Ai For Big Data Based Engineering Applications From Security Perspectives

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AI for Big Data-Based Engineering Applications from Security Perspectives

Author : Balwinder Raj,Brij B. Gupta,Shingo Yamaguchi,Sandeep Singh Gill
Publisher : CRC Press
Page : 227 pages
File Size : 55,6 Mb
Release : 2023-06-30
Category : Computers
ISBN : 9781000901559

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AI for Big Data-Based Engineering Applications from Security Perspectives by Balwinder Raj,Brij B. Gupta,Shingo Yamaguchi,Sandeep Singh Gill Pdf

Artificial intelligence (AI), machine learning, and advanced electronic circuits involve learning from every data input and using those inputs to generate new rules for future business analytics. AI and machine learning are now giving us new opportunities to use big data that we already had, as well as unleash a whole lot of new use cases with new data types. With the increasing use of AI dealing with highly sensitive information such as healthcare, adequate security measures are required to securely store and transmit this information. This book provides a broader coverage of the basic aspects of advanced circuits design and applications. AI for Big Data-Based Engineering Applications from Security Perspectives is an integrated source that aims at understanding the basic concepts associated with the security of advanced circuits. The content includes theoretical frameworks and recent empirical findings in the field to understand the associated principles, key challenges, and recent real-time applications of advanced circuits, AI, and big data security. It illustrates the notions, models, and terminologies that are widely used in the area of Very Large Scale Integration (VLSI) circuits, security, identifies the existing security issues in the field, and evaluates the underlying factors that influence system security. This work emphasizes the idea of understanding the motivation behind advanced circuit design to establish the AI interface and to mitigate security attacks in a better way for big data. This book also outlines exciting areas of future research where already existing methodologies can be implemented. This material is suitable for students, researchers, and professionals with research interest in AI for big data–based engineering applications, faculty members across universities, and software developers.

AI, Machine Learning and Deep Learning

Author : Fei Hu,Xiali Hei
Publisher : CRC Press
Page : 420 pages
File Size : 54,8 Mb
Release : 2023-06-05
Category : Computers
ISBN : 9781000878899

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AI, Machine Learning and Deep Learning by Fei Hu,Xiali Hei Pdf

Today, Artificial Intelligence (AI) and Machine Learning/ Deep Learning (ML/DL) have become the hottest areas in information technology. In our society, many intelligent devices rely on AI/ML/DL algorithms/tools for smart operations. Although AI/ML/DL algorithms and tools have been used in many internet applications and electronic devices, they are also vulnerable to various attacks and threats. AI parameters may be distorted by the internal attacker; the DL input samples may be polluted by adversaries; the ML model may be misled by changing the classification boundary, among many other attacks and threats. Such attacks can make AI products dangerous to use. While this discussion focuses on security issues in AI/ML/DL-based systems (i.e., securing the intelligent systems themselves), AI/ML/DL models and algorithms can actually also be used for cyber security (i.e., the use of AI to achieve security). Since AI/ML/DL security is a newly emergent field, many researchers and industry professionals cannot yet obtain a detailed, comprehensive understanding of this area. This book aims to provide a complete picture of the challenges and solutions to related security issues in various applications. It explains how different attacks can occur in advanced AI tools and the challenges of overcoming those attacks. Then, the book describes many sets of promising solutions to achieve AI security and privacy. The features of this book have seven aspects: This is the first book to explain various practical attacks and countermeasures to AI systems Both quantitative math models and practical security implementations are provided It covers both "securing the AI system itself" and "using AI to achieve security" It covers all the advanced AI attacks and threats with detailed attack models It provides multiple solution spaces to the security and privacy issues in AI tools The differences among ML and DL security and privacy issues are explained Many practical security applications are covered

Research Anthology on Artificial Intelligence Applications in Security

Author : Management Association, Information Resources
Publisher : IGI Global
Page : 2253 pages
File Size : 51,5 Mb
Release : 2020-11-27
Category : Computers
ISBN : 9781799877486

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Research Anthology on Artificial Intelligence Applications in Security by Management Association, Information Resources Pdf

As industries are rapidly being digitalized and information is being more heavily stored and transmitted online, the security of information has become a top priority in securing the use of online networks as a safe and effective platform. With the vast and diverse potential of artificial intelligence (AI) applications, it has become easier than ever to identify cyber vulnerabilities, potential threats, and the identification of solutions to these unique problems. The latest tools and technologies for AI applications have untapped potential that conventional systems and human security systems cannot meet, leading AI to be a frontrunner in the fight against malware, cyber-attacks, and various security issues. However, even with the tremendous progress AI has made within the sphere of security, it’s important to understand the impacts, implications, and critical issues and challenges of AI applications along with the many benefits and emerging trends in this essential field of security-based research. Research Anthology on Artificial Intelligence Applications in Security seeks to address the fundamental advancements and technologies being used in AI applications for the security of digital data and information. The included chapters cover a wide range of topics related to AI in security stemming from the development and design of these applications, the latest tools and technologies, as well as the utilization of AI and what challenges and impacts have been discovered along the way. This resource work is a critical exploration of the latest research on security and an overview of how AI has impacted the field and will continue to advance as an essential tool for security, safety, and privacy online. This book is ideally intended for cyber security analysts, computer engineers, IT specialists, practitioners, stakeholders, researchers, academicians, and students interested in AI applications in the realm of security research.

Advanced Computer Science Applications

Author : Karan Singh,Latha Banda,Manisha Manjul
Publisher : CRC Press
Page : 410 pages
File Size : 48,8 Mb
Release : 2023-09-15
Category : Computers
ISBN : 9781000839517

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Advanced Computer Science Applications by Karan Singh,Latha Banda,Manisha Manjul Pdf

This new book brings together the most recent trends related to AI, machine learning, and network security. The chapters cover diverse topics on machine learning algorithms and security analytics, AI and machine learning, and ntework security applications. The volume presents a survey of speculative parallelism techniques, performance reviews, and efficient power consumption. The book also covers the concepts of IoT, security early detection for COVID-19, multimetric geoprahpical routing in VANETs, V2X communication in VANET, and optimization of congestion control scheme for VANETs. This book is a comprehensive take on recent applications and advancement in the field of computer science and will be of value to scientists, researchers, faculty, and students involved in research in the area of AI, machine learning, and network security.

Artificial Intelligence and Cyber Security in Industry 4.0

Author : Velliangiri Sarveshwaran,Joy Iong-Zong Chen,Danilo Pelusi
Publisher : Springer Nature
Page : 374 pages
File Size : 51,8 Mb
Release : 2023-07-15
Category : Computers
ISBN : 9789819921157

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Artificial Intelligence and Cyber Security in Industry 4.0 by Velliangiri Sarveshwaran,Joy Iong-Zong Chen,Danilo Pelusi Pdf

This book provides theoretical background and state-of-the-art findings in artificial intelligence and cybersecurity for industry 4.0 and helps in implementing AI-based cybersecurity applications. Machine learning-based security approaches are vulnerable to poison datasets which can be caused by a legitimate defender's misclassification or attackers aiming to evade detection by contaminating the training data set. There also exist gaps between the test environment and the real world. Therefore, it is critical to check the potentials and limitations of AI-based security technologies in terms of metrics such as security, performance, cost, time, and consider how to incorporate them into the real world by addressing the gaps appropriately. This book focuses on state-of-the-art findings from both academia and industry in big data security relevant sciences, technologies, and applications. ​

Data Science and Applications

Author : Satyasai Jagannath Nanda
Publisher : Springer Nature
Page : 533 pages
File Size : 52,6 Mb
Release : 2024-05-20
Category : Electronic
ISBN : 9789819978205

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Data Science and Applications by Satyasai Jagannath Nanda Pdf

The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

Author : John MacIntyre,Jinghua Zhao,Xiaomeng Ma
Publisher : Springer Nature
Page : 887 pages
File Size : 55,6 Mb
Release : 2020-11-04
Category : Computers
ISBN : 9783030627461

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The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy by John MacIntyre,Jinghua Zhao,Xiaomeng Ma Pdf

This book presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020), held in Shanghai, China, on November 6, 2020. Due to the COVID-19 outbreak problem, SPIoT-2020 conference was held online by Tencent Meeting. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.

Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications

Author : Tran Khanh Dang,Josef Küng,Tai M. Chung
Publisher : Springer Nature
Page : 773 pages
File Size : 46,8 Mb
Release : 2022-11-19
Category : Computers
ISBN : 9789811980695

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Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications by Tran Khanh Dang,Josef Küng,Tai M. Chung Pdf

This book constitutes the refereed proceedings of the 9th International Conference on Future Data and Security Engineering, FDSE 2022, held in Ho Chi Minh City, Vietnam, during November 23–25, 2022. The 41 full papers(including 4 invited keynotes) and 12 short papers included in this book were carefully reviewed and selected from 170 submissions. They were organized in topical sections as follows: ​invited keynotes; big data analytics and distributed systems; security and privacy engineering; machine learning and artificial intelligence for security and privacy; smart city and industry 4.0 applications; data analytics and healthcare systems; and security and data engineering.

Big Data Analytics and Computational Intelligence for Cybersecurity

Author : Mariya Ouaissa,Zakaria Boulouard,Mariyam Ouaissa,Inam Ullah Khan,Mohammed Kaosar
Publisher : Springer Nature
Page : 336 pages
File Size : 48,8 Mb
Release : 2022-09-01
Category : Computers
ISBN : 9783031057526

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Big Data Analytics and Computational Intelligence for Cybersecurity by Mariya Ouaissa,Zakaria Boulouard,Mariyam Ouaissa,Inam Ullah Khan,Mohammed Kaosar Pdf

This book presents a collection of state-of-the-art artificial intelligence and big data analytics approaches to cybersecurity intelligence. It illustrates the latest trends in AI/ML-based strategic defense mechanisms against malware, vulnerabilities, cyber threats, as well as proactive countermeasures. It also introduces other trending technologies, such as blockchain, SDN, and IoT, and discusses their possible impact on improving security. The book discusses the convergence of AI/ML and big data in cybersecurity by providing an overview of theoretical, practical, and simulation concepts of computational intelligence and big data analytics used in different approaches of security. It also displays solutions that will help analyze complex patterns in user data and ultimately improve productivity. This book can be a source for researchers, students, and practitioners interested in the fields of artificial intelligence, cybersecurity, data analytics, and recent trends of networks.

AI-Enabled Threat Detection and Security Analysis for Industrial IoT

Author : Hadis Karimipour,Farnaz Derakhshan
Publisher : Springer Nature
Page : 250 pages
File Size : 49,6 Mb
Release : 2021-08-03
Category : Computers
ISBN : 9783030766139

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AI-Enabled Threat Detection and Security Analysis for Industrial IoT by Hadis Karimipour,Farnaz Derakhshan Pdf

This contributed volume provides the state-of-the-art development on security and privacy for cyber-physical systems (CPS) and industrial Internet of Things (IIoT). More specifically, this book discusses the security challenges in CPS and IIoT systems as well as how Artificial Intelligence (AI) and Machine Learning (ML) can be used to address these challenges. Furthermore, this book proposes various defence strategies, including intelligent cyber-attack and anomaly detection algorithms for different IIoT applications. Each chapter corresponds to an important snapshot including an overview of the opportunities and challenges of realizing the AI in IIoT environments, issues related to data security, privacy and application of blockchain technology in the IIoT environment. This book also examines more advanced and specific topics in AI-based solutions developed for efficient anomaly detection in IIoT environments. Different AI/ML techniques including deep representation learning, Snapshot Ensemble Deep Neural Network (SEDNN), federated learning and multi-stage learning are discussed and analysed as well. Researchers and professionals working in computer security with an emphasis on the scientific foundations and engineering techniques for securing IIoT systems and their underlying computing and communicating systems will find this book useful as a reference. The content of this book will be particularly useful for advanced-level students studying computer science, computer technology, cyber security, and information systems. It also applies to advanced-level students studying electrical engineering and system engineering, who would benefit from the case studies.

Combating Security Challenges in the Age of Big Data

Author : Zubair Md. Fadlullah,Al-Sakib Khan Pathan
Publisher : Springer Nature
Page : 271 pages
File Size : 51,9 Mb
Release : 2020-05-26
Category : Computers
ISBN : 9783030356422

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Combating Security Challenges in the Age of Big Data by Zubair Md. Fadlullah,Al-Sakib Khan Pathan Pdf

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.

Data-Driven Mining, Learning and Analytics for Secured Smart Cities

Author : Chinmay Chakraborty,Jerry Chun-Wei Lin,Mamoun Alazab
Publisher : Springer Nature
Page : 383 pages
File Size : 51,6 Mb
Release : 2021-04-28
Category : Computers
ISBN : 9783030721398

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Data-Driven Mining, Learning and Analytics for Secured Smart Cities by Chinmay Chakraborty,Jerry Chun-Wei Lin,Mamoun Alazab Pdf

This book provides information on data-driven infrastructure design, analytical approaches, and technological solutions with case studies for smart cities. This book aims to attract works on multidisciplinary research spanning across the computer science and engineering, environmental studies, services, urban planning and development, social sciences and industrial engineering on technologies, case studies, novel approaches, and visionary ideas related to data-driven innovative solutions and big data-powered applications to cope with the real world challenges for building smart cities.

Role of Data-Intensive Distributed Computing Systems in Designing Data Solutions

Author : Sarvesh Pandey,Udai Shanker,Vijayalakshmi Saravanan,Rajinikumar Ramalingam
Publisher : Springer Nature
Page : 339 pages
File Size : 42,5 Mb
Release : 2023-01-25
Category : Technology & Engineering
ISBN : 9783031155420

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Role of Data-Intensive Distributed Computing Systems in Designing Data Solutions by Sarvesh Pandey,Udai Shanker,Vijayalakshmi Saravanan,Rajinikumar Ramalingam Pdf

This book discusses the application of data systems and data-driven infrastructure in existing industrial systems in order to optimize workflow, utilize hidden potential, and make existing systems free from vulnerabilities. The book discusses application of data in the health sector, public transportation, the financial institutions, and in battling natural disasters, among others. Topics include real-time applications in the current big data perspective; improving security in IoT devices; data backup techniques for systems; artificial intelligence-based outlier prediction; machine learning in OpenFlow Network; and application of deep learning in blockchain enabled applications. This book is intended for a variety of readers from professional industries, organizations, and students.

Artificial Intelligence for Cybersecurity

Author : Mark Stamp,Corrado Aaron Visaggio,Francesco Mercaldo,Fabio Di Troia
Publisher : Springer
Page : 0 pages
File Size : 47,7 Mb
Release : 2022-07-16
Category : Computers
ISBN : 3030970868

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Artificial Intelligence for Cybersecurity by Mark Stamp,Corrado Aaron Visaggio,Francesco Mercaldo,Fabio Di Troia Pdf

This book explores new and novel applications of machine learning, deep learning, and artificial intelligence that are related to major challenges in the field of cybersecurity. The provided research goes beyond simply applying AI techniques to datasets and instead delves into deeper issues that arise at the interface between deep learning and cybersecurity. This book also provides insight into the difficult "how" and "why" questions that arise in AI within the security domain. For example, this book includes chapters covering "explainable AI", "adversarial learning", "resilient AI", and a wide variety of related topics. It’s not limited to any specific cybersecurity subtopics and the chapters touch upon a wide range of cybersecurity domains, ranging from malware to biometrics and more. Researchers and advanced level students working and studying in the fields of cybersecurity (equivalently, information security) or artificial intelligence (including deep learning, machine learning, big data, and related fields) will want to purchase this book as a reference. Practitioners working within these fields will also be interested in purchasing this book.

Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications

Author : Tran Khanh Dang,Josef Küng,Tai M. Chung
Publisher : Springer Nature
Page : 621 pages
File Size : 40,6 Mb
Release : 2023-11-17
Category : Computers
ISBN : 9789819982967

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Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications by Tran Khanh Dang,Josef Küng,Tai M. Chung Pdf

This book constitutes the proceedings of the 10th International Conference on Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications, FDSE 2023, held in Da Nang, Vietnam, during November 22–24, 2023. The 38 full papers and 8 short papers were carefully reviewed and selected from 135 submissions. They were organized in topical sections as follows: big data analytics and distributed systems; security and privacy engineering; machine learning and artificial intelligence for security and privacy; smart city and industry 4.0 applications; data analytics and healthcare systems; and short papers: security and data engineering.