Engineering Dependable and Secure Machine Learning Systems PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Engineering Dependable and Secure Machine Learning Systems PDF full book. Access full book title Engineering Dependable and Secure Machine Learning Systems by Onn Shehory. Download full books in PDF and EPUB format.
Author: Onn Shehory
Publisher: Springer Nature
ISBN: 3030621448
Category : Computers
Languages : en
Pages : 150
Get Book Here
Book Description
This book constitutes the revised selected papers of the Third International Workshop on Engineering Dependable and Secure Machine Learning Systems, EDSMLS 2020, held in New York City, NY, USA, in February 2020. The 7 full papers and 3 short papers were thoroughly reviewed and selected from 16 submissions. The volume presents original research on dependability and quality assurance of ML software systems, adversarial attacks on ML software systems, adversarial ML and software engineering, etc.
Author: Onn Shehory
Publisher: Springer Nature
ISBN: 3030621448
Category : Computers
Languages : en
Pages : 150
Get Book Here
Book Description
This book constitutes the revised selected papers of the Third International Workshop on Engineering Dependable and Secure Machine Learning Systems, EDSMLS 2020, held in New York City, NY, USA, in February 2020. The 7 full papers and 3 short papers were thoroughly reviewed and selected from 16 submissions. The volume presents original research on dependability and quality assurance of ML software systems, adversarial attacks on ML software systems, adversarial ML and software engineering, etc.
Author: Ross Anderson
Publisher: John Wiley & Sons
ISBN: 1119642787
Category : Computers
Languages : en
Pages : 1232
Get Book Here
Book Description
Now that there’s software in everything, how can you make anything secure? Understand how to engineer dependable systems with this newly updated classic In Security Engineering: A Guide to Building Dependable Distributed Systems, Third Edition Cambridge University professor Ross Anderson updates his classic textbook and teaches readers how to design, implement, and test systems to withstand both error and attack. This book became a best-seller in 2001 and helped establish the discipline of security engineering. By the second edition in 2008, underground dark markets had let the bad guys specialize and scale up; attacks were increasingly on users rather than on technology. The book repeated its success by showing how security engineers can focus on usability. Now the third edition brings it up to date for 2020. As people now go online from phones more than laptops, most servers are in the cloud, online advertising drives the Internet and social networks have taken over much human interaction, many patterns of crime and abuse are the same, but the methods have evolved. Ross Anderson explores what security engineering means in 2020, including: How the basic elements of cryptography, protocols, and access control translate to the new world of phones, cloud services, social media and the Internet of Things Who the attackers are – from nation states and business competitors through criminal gangs to stalkers and playground bullies What they do – from phishing and carding through SIM swapping and software exploits to DDoS and fake news Security psychology, from privacy through ease-of-use to deception The economics of security and dependability – why companies build vulnerable systems and governments look the other way How dozens of industries went online – well or badly How to manage security and safety engineering in a world of agile development – from reliability engineering to DevSecOps The third edition of Security Engineering ends with a grand challenge: sustainable security. As we build ever more software and connectivity into safety-critical durable goods like cars and medical devices, how do we design systems we can maintain and defend for decades? Or will everything in the world need monthly software upgrades, and become unsafe once they stop?
Author: Xinyu Feng
Publisher: Springer
ISBN: 3319999338
Category : Computers
Languages : en
Pages : 204
Get Book Here
Book Description
This book constitutes the proceedings of the Third International Symposium on Dependable Software Engineering: Theories, Tools, and Applications, SETTA 2018, held in Beijing, China, in September 2018. The 9 full papers presented together with 3 short papers were carefully reviewed and selected from 22 submissions. The purpose of SETTA is to provide an international forum for researchers and practitioners to share cutting-edge advancements and strengthen collaborations in the field of formal methods and its interoperability with software engineering for building reliable, safe, secure, and smart systems.
Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1609608194
Category : Computers
Languages : en
Pages : 2174
Get Book Here
Book Description
"This reference offers a wide-ranging selection of key research in a complex field of study,discussing topics ranging from using machine learning to improve the effectiveness of agents and multi-agent systems to developing machine learning software for high frequency trading in financial markets"--Provided by publishe
Author: Frank J. Furrer
Publisher: Springer Nature
ISBN: 365837182X
Category : Computers
Languages : en
Pages : 559
Get Book Here
Book Description
Cyber-physical systems (CPSs) consist of software-controlled computing devices communicating with each other and interacting with the physical world through sensors and actuators. Because most of the functionality of a CPS is implemented in software, the software is of crucial importance for the safety and security of the CPS. This book presents principle-based engineering for the development and operation of dependable software. The knowledge in this book addresses organizations that want to strengthen their methodologies to build safe and secure software for mission-critical cyber-physical systems. The book: • Presents a successful strategy for the management of vulnerabilities, threats, and failures in mission-critical cyber-physical systems; • Offers deep practical insight into principle-based software development (62 principles are introduced and cataloged into five categories: Business & organization, general principles, safety, security, and risk management principles); • Provides direct guidance on architecting and operating dependable cyber-physical systems for software managers and architects.
Author: Vandana Mohindru Sood
Publisher: CRC Press
ISBN: 1040011888
Category : Computers
Languages : en
Pages : 282
Get Book Here
Book Description
A cyber-physical system (CPS) is a computer system in which a mechanism is controlled or monitored by computer-based algorithms and involves transdisciplinary approaches, merging theories of cybernetics, mechatronics, design, and process science. This text mainly concentrates on offering a foundational theoretical underpinning, and a comprehensive and coherent review of intelligent security solutions for cyber-physical systems. Features: Provides an overview of cyber-physical systems (CPSs) along with security concepts like attack detection methods, cyber-physical systems failures, and risk identification and management Showcases cyber-physical systems (CPSs) security solutions, lightweight cryptographic solutions, and CPS forensics, etc Emphasizes machine learning methods for behavior-based intrusion detection in cyber-physical systems (CPSs), resilient machine learning for networked CPS, fog computing industrial CPS, etc Elaborates classification of network abnormalities in Internet of Things-based cyber-physical systems (CPSs) using deep learning Includes case studies and applications in the domain of smart grid systems, industrial control systems, smart manufacturing, social network and gaming, electric power grid and energy systems, etc
Author: James Joshi
Publisher: Elsevier
ISBN: 0080560156
Category : Computers
Languages : en
Pages : 365
Get Book Here
Book Description
Network Security: Know It All explains the basics, describes the protocols, and discusses advanced topics, by the best and brightest experts in the field of network security.Assembled from the works of leading researchers and practitioners, this best-of-the-best collection of chapters on network security and survivability is a valuable and handy resource. It consolidates content from the field's leading experts while creating a one-stop-shopping opportunity for readers to access the information only otherwise available from disparate sources.* Chapters contributed by recognized experts in the field cover theory and practice of network security technology, allowing the reader to develop a new level of knowledge and technical expertise. * Up-to-date coverage of network security issues facilitates learning and lets the reader remain current and fully informed from multiple viewpoints.* Presents methods of analysis and problem-solving techniques, enhancing the reader's grasp of the material and ability to implement practical solutions.* Examples illustrate core security concepts for enhanced comprehension
Author: Kanthavel, R.
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 534
Get Book Here
Book Description
Artificial Intelligence (AI) is rapidly becoming essential to large-scale communication networks. Driven by the need for greater efficiency, security, and optimization, AI has evolved into a powerful tool that processes vast data and delivers insights through real-time processing, predictive analysis, and adaptive learning. Because these advancements transform how we interact with data and services, applying AI to complex networks has never been more essential. AI for Large Scale Communication Networks explores how AI can enhance network performance, scalability, and security. With contributions from experts, this book covers topics such as algorithm optimization, machine learning improvements, and neural network applications. It also addresses critical challenges like fault tolerance and distributed computing, emphasizing the need for interdisciplinary collaboration. Designed for academics, practitioners, and students, this resource provides actionable insights and strategies to optimize communication networks using AI.
Author: Ning Xiong
Publisher: Springer Nature
ISBN: 3031207386
Category : Technology & Engineering
Languages : en
Pages : 1527
Get Book Here
Book Description
This book consists of papers on the recent progresses in the state of the art in natural computation, fuzzy systems, and knowledge discovery. The book is useful for researchers, including professors, graduate students, as well as R & D staff in the industry, with a general interest in natural computation, fuzzy systems, and knowledge discovery. The work printed in this book was presented at the 2022 18th International Conference on Natural Computation, Fuzzy Systems, and Knowledge Discovery (ICNC-FSKD 2022), held from 30 July to 1 August 2022, in Fuzhou, China. All papers were rigorously peer-reviewed by experts in the areas.
Author: Qiang Yang
Publisher: Springer Nature
ISBN: 3030630765
Category : Computers
Languages : en
Pages : 291
Get Book Here
Book Description
This book provides a comprehensive and self-contained introduction to federated learning, ranging from the basic knowledge and theories to various key applications. Privacy and incentive issues are the focus of this book. It is timely as federated learning is becoming popular after the release of the General Data Protection Regulation (GDPR). Since federated learning aims to enable a machine model to be collaboratively trained without each party exposing private data to others. This setting adheres to regulatory requirements of data privacy protection such as GDPR. This book contains three main parts. Firstly, it introduces different privacy-preserving methods for protecting a federated learning model against different types of attacks such as data leakage and/or data poisoning. Secondly, the book presents incentive mechanisms which aim to encourage individuals to participate in the federated learning ecosystems. Last but not least, this book also describes how federated learning can be applied in industry and business to address data silo and privacy-preserving problems. The book is intended for readers from both the academia and the industry, who would like to learn about federated learning, practice its implementation, and apply it in their own business. Readers are expected to have some basic understanding of linear algebra, calculus, and neural network. Additionally, domain knowledge in FinTech and marketing would be helpful.”
