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Handbook of Big Data Analytics and Forensics, Choo Kim-Kwang Raymond, Dehghantanha Ali


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Автор: Choo Kim-Kwang Raymond, Dehghantanha Ali
Название:  Handbook of Big Data Analytics and Forensics
ISBN: 9783030747527
Издательство: Springer
Классификация:



ISBN-10: 3030747522
Обложка/Формат: Hardcover
Страницы: 500
Вес: 0.59 кг.
Дата издания: 03.10.2021
Серия: Springer water
Язык: English
Издание: 1st ed. 2022
Иллюстрации: 77 illustrations, color; 11 illustrations, black and white; viii, 287 p. 88 illus., 77 illus. in color.; 77 illustrations, color; 11 illustrations, bl
Размер: 23.39 x 15.60 x 1.75 cm
Читательская аудитория: Professional & vocational
Подзаголовок: Workshops of the european conference on machine learning and knowledge discovery in databases (ecml pkdd 2020): sogood 2020, pdfl 2020, mlcs 2020, nfmcp 2020, dina 2020, edml 2020, xkdd 2020 and inra 2020, ghent, belgium, september 14-18, 2020, proce
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This handbook discusses challenges and limitations in existing solutions, and presents state-of-the-art advances from both academia and industry, in big data analytics and digital forensics. The second chapter comprehensively reviews IoT security, privacy, and forensics literature, focusing on IoT and unmanned aerial vehicles (UAVs). The authors propose a deep learning-based approach to process cloud’s log data and mitigate enumeration attacks in the third chapter. The fourth chapter proposes a robust fuzzy learning model to protect IT-based infrastructure against advanced persistent threat (APT) campaigns. Advanced and fair clustering approach for industrial data, which is capable of training with huge volume of data in a close to linear time is introduced in the fifth chapter, as well as offering an adaptive deep learning model to detect cyberattacks targeting cyber physical systems (CPS) covered in the sixth chapter. The authors evaluate the performance of unsupervised machine learning for detecting cyberattacks against industrial control systems (ICS) in chapter 7, and the next chapter presents a robust fuzzy Bayesian approach for ICS’s cyber threat hunting. This handbook also evaluates the performance of supervised machine learning methods in identifying cyberattacks against CPS. The performance of a scalable clustering algorithm for CPS’s cyber threat hunting and the usefulness of machine learning algorithms for MacOS malware detection are respectively evaluated. This handbook continues with evaluating the performance of various machine learning techniques to detect the Internet of Things malware. The authors demonstrate how MacOSX cyberattacks can be detected using state-of-the-art machine learning models. In order to identify credit card frauds, the fifteenth chapter introduces a hybrid model. In the sixteenth chapter, the editors propose a model that leverages natural language processing techniques for generating a mapping between APT-related reports and cyber kill chain. A deep learning-based approach to detect ransomware is introduced, as well as a proposed clustering approach to detect IoT malware in the last two chapters. This handbook primarily targets professionals and scientists working in Big Data, Digital Forensics, Machine Learning, Cyber Security Cyber Threat Analytics and Cyber Threat Hunting as a reference book. Advanced level-students and researchers studying and working in Computer systems, Computer networks and Artificial intelligence will also find this reference useful.
Дополнительное описание: 1. Big data analytics and forensics: an overview.- 2. Lot privacy, security and forensics challenges: an unmanned aerial vehicle (uav) case study.- 3. Detection of enumeration attacks in cloud environments using infrastructure log data.- 4.- Cyber threat



The 2020 International Conference on Machine Learning and Big Data Analytics for Iot Security and Privacy: Spiot-2020, Volume 2

Автор: Macintyre John, Zhao Jinghua, Ma Xiaomeng
Название: The 2020 International Conference on Machine Learning and Big Data Analytics for Iot Security and Privacy: Spiot-2020, Volume 2
ISBN: 3030627454 ISBN-13(EAN): 9783030627454
Издательство: Springer
Цена: 27950.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание:

Session 5: Data-driven co-design of communication, computing and control for IoT security

Design of a Force Balance Geophone Utilizing Bandwidth Extension and Data Acquisition Interface

Application of 3ds Max Technology in Archaeology

The Application of Virtual Reality Technology in ESP Teaching

Application of Simulation Method Based on Computer Bionic Design

The Implementation and Application of Computer Simulation Technology in PE Teaching

Construction of College Communities in the New Media Based on Network Environment

Political and Ideological Personnel Management Mode Based on Computer Network

Analysis of Mapping Knowledge Domain on Health and Wellness Tourism in the Perspective of Cite Space

Application of Smart Retail Mode in Suning.Com

Construction and Development of High-tech Smart City

Design and Implementation of Self-Service Tourism Management Information System Based on B/S Architecture

Chinese Culture Penetration in Teaching Chinese as a Foreign Language in the Era of Mobile Internet

Application and Outlook of Digital Media Technology in Smart Tourism

Accounting Informationization in Computer Network Environment

Mobile Phone GPS and Sensor Technology in College Students' Extracurricular Exercises

Design of Networking Network Model Based on Network Function Virtualization Technology

Intelligent Media Technology Empowered Brand Communication of Chinese Intangible Cultural Heritage

Construction Strategy of Smart English Teaching Platform from the Perspective of "Internet + Education"

Online Writing Effectiveness under the Blended Teaching Mode of Moscotech APP

A Narrative Environment Model for the Sustainability of Intangible Cultural Heritage under the 5G Era

Application Study of VPN on the Network of Hydropower Plant

Prediction of Technology Trend of Educational Robot Industry Based On Patent Map Analysis

Coal Handling System of Power Plant Based On PLC

Discussion on the Construction of Wireless Campus Network Based On SDN Architecture

Applicational Status Analysis of Artificial Intelligence Technology in Middle School Education and Teaching

Virtual Enterprise Partner Selection by Improved Analytic Hierarchy Process with Entropy Weight and Range Method

Research and implementation of Intelligent Tourism Guide System Based on cloud computing platform

Analysis of financial needs of new agricultural operators based on K-means clustering algorithm

Research on the application of virtual network technology in computer network security

Application of Bionics in Underwater Acoustic Covert Communication

Energy-saving and efficient underwater wireless sensor network security data aggregation model

False Data Filtering in Underwater Wireless Sensor Networks

Research on Underwater Bionic Covert Communication

Session 6: Authentication and access control for data usage in IoT

The Application of Virtual Reality Technology in Architectural Design

Computer-assisted Teaching and Cultivate Students' Innovative Thinking Ability

The Reform Progress and Practical Difficulties of State-owned Hospitals under Information Age―Case Analysis Based on the Reform in a Medical Institution of A Group in China

Financing Efficiency of SMEs in New Third Board Market in the Information Times

Application of Virtual Instrument Technology in Electronic Course Teaching

A Solution for Internet of Things based on Blockchain and Edge Computer

Discovery and Advice of Free Charging of Electronic Devices

Design and Implementation of Tourism Information Management System Based on .NET

A Computer Model for Decision of Equipment Maintenance Spare Parts Reserve

Risk Level Determination of Science a

Edge learning for distributed big data analytics

Автор: Guo, Song (the Hong Kong Polytechnic University) Qu, Zhihao (the Hong Kong Polytechnic University)
Название: Edge learning for distributed big data analytics
ISBN: 1108832377 ISBN-13(EAN): 9781108832373
Издательство: Cambridge Academ
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Цена: 9502.00 р.
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Описание: Introduces fundamental theory, basic and advanced algorithms, and system design issues. Essential reading for experienced researchers and developers, or for those who are just entering the field.

Cognitive Social Mining Applications in Data Analytics and Forensics

Автор: Anandakumar Haldorai, Arulmurugan Ramu
Название: Cognitive Social Mining Applications in Data Analytics and Forensics
ISBN: 1522575227 ISBN-13(EAN): 9781522575221
Издательство: Mare Nostrum (Eurospan)
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Цена: 28413.00 р.
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Описание: Recently, there has been a rapid increase in interest regarding social network analysis in the data mining community. Cognitive radios are expected to play a major role in meeting this exploding traffic demand on social networks due to their ability to sense the environment, analyze outdoor parameters, and then make decisions for dynamic time, frequency, space, resource allocation, and management to improve the utilization of mining the social data.Cognitive Social Mining Applications in Data Analytics and Forensics is an essential reference source that reviews cognitive radio concepts and examines their applications to social mining using a machine learning approach so that an adaptive and intelligent mining is achieved. Featuring research on topics such as data mining, real-time ubiquitous social mining services, and cognitive computing, this book is ideally designed for social network analysts, researchers, academicians, and industry professionals.

Handbook of Digital Forensics of Multimedia Data and Devices

Автор: Ho Anthony T S
Название: Handbook of Digital Forensics of Multimedia Data and Devices
ISBN: 1118640500 ISBN-13(EAN): 9781118640500
Издательство: Wiley
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Цена: 21059.00 р.
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Описание: Digital forensics and multimedia forensics are rapidly growing disciplines whereby electronic information is extracted and interpreted for use in a court of law.

Handbook Of Electronic Security And Digital Forensics

Автор: Jahankhani Hamid Et Al
Название: Handbook Of Electronic Security And Digital Forensics
ISBN: 9812837035 ISBN-13(EAN): 9789812837035
Издательство: World Scientific Publishing
Рейтинг:
Цена: 33106.00 р.
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Описание: Cybercrime is one of the biggest growth industries around the globe, whether it is in the form of violation of company policies, fraud, hate crime, extremism, or terrorism. This book provides literature on e-security needs across applications, implementation, testing or investigative techniques, judicial processes and criminal intelligence.

Deep Learning Techniques and Optimization Strategies in Big Data Analytics

Автор: J. Joshua Thomas, Pinar Karagoz, B. Bazeer Ahamed, Pandian Vasant
Название: Deep Learning Techniques and Optimization Strategies in Big Data Analytics
ISBN: 179981193X ISBN-13(EAN): 9781799811930
Издательство: Mare Nostrum (Eurospan)
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Цена: 27027.00 р.
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Описание: Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there's a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.

Deep Learning Techniques and Optimization Strategies in Big Data Analytics

Автор: J. Joshua Thomas, Pinar Karagoz, B. Bazeer Ahamed,
Название: Deep Learning Techniques and Optimization Strategies in Big Data Analytics
ISBN: 1799811921 ISBN-13(EAN): 9781799811923
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 35897.00 р.
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Описание: Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there's a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.

Big Data Analytics and Computing for Digital Forensic Investigations

Автор: Suneeta Satpathy, Sachi Nandan Mohanty
Название: Big Data Analytics and Computing for Digital Forensic Investigations
ISBN: 0367456788 ISBN-13(EAN): 9780367456788
Издательство: Taylor&Francis
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Цена: 12095.00 р.
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Описание: The book investigates the areas of digital forensics, digital investigation, and data analysis procedures as they apply to computer fraud and cyber crime, with the main objective of describing a variety of digital crimes and retrieving potential digital evidence.

Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges

Автор: Hassanien Aboul Ella, Darwish Ashraf
Название: Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges
ISBN: 3030593371 ISBN-13(EAN): 9783030593377
Издательство: Springer
Цена: 27950.00 р.
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Описание: The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data.

Social Big Data Analytics: Practices, Techniques, and Applications

Автор: Abu-Salih Bilal, Wongthongtham Pornpit, Zhu Dengya
Название: Social Big Data Analytics: Practices, Techniques, and Applications
ISBN: 9813366516 ISBN-13(EAN): 9789813366510
Издательство: Springer
Цена: 19564.00 р.
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Описание: Chapter 1: Big data technologies

Big data is no more "all just hype" but widely applied in nearly all aspects of our business, governments, and organizations with the technology stack of AI. Its influences are far beyond a simple technique innovation but involves all rears in the world. This chapter will first have historical review of big data; followed by discussion of characteristics of big data, i.e. the 3V's to up 10V's of big data. The chapter then introduces technology stacks for an organization to build a big data application, from infrastructure/platform/ecosystem to constructional units/components; following by several successful examples. Finally, we provide some big data online resources for reference.

Chapter 2: Credibility and influence in social big data

Online Social Networks (OSNs) are a fertile medium through which users can express their sentiments and share their opinions, experiences and knowledge of several topics. There is a deficiency of assessment mechanisms that incorporate domain-based trustworthiness. In OSNs, determining users' influence in a particular domain has been driven by its significance in a broad range of applications such as personalized recommendation systems, opinion analysis, expertise retrieval, to name a few. This chapter presents a comprehensive framework that aims to infer value from BSD by measuring the domain-based trustworthiness of OSN users, addressing the main features of big data, and incorporating semantic analysis and the temporal factor.

Chapter 3: Semantic data discovery from social big data

The challenge of managing and extracting useful knowledge from social media data sources has attracted much attention from academia and industry. Social big data is an important big data island; thus, social data analytics are intended to make sense of data and to obtain value from data. Social big data provides a wealth of information that businesses, political governments, organisations, etc. can mine and analyse to exploit value in a variety of areas. This chapter discusses the development of an approach that aims to semantically analyse social content, thus enriching social data with semantic conceptual representation for domain-based discovery.

Chapter 4: Predictive analytics using social big data and machine learning

Previous works in the area of topic distillation and discovery lack an appropriate and applicable technical solution that can handle the complex task of obtaining an accurate interpretation of the contextual social content. This is evident through the inadequacy of these endeavours in addressing the topics of microblogging short messages like tweets, and their inability to classify and predict the messages' actual and precise domains of interest at the user level. Hence, this chapter intends to address this problem by presenting solutions to domain-based classification and prediction of social big data at the user and tweet levels incorporating comprehensive knowledge discovery tools and well-known machine learning algorithms.

Chapter 5: Affective design in the era of big social data

In today's competitive market, product designers not only need to optimize functional qualities when developing a new product, but also they need to optimize the affective qualities of the product. The reason is that products with high affective qualities is more likely to attract more potential consumers to buy. In the past, affective design is generally conducted based on the limited amount of customer survey data which is collected from marketing questionnaires and consumer interviews. Since the data amount is limited, the affective design cannot fully reflect the current or even the recent situation of the marketplaces. Thanks to the advanced computing and web technologies, big data from social media or product reviews in w

The 2020 International Conference on Machine Learning and Big Data Analytics for Iot Security and Privacy: Spiot-2020, Volume 1

Автор: Macintyre John, Zhao Jinghua, Ma Xiaomeng
Название: The 2020 International Conference on Machine Learning and Big Data Analytics for Iot Security and Privacy: Spiot-2020, Volume 1
ISBN: 303062742X ISBN-13(EAN): 9783030627423
Издательство: Springer
Цена: 27950.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание:

Session 1: Novel machine learning methods for IoT security

The Innovation of UI Design Courses in Higher Vocational Colleges Based on the Internet Perspective

Predicting the Getting-on and Getting-off Points Based on the Trafic Big Data

The Prediction analysis of Passengers Boarding and Alighting Points Based on the Big Data of Urban Traffic

Verifiable Random Number Based on B-Spline Curve

An Improved Particle Swarm Optimization Algorithm Based on DFC&HRS

Application and Practice of ID3 Algorithms in College Students' Education

Construction of Human Knee Joint Mechanics Model and Study on Mechanical Characteristics of Flexion movement based on neural network algorithm

Application of Artificial Intelligence Technology in Physical Fitness Test of College Students

Theoretical Research on College Students' Professional Literacy Design Based on Deep Learning

Artificial Intelligence is the Technical Guarantee of Network Security

Intelligent Question Answering System of Medical Knowledge Map Based on Deep Learning

Construction and Practice of Red Teaching Resources Based on Machine Learning

Reasonable Approach and Development Trend of Artificial Intelligence Sports Development

Returnee Migrant Workers' Entrepreneurship Based on Artificial Intelligence

Improvement of College Teachers' Teaching Ability under the Background of the Development of Artificial Intelligence Platform

Influence Factors of Using Modern Teaching Technology in the Classroom of Junior Middle School Teachers under the Background of Artificial Intelligence--Analysis Based on HLM

Analysis and Design of Personalized Learning System Based on Decision Tree Technology

Deep Learning Classification and Recognition Model Construction of Face Living Image Based on Multi-Feature Fusion

A Prediction Method of Blood Glucose Concentration Based On Nonlinear Auto-Regressive Model

Signal Processing Based On Machine Learning Optical Communication

Refined Management of Installation Engineering Cost based on Artificial Intelligence Technology

Application of Artificial Intelligence Technology in International Trade Finance

An Improved Genetic Algorithm for Vehicle Routing Problem

A Machine-Learning Based Store Layout Strategy in Shopping Mall

Risk Analysis in Online Peer-to-Peer Loaning Based on Machine Learning: A Decision Tree Implementation on PPDai.com

The Application of BP Neural Network in the Opioid Crisis

Design of Personalized Intelligent Learning Assistant System under Artificial Intelligence Background

Application of Artificial Intelligence in Intelligent Decision-making of Human Resource Allocation

Research on Early Warning of Security Risk of Hazardous Chemicals Storage Based on BP-PSO

The Application of Artificial Intelligence and Machine Learning in Financial Stability

Application of alternative routing configuration mechanism based on Genetic Algorithm in power communication network

Safety Situation Assessment of Underwater Nodes based on BP Neural Network

Session 2: Big data analytics for IoT security

The Innovation of College Counsellor's Work Based On Big Data Analysis

Analysis of India's Big Data Industry

The Application of Computer Virtual Technology in Modern Sports Training

The Research on the Development and Utilization of Hospital Archive Information in the Big Data Era

Integration and Optimization of College English Teaching Information Resources in the Context of Big Data

Discussion on the Training of Cross-border E-commerce Application Talents Based on the Internet Era

Level of Technology Innovation Development and Promotion Strategies of High Technology Industry in Hubei Province Based on Smart City

Wisdom Medi

Machine Intelligence and Big Data Analytics for Cybersecurity Applications

Автор: Maleh Yassine, Shojafar Mohammad, Alazab Mamoun
Название: Machine Intelligence and Big Data Analytics for Cybersecurity Applications
ISBN: 3030570231 ISBN-13(EAN): 9783030570231
Издательство: Springer
Цена: 27950.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book presents the latest advances in machine intelligence and big data analytics to improve early warning of cyber-attacks, for cybersecurity intrusion detection and monitoring, and malware analysis.


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