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Ventura L: Artificial Intelligence in
Cybersecurity

Artificial Intelligence in Cybersecurity

Use AI to Protect Your Organization

Learn how to manage the risks and opportunities of agentic AI with this practical guide to ensuring the safe and beneficial developments of advanced AI systems.

Principles and Responsible Practices

Safer Agentic AI

Learn to build a web app that can monitor millions of posts across all social media platforms to chart public opinion in real time. Social media has become our modern-day agora, the place where we get our news and engage in political discourse. With disinformation, hate speech, foreign interference, authoritarianism, market monopolization, and political polarization all on the rise, monitoring social media in the public interest has never been so difficult nor so urgent. Social Media Observatory is an in-depth beginner’s guide to coding full-stack web applications in Python to track and analyze social media activity at scale, giving you unparalleled insights into the cultural and political conversations of our time, then empowering you to reach your own conclusions. You’ll start by coding a web app to monitor Russian disinformation channels discussing Ukraine on Telegram, then learn more adversarial methods to scrape the Wayback Machine, Instagram, and TikTok. You’ll detect Twitter bots following Saudi influencers, extract text-embedded URLs to reveal a white supremacist blogosphere, parse archived tweets to reveal the discourse leading up to the January 6 insurrection, and learn to circumvent Meta's and ByteDance's defenses to scrape Instagram and TikTok, collecting evidence of war crimes in the Middle East. Finally, you’ll write an API and deploy your observatory to a cloud server to collaborate with other investigators. By the end of the book, you’ll have a working website that allows collaborators to log in, request data collection, and perform analysis of collected data, via a point-and-click interface.&nbsp; Along the way, you’ll learn to: <ul><li>Use Python and RabbitMQ to retrieve Telegram data from a remote API</li><li>Store data with PostgreSQL and query it with SQLAlchemy</li><li>Analyze the data you’ve retrieved with Pandas, NetworkX, Gephi, and other tools</li><li>Use state-of-the-art AI tools to transcribe audio and classify text</li><li>Deploy a website with an interactive dashboard using FastAPI, Dash, Cytoscape, Uvicorn, Gunicorn, Nginx, AWS, and Let’s Encrypt</li><li>Containerize your apps with Docker and provision infrastructure with Pulumi</li></ul> Whether you’re a citizen scientist, a security researcher, a journalist, an activist, or a scholar, Social Media Observatory is an essential blueprint for building your window into online worlds.

Learn to build a web app that can monitor millions of posts across all social media platforms to chart public opinion in real time. Social media has become our modern-day agora, the place where we get our news and engage in political discourse. With disinformation, hate speech, foreign interference, authoritarianism, market monopolization, and political polarization all on the rise, monitoring social media in the public interest has never been so difficult nor so urgent. Social Media Observatory is an in-depth beginner’s guide to coding full-stack web applications in Python to track and analyze social media activity at scale, giving you unparalleled insights into the cultural and political conversations of our time, then empowering you to reach your own conclusions. You’ll start by coding a web app to monitor Russian disinformation channels discussing Ukraine on Telegram, then learn more adversarial methods to scrape the Wayback Machine, Instagram, and TikTok. You’ll detect Twitter bots following Saudi influencers, extract text-embedded URLs to reveal a white supremacist blogosphere, parse archived tweets to reveal the discourse leading up to the January 6 insurrection, and learn to circumvent Meta's and ByteDance's defenses to scrape Instagram and TikTok, collecting evidence of war crimes in the Middle East. Finally, you’ll write an API and deploy your observatory to a cloud server to collaborate with other investigators. By the end of the book, you’ll have a working website that allows collaborators to log in, request data collection, and perform analysis of collected data, via a point-and-click interface.&nbsp; Along the way, you’ll learn to: <ul><li>Use Python and RabbitMQ to retrieve Telegram data from a remote API</li><li>Store data with PostgreSQL and query it with SQLAlchemy</li><li>Analyze the data you’ve retrieved with Pandas, NetworkX, Gephi, and other tools</li><li>Use state-of-the-art AI tools to transcribe audio and classify text</li><li>Deploy a website with an interactive dashboard using FastAPI, Dash, Cytoscape, Uvicorn, Gunicorn, Nginx, AWS, and Let’s Encrypt</li><li>Containerize your apps with Docker and provision infrastructure with Pulumi</li></ul> Whether you’re a citizen scientist, a security researcher, a journalist, an activist, or a scholar, Social Media Observatory is an essential blueprint for building your window into online worlds.

Social Media Observatory

De Gruyter Series in Measurement Sciences

Advances and Applications

Artificially Intelligent Sensing

Das Buch führt anschaulich und verständlich in das Gebiet der intelligenten Verfahren ein. In geschlossenen Darstellungen zeigt es zuerst die theoretischen Grundlagen und anschließend praktische Beispiele, wobei bei den Beispielen auch fehlerhafte Ansätze gezeigt werden.Ausgehend von linearen Systemen und ihren Einschränkungen werden nichtlineare Systeme sowie grundlegende Lernverfahren eingeführt. Darauf aufbauend werden intelligente Verfahren, z.B. der lernfähige, nichtlineare Beobachter, entwickelt sowie die Identifikation von nichtlinearen Systemen und deren Optimierung behandelt. &nbsp;Anschließend werden Regelungsverfahren von nichtlinearen Systemen vorgestellt, wobei die modellbasierte adaptive Regelung sowie die Regelung von unbekannten Systemen Schwerpunkte sind. Den Abschluss bildet ein Kapitel über Fuzzy-Logik.Die Verfahren können bei vielen nichtlinearen Systemen angewendet werden und wurden bereits äußerst erfolgreich in der Medizin, in der Robotik und in der Getriebesteuerung von Hybridfahrzeugen eingesetzt.Neu an der zweiten Auflage sind Kapitel über robuste Schätzverfahren und Concurrent Learning.Die ZielgruppenDas Werk richtet sich an Studierende &nbsp;und Wissenschaftler der Ingenieurwissenschaften, Informatik und Mathematik sowie Ingenieure in der Praxis.Die AutorenUniv.-Prof. i .R. Dr.-Ing. Dr.-Ing. h.c. Dierk Schröder, Fellow IEEE, Technische Universität München, Lehrstuhl für Elektrische Antriebssysteme und Leistungselektronik&nbsp;Univ.-Prof. Dr.-Ing./Univ. Tokio habil. Martin Buss, Fellow IEEE, Technische Universität München, Lehrstuhl für Steuerungs- und Regelungstechnik

Anschauliche und verständliche Einführung in das Gebiet der intelligenten Verfahren&nbsp;Verfahren können für alle nichtlinearen Systemen angewendet werdenDie geschlossene Darstellung zeigt die theoretischen Grundlagen und praktische Beispiele

Identifikation und Regelung nichtlinearer Systeme

Intelligente Verfahren

Chapman & Hall/CRC Data Mining and Knowledge Discovery Series

As data continues to grow exponentially, knowledge of data science and machine learning has become more crucial than ever. Machine learning has grown exponentially, however, the abundance of resources can be overwhelming

As data continues to grow exponentially, knowledge of data science and machine learning has become more crucial than ever. Machine learning has grown exponentially, however, the abundance of resources can be overwhelming

Using SAS Enterprise Miner

Data Science and Machine Learning for Non-Programmers

Algorithms have become the key organizer through which power is enacted in our society. A huge amount of data regarding our daily routines are monitored and analyzed to make recommendations that manage, control, and lead our behaviors in everyday life. AI, Humans, and Misinformation: How Does AI Alter Human Behavior and How Do Humans Influence Algorithmic Misinformation? is a guide to understanding the dynamics of AI and misinformation in human contexts by addressing meaningful questions-How does AI alter human behavior and how do humans influence algorithmic decision-making? In answering these questions, this book examines the role of misinformation, disinformation, and fake news, and shows readers how to develop AI methods and algorithms that combat misinformation by using AI design choices that provide users and developers alike with meaningful control over AI. This book brings together various perspectives on algorithms into an integrated conceptual framework, and provides a broad socio-technical analysis, addressing critical and ethical issues of misinformation and fake news. The book offers a compelling insight into the misinformation phenomenon and the future of AI-based society. Readers will find an integrated technical analysis of the logic and social implications of algorithmic processes. Reporting from the cutting edge of critical technical methods and research, the result is useful and constructive for developing the relations between algorithms and humans. This is an imperative methodology for understanding what is at stake as industry and government use AI to reshape the world.

Decoding Bias, Algorithms, and Trust

Minds, Machines, and Misinformation

Although some businesses have developed strategies for managing short-term disruptions, many do not have systems or resources in place for the long-term consequence management of catastrophic events that could lead to failure. This book is unique in that it gives practical, concise guidelines to the corporate manager in the event of any crisis or physical catastrophe, from a kidnapping to a collapsing building, that creates long term effects for business property, employees or customers.

Although some businesses have developed strategies for managing short-term disruptions, many do not have systems or resources in place for the long-term consequence management of catastrophic events that could lead to failure. This book is unique in that it gives practical, concise guidelines to the corporate manager in the event of any crisis or physical catastrophe, from a kidnapping to a collapsing building, that creates long term effects for business property, employees or customers.

Corporate Management in a Physical Crisis

Leaders of many public and private organizations face increased pressure to allow the use of personal mobile devices in their enterprises. This book provides an understanding of the increased risks that accompany the introduction of BYOD (Bring Your Own Device) into the enterprise.

Leaders of many public and private organizations face increased pressure to allow the use of personal mobile devices in their enterprises. This book provides an understanding of the increased risks that accompany the introduction of BYOD (Bring Your Own Device) into the enterprise.

Security and Privacy Concerns

Personal Mobile Devices in the Enterprise

New Directions in Contemporary Art

The field of AI Art is a hotbed for strange, uneasy partnerships between big tech, big art and critical culture. Not since Walter Benjamin's Age of Mechanical Reproduction has there been a similar challenge to humanist art criticism. This book examines how a contemporary critic should best engage with, contextualise and effectively critique machine-learning-based art. In considering this question, Nora Khan looks at the rush of institutions to place AI Art within an art-historical lineage while they simultaneously accept significant funding from technology companies. She discusses the scale and speed at which technological production, machine learning, and AI have abraded the individual's capacity for critical evaluation, moving us to consider what a shared, collective criticism of AI might sound like.

The field of AI Art is a hotbed for strange, uneasy partnerships between big tech, big art and critical culture. Not since Walter Benjamin's Age of Mechanical Reproduction has there been a similar challenge to humanist art criticism. This book examines how a contemporary critic should best engage with, contextualise and effectively critique machine-learning-based art. In considering this question, Nora Khan looks at the rush of institutions to place AI Art within an art-historical lineage while they simultaneously accept significant funding from technology companies. She discusses the scale and speed at which technological production, machine learning, and AI have abraded the individual’s capacity for critical evaluation, moving us to consider what a shared, collective criticism of AI might sound like.

AI Art, Machine Learning and the Stakes for Art Criticism

Leveraging AI, Data and Analytics in Travel

Technology-Led Tourism

Intelligent IoT-based Diagnostic and Assistive Systems for Neurological Disorders

This book addresses the integration of new devices (such as the iPhone), new technologies (such as cloud computing and green computing), and new software systems in pervasive and ubiquitous computing from the point of view of security, trust, and privacy (STP). It provides an overview of recent progress in ubiquitous and pervasive computing, examining current practices, trends, and challenges. The book covers theoretical approaches, mathematical models, empirical research, practical implementations, and diverse application areas, along with a rich and useful presentation of strategies for security issues in different computing areas.

This book addresses the integration of new devices (such as the iPhone), new technologies (such as cloud computing and green computing), and new software systems in pervasive and ubiquitous computing from the point of view of security, trust, and privacy (STP). It provides an overview of recent progress in ubiquitous and pervasive computing, examining current practices, trends, and challenges. The book covers theoretical approaches, mathematical models, empirical research, practical implementations, and diverse application areas, along with a rich and useful presentation of strategies for security issues in different computing areas.

New Trends and Applications

Security, Privacy, and Trust in Ubiquitous Computing

Artificial Intelligence in Cybersecurity

Bibliografische Angaben

Schlagworte

Bibliografische Angaben

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