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Aiding Forensic Investigation Through
Deep Learning and Machine Learning Fram

Aiding Forensic Investigation Through Deep Learning and Machine Learning Frameworks

Studies in National Governance and Emerging Technologies

This book provides a comprehensive analysis of cybersecurity governance and policymaking in the European Union. It considers how cybersecurity policy is implemented by policymakers and public administrators at EU and member-state level, the strengths and weaknesses of EU cybersecurity policy, and how the EU's approach to cybersecurity is distinct from other global actors. In doing so, the book not only advances our understanding of the EU’s cybersecurity governance but also provides a framework for evaluating its relevance and adaptability in a rapidly changing global landscape. It will appeal to scholars and students of public policy, cybersecurity, and EU governance, as well as practitioners.Francesco Amoretti
 is Professor of Political Science at the University of Salerno, Italy.&nbsp;
 Simone Busetti
 is&nbsp;Associate Professor of Political Science at the University of Teramo, Italy.&nbsp;
 Maria Stella Righettini
 is Associate Professor in Governance and Policy Evaluation at the University of Padova, Italy.&nbsp;
 Giancarlo Vecchi
 is Associate Professor in Political Science at Politecnico di Milano, Italy.
 &nbsp;

This book provides a comprehensive analysis of cybersecurity governance and policymaking in the European Union. It considers how cybersecurity policy is implemented by policymakers and public administrators at EU and member-state level, the strengths and weaknesses of EU cybersecurity policy, and how the EU's approach to cybersecurity is distinct from other global actors. In doing so, the book not only advances our understanding of the EU’s cybersecurity governance but also provides a framework for evaluating its relevance and adaptability in a rapidly changing global landscape. It will appeal to scholars and students of public policy, cybersecurity, and EU governance, as well as practitioners.

Defending a Digital Society

Cybersecurity Policy in the European Union

Tech, War and the Fight for Humanity

Thundercloud

Chapman & Hall/CRC Texts in Statistical Science

From Alan Turing breaking the Enigma code to ChatGPT reshaping how we work and create, artificial intelligence has always been powered by a single unifying principle: learning from data under uncertainty. This book reveals the mathematical machinery behind modern AI, weaving together Bayesian probability, statistical learning, and deep neural networks into a coherent intellectual framework. Whether you seek to understand why large language models hallucinate, how recommendation systems predict your preferences, or what makes reinforcement learning agents master complex games, this book equips you with both the theoretical foundations and practical intuitions that define the modern AI playbook.Key Features:<ul> <li>Builds Bayesian reasoning from first principles through historical examples like submarine search and WWII code-breaking</li> <li>Bridges classical statistics and deep learning, connecting linear regression to transformers</li> <li>Covers the complete AI stack: probability, decision theory, Gaussian processes, neural networks, CNNs, NLP, and LLMs</li> <li>Emphasizes uncertainty quantification-building systems that know what they don't know</li> <li>Practical applications across finance, healthcare, operations, and autonomous systems</li> <li>Emerging topics: AI agents, RLHF, and retrieval-augmented generation</li> </ul>Written for graduate students, data scientists, and quantitatively-minded practitioners, this book assumes comfort with calculus and basic probability while building sophisticated intuitions progressively. Business analysts will appreciate the decision-theoretic framing; engineers will value the architectural insights; researchers will find rigorous foundations for further study. Whether used as a course textbook, professional reference, or intellectual companion for understanding the AI revolution transforming every industry, this book delivers the rare combination of mathematical depth and accessible exposition that makes complex ideas genuinely understandable.

Foundations of Data Science

Bayes, AI, and Deep Learning

The Fight for the Future of Work

We Are Not Machines

Discover how to adapt, adopt, and thrive in an AI-anxious era, written by the man with the compass for our maze Expecting the apocalypse around the corner? This book is your playbook to surviving the rise of machine learning. 71% of workers are anxious about AI. The good news: the machines still need you, and you can make them work for you. Don't Panic cuts through the noise, showing you exactly how this technology works and where it fails, and why your human judgment is more valuable than ever. Instead of focusing on technical skills or abstract predictions, author Nate B. Jones ("AI Nate") begins with the emotional reality behind AI anxiety, drawing on his 20-years experience in the tech industry. He's garnered trust from more than 1 million people to help them stay relevant in a rapidly changing technological landscape. AI might have a planet-sized brain, but just like Marvin the Android from The Hitchhiker’s Guide to the Galaxy, it’s permanently stuck at factory settings. It can’t learn, it can’t adapt, and it can’t gain wisdom. This book reveals why AI's permanent blind spots make human judgment more valuable today than ever before.&nbsp; Worry less, and start owning your future.

Discover how to adapt, adopt, and thrive in an AI-anxious era, written by the man with the compass for our maze Expecting the apocalypse around the corner? This book is your playbook to surviving the rise of machine learning. 71% of workers are anxious about AI. The good news: the machines still need you, and you can make them work for you. Don't Panic cuts through the noise, showing you exactly how this technology works and where it fails, and why your human judgment is more valuable than ever. Instead of focusing on technical skills or abstract predictions, author Nate B. Jones ("AI Nate") begins with the emotional reality behind AI anxiety, drawing on his 20-years experience in the tech industry. He's garnered trust from more than 1 million people to help them stay relevant in a rapidly changing technological landscape. AI might have a planet-sized brain, but just like Marvin the Android from The Hitchhiker’s Guide to the Galaxy, it’s permanently stuck at factory settings. It can’t learn, it can’t adapt, and it can’t gain wisdom. This book reveals why AI's permanent blind spots make human judgment more valuable today than ever before.&nbsp; Worry less, and start owning your future.

AI Optimism for the Mildly Alarmed

Don't Panic

A brilliant exploration of the phenomenon of prediction markets that asks: what happens when democracy becomes another commodity? Prediction markets are sweeping the world, fundamentally changing the nature of gambling - and the very ways in which we attempt to divine the future.Posed as binary 'Yes/No' questions about future events, prediction markets allow any difference of opinion - whether on pop culture or politics, wars or assassinations - to be financialised. A regulatory minefield with moral implications that divide nations, governments and bettors, they have proved as effective at accurately predicting the timing of missile strikes as they have at calling the outcomes of elections.But are these markets really a new phenomenon? And what does it mean when those tasked with safeguarding democracy hold financial stakes in its volatility?From Renaissance Rome, where merchants wagered on papal conclaves, through nineteenth-century London's wartime coffee house gossip, to the Pentagon's ill-fated terrorism futures exchange and blockchain-based betting on Polymarket today, The Big Bet tells the gripping five-hundred-year story of a permissive regime that no one designed and no one voted for.Drawing on deep expertise, Michael Auerbach examines how these markets are changing our world, and what they mean for the future where democracy becomes just another commodity to be priced and traded. Because prediction markets are not an anomaly - they are the logical endpoint of a society that has applied market capitalism to every aspect of life. And in a world where everything is a wager and nothing is off limits, knowing where the chips will fall matters more than ever.

Prediction Markets and the Future of Democracy

The Big Bet

Agritech

Digitalisation and Artificial Intelligence in Agritech and Food Supply Chains, Volume I

The primary objective of this work is to develop a behavioral basis for an AI algorithm to assist managers of finance, production, and marketing divisions of firms in imperfect markets. Production, sales revenue, external finance, and networth (market value of the fixed assets) have the pivotal role as objectives. However, all of them cannot be maximized simultaneously due to the interdependence among them. The managers tend to pursue the most valuable objective using the most productive strategy at each point of time. This was utilized as a basis for the AI algorithm. Non-linearities in the switches in objectives and strategies are a short run phenomenon while swaps will be preferred if firms have a long run advantage. Such observed phenomena were also incorporated in the specification of the AI algorithms. The important results are as follows. (i) In most industries the shortage of demand is not a constraint. Instead, the ability of firms to increase their strategic supply is dominant. (ii) Most firms pursue strategic supply based on the capital stock available. This indicates a preference for external finance. (iii) In the short run firms utilize working capital finance and selling costs to ensure that the sales revenue achieved is commensurate with the strategic supply. (iv) Thus, the postulate that expected demand determines the strategic supply as well as the profit maximization postulate for the short run do not appear as the priorities.

The primary objective of this work is to develop a behavioral basis for an AI algorithm to assist managers of finance, production, and marketing divisions of firms in imperfect markets. Production, sales revenue, external finance, and networth (market value of the fixed assets) have the pivotal role as objectives. However, all of them cannot be maximized simultaneously due to the interdependence among them. The managers tend to pursue the most valuable objective using the most productive strategy at each point of time. This was utilized as a basis for the AI algorithm. Non-linearities in the switches in objectives and strategies are a short run phenomenon while swaps will be preferred if firms have a long run advantage. Such observed phenomena were also incorporated in the specification of the AI algorithms.&nbsp;The important results are as follows. (i) In most industries the shortage of demand is not a constraint. Instead, the ability of firms to increase their strategic supply is dominant. (ii) Most firms pursue strategic supply based on the capital stock available. This indicates a preference for external finance. (iii) In the short run firms utilize working capital finance and selling costs to ensure that the sales revenue achieved is commensurate with the strategic supply. (iv) Thus, the postulate that expected demand determines the strategic supply as well as the profit maximization postulate for the short run do not appear as the priorities.

Towards an AI Algorithm for Multiple Objectives in Imperfect Markets

Exploring the Future of Digital Defense

Cyber Security Unleashed

nuggets

Technische Innovationen wie das Internet der Dinge, Cloud Computing und Big Data revolutionieren nicht nur die Produktion und die Nutzung von Gütern. Sie verändern auch das Marketing, denn sie ermöglichen eine nie dagewesene Vernetzung, Datenanalyse und Interaktivität.
Das zeigt sich eindrucksvoll am Beispiel Digitaler Zwillinge, die - als virtuelles Abbild eines Produkts - die reale mit der digitalen Welt verbinden. Unternehmen geben sie die Möglichkeit, smarte, individualisierte Produkte und Services zu gestalten, die sich individuell auf die Nutzerbedürfnisse einstellen. Digitale Zwillinge sind der Schlüssel, um innovative Produkte effizient zu entwickeln, zu überwachen, zu steuern und zu optimieren. Zudem können sie auch bei der Prognose von Kundenverhalten helfen.
Kerstin Pezoldt erklärt in diesem nugget-Band kompakt und präzise, was Digital Twins im Produktlebenszyklus leisten und welche Rolle sie bei der Vermarktung von Konsumgütern spielen, etwa bei PKWs und Smartphones aber auch bei Haushaltsgeräten und nicht zuletzt bei sog. Smart-Home-Lösungen.

Definition, Funktionsweise und Nutzungsoptionen

Digitale Zwillinge im Marketing

Cyberangriffe gehören heute zu den größten Unternehmensrisiken. Dieses Buch zeigt Aufsichtsräten und Vorständen, wie sie Cyberrisiken wirksam überwachen, fundierte Entscheidungen treffen und ihrer Verantwortung für Cybersecurity gerecht werden. Es behandelt die aktuelle Bedrohungslage, regulatorische Anforderungen wie NIS-2 und DORA sowie die Rolle des Aufsichtsrats in der Cybersecurity-Governance. Das Buch erklärt, wie Cybersecurity strategisch verankert, Risiken gesteuert und verständlich berichtet werden. Weitere Schwerpunkte sind der Aufbau einer sicheren Organisation, Audits, Krisenmanagement sowie Zukunftstrends wie Künstliche Intelligenz. Geschrieben von einem DAX-40-CISO und einer erfahrenen Aufsichtsrätin verbindet es operative Erfahrung mit den Anforderungen der Corporate Governance. Im Mittelpunkt stehen konkrete Fragen, mit denen Aufsichtsräte Risiken besser bewerten, Managemententscheidungen kritisch hinterfragen und die Cyber-Resilienz ihres Unternehmens nachhaltig stärken können.

Cyberangriffe gehören heute zu den größten Unternehmensrisiken. Dieses Buch zeigt Aufsichtsräten und Vorständen, wie sie Cyberrisiken wirksam überwachen, fundierte Entscheidungen treffen und ihrer Verantwortung für Cybersecurity gerecht werden. Es behandelt die aktuelle Bedrohungslage, regulatorische Anforderungen wie NIS-2 und DORA sowie die Rolle des Aufsichtsrats in der Cybersecurity-Governance. Das Buch erklärt, wie Cybersecurity strategisch verankert, Risiken gesteuert und verständlich berichtet werden. Weitere Schwerpunkte sind der Aufbau einer sicheren Organisation, Audits, Krisenmanagement sowie Zukunftstrends wie Künstliche Intelligenz.
 
 Geschrieben von einem DAX-40-CISO und einer erfahrenen Aufsichtsrätin verbindet es operative Erfahrung mit den Anforderungen der Corporate Governance. Im Mittelpunkt stehen konkrete Fragen, mit denen Aufsichtsräte Risiken besser bewerten, Managemententscheidungen kritisch hinterfragen und die Cyber-Resilienz ihres Unternehmens nachhaltig stärken können.

Was Aufsichtsräte fragen und Vorstände beantworten müssen

Risiko Cybersecurity

Aiding Forensic Investigation Through Deep Learning and Machine Learning Frameworks

Weitere Titel zum Thema