Evaluating Architectural Safeguards for Uncertain AI Black-Box Components - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Evaluating Architectural Safeguards for Uncertain AI Black-Box Components write by Scheerer, Max. This book was released on 2023-10-23. Evaluating Architectural Safeguards for Uncertain AI Black-Box Components available in PDF, EPUB and Kindle. Although tremendous progress has been made in Artificial Intelligence (AI), it entails new challenges. The growing complexity of learning tasks requires more complex AI components, which increasingly exhibit unreliable behaviour. In this book, we present a model-driven approach to model architectural safeguards for AI components and analyse their effect on the overall system reliability.
Context-based Access Control and Attack Modelling and Analysis
Context-based Access Control and Attack Modelling and Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Context-based Access Control and Attack Modelling and Analysis write by Walter, Maximilian. This book was released on 2024-07-03. Context-based Access Control and Attack Modelling and Analysis available in PDF, EPUB and Kindle. This work introduces architectural security analyses for detecting access violations and attack paths in software architectures. It integrates access control policies and vulnerabilities, often analyzed separately, into a unified approach using software architecture models. Contributions include metamodels for access control and vulnerabilities, scenario-based analysis, and two attack analyses. Evaluation demonstrates high accuracy in identifying issues for secure system development.
A Reference Structure for Modular Model-based Analyses
A Reference Structure for Modular Model-based Analyses - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook A Reference Structure for Modular Model-based Analyses write by Koch, Sandro Giovanni. This book was released on 2024-04-25. A Reference Structure for Modular Model-based Analyses available in PDF, EPUB and Kindle. In this work, the authors analysed the co-dependency between models and analyses, particularly the structure and interdependence of artefacts and the feature-based decomposition and composition of model-based analyses. Their goal is to improve the maintainability of model-based analyses. They have investigated the co-dependency of Domain-specific Modelling Languages (DSMLs) and model-based analyses regarding evolvability, understandability, and reusability.
Regulating Artificial Intelligence
Regulating Artificial Intelligence - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Regulating Artificial Intelligence write by Thomas Wischmeyer. This book was released on 2019-11-29. Regulating Artificial Intelligence available in PDF, EPUB and Kindle. This book assesses the normative and practical challenges for artificial intelligence (AI) regulation, offers comprehensive information on the laws that currently shape or restrict the design or use of AI, and develops policy recommendations for those areas in which regulation is most urgently needed. By gathering contributions from scholars who are experts in their respective fields of legal research, it demonstrates that AI regulation is not a specialized sub-discipline, but affects the entire legal system and thus concerns all lawyers. Machine learning-based technology, which lies at the heart of what is commonly referred to as AI, is increasingly being employed to make policy and business decisions with broad social impacts, and therefore runs the risk of causing wide-scale damage. At the same time, AI technology is becoming more and more complex and difficult to understand, making it harder to determine whether or not it is being used in accordance with the law. In light of this situation, even tech enthusiasts are calling for stricter regulation of AI. Legislators, too, are stepping in and have begun to pass AI laws, including the prohibition of automated decision-making systems in Article 22 of the General Data Protection Regulation, the New York City AI transparency bill, and the 2017 amendments to the German Cartel Act and German Administrative Procedure Act. While the belief that something needs to be done is widely shared, there is far less clarity about what exactly can or should be done, or what effective regulation might look like. The book is divided into two major parts, the first of which focuses on features common to most AI systems, and explores how they relate to the legal framework for data-driven technologies, which already exists in the form of (national and supra-national) constitutional law, EU data protection and competition law, and anti-discrimination law. In the second part, the book examines in detail a number of relevant sectors in which AI is increasingly shaping decision-making processes, ranging from the notorious social media and the legal, financial and healthcare industries, to fields like law enforcement and tax law, in which we can observe how regulation by AI is becoming a reality.
Interpretable Machine Learning
Interpretable Machine Learning - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Interpretable Machine Learning write by Christoph Molnar. This book was released on 2020. Interpretable Machine Learning available in PDF, EPUB and Kindle. This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
