous security and privacy protection. This book gives strong motivation of leveraging WiFi signals to sense human activities for user authentication, and presents the key issues of WiFi-based user authentication in diversified behaviors and complex scenarios. This book provides the approaches for digging WiFi signals to sense human activities and extract features, realizing user authentication under fine-grained finger gestures, undefined body gestures, and multi-user scenarios. State-of-the-art researches and future directions involved with WiFi signal-based user authentication are presented and discussed as well. This book will benefit researchers and practitioners in the related field.
Author: Cliff Wang
Publisher: Springer
ISBN: 3030105970
Category : Computers
Languages : en
Pages : 270
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Book Description
This book discusses and summarizes current research issues, identifies challenges, and outlines future directions for proactive and dynamic network defense. This book also presents the latest fundamental research results toward understanding proactive and dynamic network defense by top researchers in related areas. It includes research results that offer formal frameworks to define proactive and dynamic network defense, and develop novel models to analyze and evaluate proactive designs and strategies in computer systems, network systems, cyber-physical systems and wireless networks. A wide variety of scientific techniques have been highlighted to study these problems in the fundamental domain. As the convergence of our physical and digital worlds grows fast pace, protecting information systems from being tampered or unauthorized access is becoming one of the most importance issues. The traditional mechanisms of network defense are built upon a static, passive, and reactive nature, which has insufficient to defend against today's attackers that attempt to persistently analyze, probe, circumvent or fool such mechanisms. It has not yet been fully investigated to address the early stage of “cyber kill chain” when adversaries carry out sophisticated reconnaissance to plan attacks against a defense system. Recently, proactive and dynamic network defense has been proposed as an important alternative towards comprehensive network defense. Two representative types of such defense are moving target defense (MTD) and deception-based techniques. These emerging approaches show great promise to proactively disrupt the cyber-attack kill chain and are increasingly gaining interest within both academia and industry. However, these approaches are still in their preliminary design stage. Despite the promising potential, there are research issues yet to be solved regarding the effectiveness, efficiency, costs and usability of such approaches. In addition, it is also necessary to identify future research directions and challenges, which is an essential step towards fully embracing proactive and dynamic network defense. This book will serve as a great introduction for advanced-level computer science and engineering students who would like to start R&D efforts in the field of proactive and dynamic network defense. Researchers and professionals who work in this related field will also find this book useful as a reference.
Author: Zubair Md. Fadlullah
Publisher: Springer Nature
ISBN: 3030356426
Category : Computers
Languages : en
Pages : 271
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Book Description
This book addresses the key security challenges in the big data centric computing and network systems, and discusses how to tackle them using a mix of conventional and state-of-the-art techniques. The incentive for joining big data and advanced analytics is no longer in doubt for businesses and ordinary users alike. Technology giants like Google, Microsoft, Amazon, Facebook, Apple, and companies like Uber, Airbnb, NVIDIA, Expedia, and so forth are continuing to explore new ways to collect and analyze big data to provide their customers with interactive services and new experiences. With any discussion of big data, security is not, however, far behind. Large scale data breaches and privacy leaks at governmental and financial institutions, social platforms, power grids, and so forth, are on the rise that cost billions of dollars. The book explains how the security needs and implementations are inherently different at different stages of the big data centric system, namely at the point of big data sensing and collection, delivery over existing networks, and analytics at the data centers. Thus, the book sheds light on how conventional security provisioning techniques like authentication and encryption need to scale well with all the stages of the big data centric system to effectively combat security threats and vulnerabilities. The book also uncovers the state-of-the-art technologies like deep learning and blockchain which can dramatically change the security landscape in the big data era.
Author: Sheng Zhong
Publisher: Springer
ISBN: 303001150X
Category : Computers
Languages : en
Pages : 194
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Book Description
This timely book provides broad coverage of security and privacy issues in the macro and micro perspective. In macroperspective, the system and algorithm fundamentals of next-generation wireless networks are discussed. In micro-perspective, this book focuses on the key secure and privacy techniques in different emerging networks from the interconnection view of human and cyber-physical world. This book includes 7 chapters from prominent international researchers working in this subject area. This book serves as a useful reference for researchers, graduate students, and practitioners seeking solutions to wireless security and privacy related issues Recent advances in wireless communication technologies have enabled the large-scale deployment of next-generation wireless networks, and many other wireless applications are emerging. The next generation of mobile networks continues to transform the way people communicate and access information. As a matter of fact, next-generation emerging networks are exploiting their numerous applications in both military and civil fields. For most applications, it is important to guarantee high security of the deployed network in order to defend against attacks from adversaries, as well as the privacy intrusion. The key target in the development of next-generation wireless networks is to promote the integration of the human, cyber, and physical worlds. Previous work in Cyber Physical Systems (CPS) considered the connection between the cyber world and the physical world. In the recent studies, human involvement brings new channels and initiatives in this interconnection. In this integration process, security and privacy are critical issues to many wireless network applications, and it is a paramount concern for the growth of next-generation wireless networks. This is due to the open nature of wireless communication and the involvement of humans. New opportunities for tackling these security and privacy issues in next-generation wireless networks will be achieved by leveraging the properties of interaction among human, computers and things.
Author: Shangguan Longfei
Publisher: Springer Nature
ISBN: 3031347765
Category : Computers
Languages : en
Pages : 633
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Book Description
This book constitutes the refereed post-conference proceedings of the 19th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2022, which was held in Pittsburgh, November 14-17, 2022. The conference was held virtually due to the COVID-19 pandemic. The 26 full and 2 short papers were carefully reviewed and selected from 95 submissions and present discussions, They were organized in topical sections as follows: Internet of Things (IoT), Security and Privacy, Human-centric sensing, Drone applications and edge computing, Wireless networks, Mobile and human computer interactions, Poster and demo sessions, Technology for health
Author: Luxmi Sapra
Publisher: CRC Press
ISBN: 1000934047
Category : Computers
Languages : en
Pages : 133
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Book Description
Security implementation is crucial in the Internet of Medical Things (IoMT) as it ensures the protection of sensitive medical data and prevents unauthorized access to or manipulation of devices and systems. This book covers different aspects of security implementations and challenges in IoMT and aims to bring researchers together to contribute their findings to recommend new methodologies and feasible solutions for implementing security and novel architectures in artificial intelligence, machine learning, and data science in the field of healthcare and IoT. IoMT includes a wide range of connected medical devices and systems, such as wearable devices, medical sensors, and electronic health records, that collect, store, and share sensitive medical information. Without proper security measures, this information could be compromised, leading to serious privacy breaches, financial fraud, and even physical harm to patients.
Author:
Publisher:
ISBN:
Category : Technology
Languages : en
Pages : 68
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Book Description
Author: Zhen Cui
Publisher: Frontiers Media SA
ISBN: 2832526365
Category : Science
Languages : en
Pages : 151
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Book Description
Affective computing refers to computing that relates to, arises from, or influences emotions. The goal of affective computing is to bridge the gap between humans and machines and ultimately endow machines with emotional intelligence for improving natural human-machine interaction. In the context of human-robot interaction (HRI), it is hoped that robots can be endowed with human-like capabilities of observation, interpretation, and emotional expression. The research on affective computing has recently achieved extensive progress with many fields contributing including neuroscience, psychology, education, medicine, behavior, sociology, and computer science. Current research in affective computing concentrates on estimating human emotions through different forms of signals such as speech, face, text, EEG, fMRI, and many others. In neuroscience, the neural mechanisms of emotion are explored by combining neuroscience with the psychological study of personality, emotion, and mood. In psychology and philosophy, emotion typically includes a subjective, conscious experience characterized primarily by psychophysiological expressions, biological reactions, and mental states. The multi-disciplinary features of understanding “emotion” result in the fact that inferring the emotion of humans is definitely difficult. As a result, a multi-disciplinary approach is required to facilitate the development of affective computing. One of the challenging problems in affective computing is the affective gap, i.e., the inconsistency between the extracted feature representations and subjective emotions. To bridge the affective gap, various hand-crafted features have been widely employed to characterize subjective emotions. However, these hand-crafted features are usually low-level, and they may hence not be discriminative enough to depict subjective emotions. To address this issue, the recently-emerged deep learning (also called deep neural networks) techniques provide a possible solution. Due to the used multi-layer network structure, deep learning techniques are capable of learning high-level contributing features from a large dataset and have exhibited excellent performance in multiple application domains such as computer vision, signal processing, natural language processing, human-computer interaction, and so on. The goal of this Research Topic is to gather novel contributions on deep learning techniques applied to affective computing across the diverse fields of psychology, machine learning, neuroscience, education, behavior, sociology, and computer science to converge with those active in other research areas, such as speech emotion recognition, facial expression recognition, Electroencephalogram (EEG) based emotion estimation, human physiological signal (heart rate) estimation, affective human-robot interaction, multimodal affective computing, etc. We welcome researchers to contribute their original papers as well as review articles to provide works regarding the neural approach from computation to affective computing systems. This Research Topic aims to bring together research including, but not limited to: • Deep learning architectures and algorithms for affective computing tasks such as emotion recognition from speech, face, text, EEG, fMRI, and many others. • Explainability of deep Learning algorithms for affective computing. • Multi-task learning techniques for emotion, personality and depression detection, etc. • Novel datasets for affective computing • Applications of affective computing in robots, such as emotion-aware human-robot interaction and social robots, etc.
Author: Lei Wang
Publisher: Springer Nature
ISBN: 9819710103
Category :
Languages : en
Pages : 329
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Book Description
Author: Yan Meng
Publisher: Springer Nature
ISBN: 3031241851
Category : Technology & Engineering
Languages : en
Pages : 177
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Book Description
This book presents the security and privacy challenges of the smart home following the logic of “terminal device – voice interface – application platform”. For each component, the authors provide answers to the three questions: 1) In the terminal device layer, how to conduct cross-layer privacy breach analysis and provide effective countermeasures; 2) In the voice interface layer, how to design effective and lightweight schemes to defend against voice spoofing; 3) In the application layer, how to design an effective anomaly detection system without breaching the application platform. The authors conduct a thorough analysis of the security threats and challenges in each component of the smart home, review the existing state-of-the-art solutions proposed by other researchers, and elaborate on proposed countermeasures. This book aims to provide both security threats analysis and state-of-the-art countermeasures for the smart home network.
