Complexities 1 E-Book

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 301

Veröffentlichungsjahr: 2023

Beschreibung

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.

Leseprobe

Table of Contents

Cover

Table of Contents

Title Page

Copyright Page

Foreword: Sharing Complexity: An Acclaim for Complex Thinking

F.1. Omnipresent complexity

F.2. The science of complexity

F.3. The role of chance

F.4. An acclaim for complex thinking

F.5. Complexity and democracy

Preface

1 The Complexity of Cybersecurity

1.1. Formal approach to the complexity of cybersecurity

1.2. Cybersecurity in real life: Advanced persistent threats, computer networks, defense teams and complex log data

1.3. User and entity behavior analysis as a way of reducing complexity

1.4. Conclusion and future work

1.5. References

2 Complexity and Biology: When Historical Perspectives Intersect with Epistemological Analyses

2.1. Complexity throughout the history of thought on living

2.2. The living: Between potentialities and actualizations

2.3. Reductionist biotechnologies?

2.4. References

3 Two Complexities: Information and Structure Content

3.1. The simple, the random and the structured: A triangle of concepts key to a complete understanding

3.2. Calculation, the key to the solution

3.3. Thought experiment

3.4. Mathematical definition

3.5. Random complexity and structural complexity

3.6. Recent progress

3.7. Less undecidability

3.8. Experimentation

3.9. Appendices

3.10. References

4 Leveraging Complexity in Oncology – A Data Narrative

4.1. Large collaborative research initiatives – the Human Genome Project

4.2. Human cell atlas – unraveling complexity

4.3. From bench to bedside

4.4. The battle with cancer

4.5. Health economics – cost is another matter

4.6. From molecules to medicine

4.7. Artificial intelligence

4.8. The fourth paradigm

4.9. Modeling the complexity of cancer

4.10. References

5 Complexity or Complexities of Information: The Dimensions of Complexity

5.1. Introduction

5.2. A brief historical overview

5.3. The phenomenology of complexity in systems engineering

5.4. The four dimensions of complexity

5.5. The term “simplexity”: A remark on Richard Feynman’s Nobel lecture

5.6. Computational volume: Remarks on the first quantification of complexity

5.7. References

List of Authors

Index

Other titles from ISTE in Systems and Industrial Engineering – Robotics

End User License Agreement

List of Illustrations

Chapter 1

Figure 1.1. Security incidents

Figure 1.2. Malware classification (Or-Meir et al. 2019)

Figure 1.3. Malware behavior (Or-Meir et al. 2019)

Figure 1.4. Malware versus benware arms race.

Figure 1.5. Mechanism of an IFDA attack.

Figure 1.6. Fake GAN video of Barack Obama (BuzzFeedVideo 2018)

Figure 1.7. Fake person – GAN

Figure 1.8. Fake cat – GAN

Figure 1.9. Representation of an APT in the MITRE ATT&CK framework. Red column...

Figure 1.10. Number of nodes in a firewall network over one week

Figure 1.11. Examples of firewall log messages

Figure 1.12. Firewall data complexity pattern (at 2 AM on the left and 9 AM on...

Figure 1.13. Firewall network point-in-time anomaly

Figure 1.14. Overview of our embedding-based detection framework.

Figure 1.15. Base method representations during a network discovery attack.

Figure 1.16. Embedding-based representations during a network discovery attack...

Figure 1.17. Base method representation during a botnet C&C attack.

Figure 1.18. Embedding-based representations during a botnet C&C attack....

Chapter 3

Figure 3.1. Results of experiments carried out on K(s) and P(s)

Chapter 4

Figure 4.1. Photomontage showing conditional dependency diagrams. Disease– env...

Figure 4.2. US Food and Drug Administration approvals provided new hope to pat...

Figure 4.3. NMEs approved by the FDA in the period 2005–2020 alongside investm...

Figure 4.4. Fluence graph for the cancer model described in the text. Solid li...

Chapter 5

Figure 5.1. Illustration depicting the three areas of complexity.

Figure 5.2. An illustration of control energy used to manage module/thread coo...

Figure 5.3. Architecture of a robust/resilient system

List of Tables

Chapter 1

Table 1.1. Relationships between types of malware and malicious behavior

Table 1.2. Cyber-risks of malicious/criminal origin

Table 1.3. Cyber-risks of accidental origin

Table 1.4. Cyber-risk and financial impact

Table 1.5. Cybersecurity risk matrix. The colors correspond to the priority level of the problem to be taken...

Guide

Cover Page

Table of Contents

Title Page

Copyright Page

Foreword: Sharing Complexity: An Acclaim for Complex Thinking

Preface

Begin Reading

List of Authors

Index

Other titles from iSTE in Systems and Industrial Engineering – Robotics

WILEY END USER LICENSE AGREEMENT

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Systems of Systems Complexity Set

coordinated byJean-Pierre Briffaut

Volume 5

Complexities 1

Various Approaches in the Field of Techno-scientific Knowledge

Edited by

Jean-Pierre Briffaut

Foreword by

Philippe Kourilsky

First published 2023 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.

Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:

ISTE Ltd27-37 St George’s RoadLondon SW19 4EUUK

www.iste.co.uk

John Wiley & Sons, Inc.111 River StreetHoboken, NJ 07030USA

www.wiley.com

© ISTE Ltd 2023The rights of Jean-Pierre Briffaut to be identified as the author of this work have been asserted by him in accordance with the Copyright, Designs and Patents Act 1988.

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s), contributor(s) or editor(s) and do not necessarily reflect the views of ISTE Group.

Library of Congress Control Number: 2023941801

British Library Cataloguing-in-Publication DataA CIP record for this book is available from the British LibraryISBN 978-1-78630-875-7

ForewordSharing Complexity: An Acclaim for Complex Thinking

F.1. Omnipresent complexity

Complexity is everywhere, all the time. We are all confronted with it and are constantly faced with complex situations and problems to which we find solutions and adapt our behavior. Curiously, we often negotiate these unconsciously more than rationally. Only a fraction of the complex decisions we make reach our consciousness. This is a property of our brain and our organic form: our immune system (a highly complex system) operates day and night outside our conscious awareness. And that is a good thing: it saves us a lot of energy.

However, beyond this biological consideration, is it not strange that, in the face of complexity, we have so neglected our conscious mental activity? Complexity should be part of our standard intellectual arsenal, one of the major notions we should all learn at school, and one we should all share. But it is not.

Why is this? First, we often find it more convenient to ignore it. This is understandable: complexity is tiring, and taking it seriously takes time and effort. However, we also find it more appropriate and rational to ignore or reduce it. Let us not forget that it is on the basis of the deliberate reduction of complexity that much contemporary science has been built, notably classical physics and molecular biology. Today, however, this reductionism is far from being as exclusive as it was: complexity has taken its place in the “hard” sciences.

F.2. The science of complexity

The science of complexity has been born. It is a recent development, since the turning point was reached in the second half and especially toward the end of the 20th century. It covers an ever-increasing number of fields, as shown by the dazzling development of informatics, algorithms and computers combined with the increasing complexity of human-made artifacts (cars, airplanes, etc.). Artificial intelligence is a striking manifestation of this. Engineering has been turned upside down. So have the natural sciences. Increased data collection, storage, and analysis capacities have given climatology a whole new dimension. The same is true of biology, since it passed the symbolic and practical milestone of human genome sequencing in the early 2000s.

The movement does not stop at the “hard” experimental sciences. It is now reaching the social sciences. On our finite planet, the complexity of human society is increasing very rapidly due to a demographic growth whose consequences are often underestimated (there are 10 times more of us today than in 1789), as well as the multiplication of physical and virtual links between individuals and social groups (over 4 billion people are connected to the Internet, and even more have a cell phone).

The science of complexity is not yet a well-identified discipline, and this raises the question of transversality and trans-disciplinarity. As our dialogue with Jacques Printz1 shows, the exchange is as productive and fascinating as it is difficult: the different disciplines have developed their own methods and languages, making mutual understanding as essential as it is delicate.

F.3. The role of chance

Complexity calls for certain modes of reasoning. One of the most important of these concerns the distinction between what is complicated and what is complex. In our view, one of the things that sets them apart is that the complex makes room for chance. Chance may be “happy” or “unhappy”, but it is always present. This is the basis of the theory of the evolution of species, which rests on the notion that mutations in DNA are unpredictable (but not necessarily equiprobable). An airliner is complex, not just complicated, because from time-to-time unforeseen accidents occur, often unpredictable and at random.

The possible origins, for an aircraft as for a human being, are either external (from the environment; for example, a storm for an aircraft or a virus for a human being) or internal (a fire for an aircraft or cancer for a human being). In both cases, a large number of malfunctions are resolved through mechanisms that detect and correct them before they become problematic for the system as a whole. This property, which complex systems of all kinds possess to varying degrees, is known as “robustness”. Robustness is a major concept because it describes a system’s ability to function “correctly” despite external or internal hazards.

The more complex a system, the more components and links it comprises, the greater the “chances” of error and the more monitoring and control devices are required. Errors are inevitable. They can be reduced, but not totally eliminated. Perfection would mean multiplying controls to such an extent that their abundance would eventually paralyze the system. The human organism spends a great deal of resources defending itself against diseases such as microbial infections and cancer. It succeeds in the vast majority of cases: only those that have escaped a multitude of internal controls become manifest. Although it cannot control them all, our organic form should be considered “robust”. Its robustness is our insurance against life. It defends us against life’s hazards, enabling us not to live, but to survive. Without it, our lives would be short-lived.

F.4. An acclaim for complex thinking

Complex thinking is not only the work of philosophers: it is also, and perhaps above all, a by-product of the so-called hard sciences, as we have shown and stated in our last two books2. As complexity invades our daily lives, we need to learn to share its management and to “think complex”.

The ubiquity of complexity is nothing new. What is new is its growing involvement in social and technical fields, as tools emerge to better describe and manage it. New behaviors, new lifestyles and new professions are emerging.

That is why it is so important to make complex thinking our own. It is singular in more ways than one. It is more than a purely intellectual process. It must accommodate a certain amount of uncertainty inherent to complex systems and requires intellectual navigation between the whole and its parts. It encourages tolerance rather than dogmatism. It requires discussion. It requires strong ethics, because it is open to all manipulations that play on uncertainty and make it permeable to fake news and intellectual dishonesty.

F.5. Complexity and democracy

The growing complexity of the world has major political impacts. It is too often overlooked that complexity is vital to democracy. By giving many the impression that democratic regimes can no longer manage it satisfactorily, complexity has become a real citizenship issue. Issues of democracy are becoming increasingly pressing to the point where we have to ask whether it is robust enough (in the sense of the robustness of complex systems) to withstand the blows of nationalism, populism and authoritarianism, and this at a critical time when we are faced with a globalization that perpetuates and produces enormous inequalities, as well as a very serious environmental crisis.

Mastering complexity by practicing complex thinking is therefore doubly essential for our mutual future: we need to apprehend and manage increasingly complex situations, which call for adapted modes of analysis and action, but also socially difficult and potentially conflictual arbitrations. We must also succeed in doing so within the democratic framework to which we are committed.

That is why, as a citizen as much as a scientist, we offer a vibrant acclaim for complex thinking.

Philippe KOURILSKY

Member of the Académie des Sciencesand Honorary Professor at the Collège de France

Notes

1

See the afterword in Printz, J. (2023).

Organization and Pedagogy of Complexity: Systemic Case Studies and Prospects

. ISTE Ltd, London, and Wiley, New York.

2

Kourilsky, P. (2014).

Le Jeu du hasard et de la complexité

. Odile Jacob, Paris; Kourilsky, P. (2019).

De la science et de la démocratie

. Odile Jacob, Paris.

Preface

Why put in the title of this book “complexities” in the plural?

The word “complexity” is used in a wide variety of contexts to account for situations in very different realms of knowledge.

There are many ways to quantify our challenges:

design an object with many features;

perform a task;

understand the uses of a system with correlated functions;

understand the tree structure of a document search with hypertext links;

decipher a message;

become aware of an operational drift situation;

understand the motivations of the actors in a collaborative context;

react in a crisis situation;

counter the emergence of complexity, that is, facilitate the transition to simplification in the realm of thought and discourse.

In each case, approaches to attempt to control the situation may involve very different methods and techniques.

It is the ambition of this book to try to show, without aiming at a complete panorama, these varieties of approaches and behaviors vis-à-vis the obstacles that constitute complexity in the understanding and realization of human courses of action. Sometimes, for the cultural sciences in particular, these obstacles can lead to wealth insofar as the analysis leads to cross-fertilization interactions between disciplines that do not usually collaborate.

In general, it is worth noting that the specialized literature shows a clear reciprocity between the concepts of “system” and “model”. It is through astronomy that the notion of system, first understood as a material organisation in ancient Greece, has been used in the realm of knowledge. It is the Galilean revolution that brought this term into the semantic field of abstract theories (The Dialogue Concerning the Two Chief World Systems by Galileo (1632)).

As for the word “model”, it comes from the Latin modulus, diminutive of modus, “measure”. It was initially a term of architecture used to establish the relationships of proportion between the parts of an architectural work. The word “modulus” led in the Middle Ages and the Renaissance first to the word “mould”, then in the 16th century to the word “model” through the intermediary of the Italian “modello”.

The word “model” presents a congenital ambiguity, sometimes meaning the original, the ideal to achieve, and sometimes the copy, the simple realization or interpretation of an existing entity. Widely used in experimental sciences from the 19th century onwards, it appears as an instrument of intelligibility “the function of which is a function of delegation. The model is an intermediary to which we delegate the knowledge function, more precisely the still-puzzling enigma, in the presence of a field of study the access of which, for various reason is difficult to us”1.

The themes covered in the different chapters make this clear explicitly or implicitly; the concepts of “system” and “model” have a heuristic function in approaching complexity in many fields of knowledge.

The contributions are divided into two parts. The first includes contributions with technical and scientific orientations. The second deals with subject matters that are more related to the human and social sciences.

Jean-Pierre BRIFFAUT

July 2023

Note

1

Bachelard, S. (1979). Some historical aspects of the notions of model and the justification of models

.

In

Proceedings of the Colloquium Elaborating and Justifying Models.

Maloine-Doin, Paris.