Predictive Computing And Information Security
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Predictive Computing And Information Security
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Author : P.K. Gupta
language : en
Publisher: Springer
Release Date : 2017-09-27
Predictive Computing And Information Security written by P.K. Gupta and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-27 with Computers categories.
This book describes various methods and recent advances in predictive computing and information security. It highlights various predictive application scenarios to discuss these breakthroughs in real-world settings. Further, it addresses state-of-art techniques and the design, development and innovative use of technologies for enhancing predictive computing and information security. Coverage also includes the frameworks for eTransportation and eHealth, security techniques, and algorithms for predictive computing and information security based on Internet-of-Things and Cloud computing. As such, the book offers a valuable resource for graduate students and researchers interested in exploring predictive modeling techniques and architectures to solve information security, privacy and protection issues in future communication.
Information Security Analytics
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Author : Mark Talabis
language : en
Publisher: Syngress
Release Date : 2014-11-25
Information Security Analytics written by Mark Talabis and has been published by Syngress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-25 with Computers categories.
Information Security Analytics gives you insights into the practice of analytics and, more importantly, how you can utilize analytic techniques to identify trends and outliers that may not be possible to identify using traditional security analysis techniques. Information Security Analytics dispels the myth that analytics within the information security domain is limited to just security incident and event management systems and basic network analysis. Analytic techniques can help you mine data and identify patterns and relationships in any form of security data. Using the techniques covered in this book, you will be able to gain security insights into unstructured big data of any type. The authors of Information Security Analytics bring a wealth of analytics experience to demonstrate practical, hands-on techniques through case studies and using freely-available tools that will allow you to find anomalies and outliers by combining disparate data sets. They also teach you everything you need to know about threat simulation techniques and how to use analytics as a powerful decision-making tool to assess security control and process requirements within your organization. Ultimately, you will learn how to use these simulation techniques to help predict and profile potential risks to your organization. Written by security practitioners, for security practitioners Real-world case studies and scenarios are provided for each analytics technique Learn about open-source analytics and statistical packages, tools, and applications Step-by-step guidance on how to use analytics tools and how they map to the techniques and scenarios provided Learn how to design and utilize simulations for "what-if" scenarios to simulate security events and processes Learn how to utilize big data techniques to assist in incident response and intrusion analysis
Threat Forecasting
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Author : John Pirc
language : en
Publisher: Syngress
Release Date : 2016-05-17
Threat Forecasting written by John Pirc and has been published by Syngress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-17 with Computers categories.
Drawing upon years of practical experience and using numerous examples and illustrative case studies, Threat Forecasting: Leveraging Big Data for Predictive Analysis discusses important topics, including the danger of using historic data as the basis for predicting future breaches, how to use security intelligence as a tool to develop threat forecasting techniques, and how to use threat data visualization techniques and threat simulation tools. Readers will gain valuable security insights into unstructured big data, along with tactics on how to use the data to their advantage to reduce risk. Presents case studies and actual data to demonstrate threat data visualization techniques and threat simulation tools Explores the usage of kill chain modelling to inform actionable security intelligence Demonstrates a methodology that can be used to create a full threat forecast analysis for enterprise networks of any size
Knowledge Discovery In Cyberspace
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Author : Kristijan Kuk
language : en
Publisher: Nova Science Publishers
Release Date : 2017
Knowledge Discovery In Cyberspace written by Kristijan Kuk and has been published by Nova Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Computers categories.
PhD Kristijan V. Kuk was born in Belgrade, Serbia, in 1977. He is received the B.S.E.E in 2007 from Technical Faculty in Zrenjanin, University of Novi Sad, Serbia. He finished PhD degree in informatics and computing science in 2013 at the Faculty of Electronic Engineering, University of Nis. In addition, he is the author of more than 40 scientific - technical papers presented at the reference international and national conferences. Eight papers are published in scientific journals from SCI/E lists, three paper is published as a chapter for Springer book. In 2014 he was elected to the position of assistant professor in Software Engineering / Computer forensics tool Development at the Academy of Criminalistic and Police Studies in Belgrade. He is a member of the CyberCrime Research Centre of the Police Academy. His research interests are artificial intelligence-based cyber security platforms, intelligent agents, data/text mining techniques in social networks, cybercrime prevention architectures and behavioral design patterns.This book is a practical handbook of research on dealing with mathematical methods in crime prevention for special agents, and discusses their capabilities and benefits that stem from integrating statistical analysis and predictive modeling. It consists of a current collection of research with contributions by authors from different nations in different disciplines. After reading this book, the reader should be able to understand the fundamental nature of cyberspace; understand the role of cyber-attacks; learn analytical techniques and the challenges of predicting events; learn how languages and culture are influenced by cyberspace; and learn techniques of the cyberspace public opinion detection and tracking process. Understanding cyberspace is the key to defending against digital attacks. This book takes a global perspective, examining the skills needed to collect and analyze event information and perform threat or target analysis duties in an effort to identify sources for signs of compromise, unauthorized activity and poor security practices. The ability to understand and react to events in cyberspace in a timely and appropriate manner will be key to future success. Most of the collections are research-based practices that have been done throughout the years. The authors hope that the presented work will be of great use to police investigators and cyber special agents interested in predictive analytics. Target Audience: Police investigator, Cyber special agent, Cyber incident response specialist, Cyber Security Engineer, Computer Forensic Analyst.
Emerging Methods In Predictive Analytics Risk Management And Decision Making
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Author : Hsu, William H.
language : en
Publisher: IGI Global
Release Date : 2014-01-31
Emerging Methods In Predictive Analytics Risk Management And Decision Making written by Hsu, William H. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-31 with Business & Economics categories.
Decision making tools are essential for the successful outcome of any organization. Recent advances in predictive analytics have aided in identifying particular points of leverage where critical decisions can be made. Emerging Methods in Predictive Analytics: Risk Management and Decision Making provides an interdisciplinary approach to predictive analytics; bringing together the fields of business, statistics, and information technology for effective decision making. Managers, business professionals, and decision makers in diverse fields will find the applications and cases presented in this text essential in providing new avenues for risk assessment, management, and predicting the future outcomes of their decisions.
Machine Learning For Beginners
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Author : Jeff Mc Frockman
language : en
Publisher:
Release Date : 2019-11-26
Machine Learning For Beginners written by Jeff Mc Frockman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-26 with categories.
If you think that machine learning has become too broad and challenging to begin learning, then Machine Learning for Beginners is the book you have been waiting for. The extent of how extensive deep learning has become does not matter, but understanding the essentials initially provides the building blocks to ascertain your knowledge in machine learning. Everyone agrees that machine learning is a broad topic with several components; however, having a strong foundation of what it encompasses plays a crucial role in what it entails in general. However, machine learning uses a similar technique of how we think and conduct our daily lives with most of the activities controlled by the brain. When we adopt this concept, the chances are that you are likely to understand what machine learning, especially deep learning, is all about. That said, inside this book, you will find valuable information specifically designed to build your knowledge about machine learning. With the changing world, mostly into making, machines learn human behaviors, you do not wish to be left behind but move with the industry. Before venturing deeper into machine learning, the book highlights the fundamental concepts of machine learning. You should initially understand the basic components or rather the terms, central aspects of these machines and some of the types of machine learning algorithms. Besides, the book provides a brief tutorial of how machine learning techniques are conducted. More so, it is vital to understand the benefits of machine learning in real life to enhance your interest in this field of computing. As such, inside, you will find some of the applications of machine learning in different areas, especially in simplifying things and making technology more straightforward. Technology may become confusing with almost similar multidisciplinary elements of computing; the book, therefore, highlights the differences between machine learning, deep learning, data science, and cognitive computing, among others. You will also learn about some of the examples of deep learning and when to avoid the utilization of machine learning, especially when it is harmful or prone to cause destruction. With different machine learning algorithm out there, you will have to learn about them also entailed in this book. Some may wonder how machines simulate human behaviors and other responses without being programmed, whereas others may think that machines imitation of how we react to events is made possible through magic. This book, Machine Learning For Beginners, provides an answer to these questions and beliefs detailing how scientists have made this learning practical where it seemed impossible. Inside you will find Definition of machine learning and its comparison to programming or code use when setting computer instructions The basics of machine learning including the vocabularies used, components, and types of algorithms Explanation of how machines learn and when to avoid using machine learning as a tool for solving problems Paradigms and algorithms of machine learning Similarities, differences, and relationships between data science, machine learning, deep learning, artificial learning, and cognitive computing Basic statistics and probability theory of machine learning Building blocks of machine learning and technical requirements of deep learning Applications of machine learning and how they improve our societies as well as some of the examples of deep learning in real life And more....
Data Mining And Predictive Analysis
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Author : Colleen McCue
language : en
Publisher: Butterworth-Heinemann
Release Date : 2014-12-30
Data Mining And Predictive Analysis written by Colleen McCue and has been published by Butterworth-Heinemann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-30 with Law categories.
Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis, 2nd Edition, describes clearly and simply how crime clusters and other intelligence can be used to deploy security resources most effectively. Rather than being reactive, security agencies can anticipate and prevent crime through the appropriate application of data mining and the use of standard computer programs. Data Mining and Predictive Analysis offers a clear, practical starting point for professionals who need to use data mining in homeland security, security analysis, and operational law enforcement settings. This revised text highlights new and emerging technology, discusses the importance of analytic context for ensuring successful implementation of advanced analytics in the operational setting, and covers new analytic service delivery models that increase ease of use and access to high-end technology and analytic capabilities. The use of predictive analytics in intelligence and security analysis enables the development of meaningful, information based tactics, strategy, and policy decisions in the operational public safety and security environment. Discusses new and emerging technologies and techniques, including up-to-date information on predictive policing, a key capability in law enforcement and security Demonstrates the importance of analytic context beyond software Covers new models for effective delivery of advanced analytics to the operational environment, which have increased access to even the most powerful capabilities Includes terminology, concepts, practical application of these concepts, and examples to highlight specific techniques and approaches in crime and intelligence analysis
Predictive Data Security Using Ai
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Author : Hiren Kumar Thakkar
language : en
Publisher: Springer Nature
Release Date : 2022-12-01
Predictive Data Security Using Ai written by Hiren Kumar Thakkar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-01 with Computers categories.
This contributed volume consists of 11 chapters that specifically cover the security aspects of the latest technologies such as Blockchain, IoT, and DevOps, and how to effectively deal with them using Intelligent techniques. Moreover, machine learning (ML) and deep learning (DL) algorithms are also not secured and often manipulated by attackers for data stealing. This book also discusses the types of attacks and offers novel solutions to counter the attacks on ML and DL algorithms. This book describes the concepts and issues with figures and the supporting arguments with facts and charts. In addition to that, the book provides the comparison of different security solutions in terms of experimental results with tables and charts. Besides, the book also provides the future directions for each chapter and novel alternative approaches, wherever applicable. Often the existing literature provides domain-specific knowledge such as the description of security aspects. However, the readers find it difficult to understand how to tackle the application-specific security issues. This book takes one step forward and offers the security issues, current trends, and technologies supported by alternate solutions. Moreover, the book provides thorough guidance on the applicability of ML and DL algorithms to deal with application-specific security issues followed by novel approaches to counter threats to ML and DL algorithms. The book includes contributions from academicians, researchers, security experts, security architectures, and practitioners and provides an in-depth understanding of the mentioned issues.
Predictive Intelligence Using Big Data And The Internet Of Things
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Author : Gupta, P.K.
language : en
Publisher: IGI Global
Release Date : 2018-12-28
Predictive Intelligence Using Big Data And The Internet Of Things written by Gupta, P.K. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-28 with Computers categories.
With the recent growth of big data and the internet of things (IoT), individuals can now upload, retrieve, store, and collect massive amounts of information to help drive decisions and optimize processes. Due to this, a new age of predictive computing is taking place, and data can now be harnessed to predict unknown occurrences or probabilities based on data collected in real time. Predictive Intelligence Using Big Data and the Internet of Things highlights state-of-the-art research on predictive intelligence using big data, the IoT, and related areas to ensure quality assurance and compatible IoT systems. Featuring coverage on predictive application scenarios to discuss these breakthroughs in real-world settings and various methods, frameworks, algorithms, and security concerns for predictive intelligence, this book is ideally designed for academicians, researchers, advanced-level students, and technology developers.
Advancements In Smart Computing And Information Security
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Author : Sridaran Rajagopal
language : en
Publisher: Springer Nature
Release Date :
Advancements In Smart Computing And Information Security written by Sridaran Rajagopal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.