Complexity is not a new issue. In fact, in their day, William of Ockham and René Descartes proposed what can best be described as reductionist methods for dealing with it. Over the course of the twentieth century, a science of complexity has emerged in an ever-increasing number of fields (computer science, artificial intelligence, engineering, among others), and has now become an integral part of everyday life. As a result, everyone is confronted with increasingly complex situations that need to be understood and analyzed from a global perspective, to ensure the sustainability of our common…mehr
Complexity is not a new issue. In fact, in their day, William of Ockham and René Descartes proposed what can best be described as reductionist methods for dealing with it. Over the course of the twentieth century, a science of complexity has emerged in an ever-increasing number of fields (computer science, artificial intelligence, engineering, among others), and has now become an integral part of everyday life. As a result, everyone is confronted with increasingly complex situations that need to be understood and analyzed from a global perspective, to ensure the sustainability of our common future. Complexities 1 analyzes how complexity is understood and dealt with in the fields of cybersecurity, medicine, mathematics and information. This broad spectrum of disciplines shows that all fields of knowledge are challenged by complexity. The following volume, Complexities 2, examines the social sciences and humanities in relation to complexity.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Jean-Pierre Briffaut is Honorary Director of Studies at the Institut Mines-Télécom, France. A member of the Institut Fredrik Bull, he is in charge of a working group on the complexity of systems of systems.
Inhaltsangabe
Foreword: Sharing Complexity: An Acclaim for Complex Thinking ix Philippe Kourilsky Preface xiii Jean-Pierre Briffaut Chapter 1 The Complexity of Cybersecurity 1 Thierry Berthier and Thomas Anglade 1.1 Formal approach to the complexity of cybersecurity 1 1.1.1 Cybersecurity and theoretical computing 1 1.1.2 Malware and computer virology 7 1.1.3 Cyber-risk 17 1.1.4 Cognitive attacks and immersive fictitious data architectures 23 1.2 Cybersecurity in real life: Advanced persistent threats, computer networks, defense teams and complex log data 27 1.2.1 What is an APT? 27 1.2.2 What is the network that companies need to protect? Who protects it? Why are "Situational Crime Prevention" (SCP) systems complex systems? 30 1.2.3 What kind of anomalies need to be raised in order to detect a multi-stage APT attack? 36 1.3 User and entity behavior analysis as a way of reducing complexity 39 1.3.1 Presentation of the method 39 1.3.2 Data used and details of the method 42 1.3.3 Visual results and interpretation 44 1.4 Conclusion and future work 47 1.5 References 48 Chapter 2 Complexity and Biology: When Historical Perspectives Intersect with Epistemological Analyses 51 Céline Cherici 2.1 Complexity throughout the history of thoughs on living 53 2.1.1 The roots of thinking on complexity 53 2.1.2 From machinules to cells: An ordered complexity? 55 2.1.3 The organism: An autonomous complexity 57 2.1.4 The emergence of complexity between comparative anatomy and embryology 59 2.2 The living: Between potentialities and actualizations 64 2.2.1 Teratology to better understand the links between actualization and potentiality in the living 64 2.2.2 Time, a key concept for understanding the interactions between the possible and the actualized 70 2.3 Reductionist biotechnologies? 73 2.3.1 From physics to biotechnology 74 2.3.2 When the living extend beyond the experimental framework 78 2.4 References 82 Chapter 3 Two Complexities: Information and Structure Content 87 Jean-Paul Delahaye 3.1 The simple, the random and the structured: A triangle of concepts key to a complete understanding 87 3.2 Calculation, the key to the solution 88 3.3 Thought experiment 89 3.4 Mathematical definition 90 3.5 Random complexity and structural complexity 91 3.6 Recent progress 92 3.7 Less undecidability 93 3.8 Experimentation 94 3.9 Appendices 95 3.9.1 Complexification 95 3.9.2 Random and structural complexity 96 3.9.3 Incalculable but approximate 97 3.9.4 The law of slow growth 98 3.9.5 Experimental evaluation of K(s) and P(s) 98 3.10 References 99 Chapter 4 Leveraging Complexity in Oncology - A Data Narrative 101 Xosé M. Fernández 4.1 Large collaborative research initiatives - the Human Genome Project 104 4.2 Human cell atlas - unraveling complexity 105 4.3 From bench to bedside 107 4.4 The battle with cancer 109 4.5 Health economics - cost is another matter 112 4.6 From molecules to medicine 115 4.7 Artificial intelligence 117 4.8 The fourth paradigm 120 4.9 Modeling the complexity of cancer 121 4.10 References 124 Chapter 5 Complexity or Complexities of Information: The Dimensions of Complexity 129 Jacques Printz 5.1 Introduction 129 5.2 A brief historical overview 130 5.3 The phenomenology of complexity in systems engineering 131 5.3.1 Measuring the complexity of an assembly through the integration process and tests 134 5.4 The four dimensions of complexity 138 5.5 The term "simplexity": A remark on Richard Feynman's Nobel lecture 142 5.6 Computational volume: Remarks on the first quantification of complexity 144 5.6.1 Quantifying interactions and functional dependencies 145 5.7 References 151 List of Authors 153 Index 155
Foreword: Sharing Complexity: An Acclaim for Complex Thinking ix Philippe Kourilsky Preface xiii Jean-Pierre Briffaut Chapter 1 The Complexity of Cybersecurity 1 Thierry Berthier and Thomas Anglade 1.1 Formal approach to the complexity of cybersecurity 1 1.1.1 Cybersecurity and theoretical computing 1 1.1.2 Malware and computer virology 7 1.1.3 Cyber-risk 17 1.1.4 Cognitive attacks and immersive fictitious data architectures 23 1.2 Cybersecurity in real life: Advanced persistent threats, computer networks, defense teams and complex log data 27 1.2.1 What is an APT? 27 1.2.2 What is the network that companies need to protect? Who protects it? Why are "Situational Crime Prevention" (SCP) systems complex systems? 30 1.2.3 What kind of anomalies need to be raised in order to detect a multi-stage APT attack? 36 1.3 User and entity behavior analysis as a way of reducing complexity 39 1.3.1 Presentation of the method 39 1.3.2 Data used and details of the method 42 1.3.3 Visual results and interpretation 44 1.4 Conclusion and future work 47 1.5 References 48 Chapter 2 Complexity and Biology: When Historical Perspectives Intersect with Epistemological Analyses 51 Céline Cherici 2.1 Complexity throughout the history of thoughs on living 53 2.1.1 The roots of thinking on complexity 53 2.1.2 From machinules to cells: An ordered complexity? 55 2.1.3 The organism: An autonomous complexity 57 2.1.4 The emergence of complexity between comparative anatomy and embryology 59 2.2 The living: Between potentialities and actualizations 64 2.2.1 Teratology to better understand the links between actualization and potentiality in the living 64 2.2.2 Time, a key concept for understanding the interactions between the possible and the actualized 70 2.3 Reductionist biotechnologies? 73 2.3.1 From physics to biotechnology 74 2.3.2 When the living extend beyond the experimental framework 78 2.4 References 82 Chapter 3 Two Complexities: Information and Structure Content 87 Jean-Paul Delahaye 3.1 The simple, the random and the structured: A triangle of concepts key to a complete understanding 87 3.2 Calculation, the key to the solution 88 3.3 Thought experiment 89 3.4 Mathematical definition 90 3.5 Random complexity and structural complexity 91 3.6 Recent progress 92 3.7 Less undecidability 93 3.8 Experimentation 94 3.9 Appendices 95 3.9.1 Complexification 95 3.9.2 Random and structural complexity 96 3.9.3 Incalculable but approximate 97 3.9.4 The law of slow growth 98 3.9.5 Experimental evaluation of K(s) and P(s) 98 3.10 References 99 Chapter 4 Leveraging Complexity in Oncology - A Data Narrative 101 Xosé M. Fernández 4.1 Large collaborative research initiatives - the Human Genome Project 104 4.2 Human cell atlas - unraveling complexity 105 4.3 From bench to bedside 107 4.4 The battle with cancer 109 4.5 Health economics - cost is another matter 112 4.6 From molecules to medicine 115 4.7 Artificial intelligence 117 4.8 The fourth paradigm 120 4.9 Modeling the complexity of cancer 121 4.10 References 124 Chapter 5 Complexity or Complexities of Information: The Dimensions of Complexity 129 Jacques Printz 5.1 Introduction 129 5.2 A brief historical overview 130 5.3 The phenomenology of complexity in systems engineering 131 5.3.1 Measuring the complexity of an assembly through the integration process and tests 134 5.4 The four dimensions of complexity 138 5.5 The term "simplexity": A remark on Richard Feynman's Nobel lecture 142 5.6 Computational volume: Remarks on the first quantification of complexity 144 5.6.1 Quantifying interactions and functional dependencies 145 5.7 References 151 List of Authors 153 Index 155
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