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E-raamat: How to Find a Needle in a Haystack: From the Insider Threat to Solo Perpetrators [Taylor & Francis e-raamat]

  • Formaat: 120 pages, 9 Tables, black and white; 19 Line drawings, black and white; 19 Illustrations, black and white
  • Ilmumisaeg: 05-Sep-2022
  • Kirjastus: CRC Press
  • ISBN-13: 9781003289647
  • Taylor & Francis e-raamat
  • Hind: 69,23 €*
  • * hind, mis tagab piiramatu üheaegsete kasutajate arvuga ligipääsu piiramatuks ajaks
  • Tavahind: 98,90 €
  • Säästad 30%
  • Formaat: 120 pages, 9 Tables, black and white; 19 Line drawings, black and white; 19 Illustrations, black and white
  • Ilmumisaeg: 05-Sep-2022
  • Kirjastus: CRC Press
  • ISBN-13: 9781003289647
"Searching for a needle in a haystack is an important task in several contexts of data analysis and decision-making. Examples include identifying the insider threat within an organization, the prediction of failure in industrial production or pinpointingthe unique signature of a solo perpetrator, such as school shooter or a lone wolf terrorist"--

Searching for a needle in a haystack is an important task in several contexts of data analysis and decision-making. Examples include identifying the insider threat within an organization, the prediction of failure in industrial production, or pinpointing the unique signature of a solo perpetrator, such as a school shooter or a lone wolf terrorist. It is a challenge different from that of identifying a rare event (e.g., a tsunami) or detecting anomalies because the "needle" is not easily distinguished from the haystack. This challenging context is imbued with particular difficulties, from the lack of sufficient data to train a machine learning model through the identification of the relevant features and up to the painful price of false alarms, which might cause us to question the relevance of machine learning solutions even if they perform well according to common performance criteria. In this book, Prof. Neuman approaches the problem of finding the needle by specifically focusing on the human factor, from solo perpetrators to insider threats. Providing for the first time a deep, critical, multidimensional, and methodological analysis of the challenge, the book offers data scientists and decision makers a deep scientific foundational approach combined with a pragmatic practical approach that may guide them in searching for a needle in a haystack.



Searching for a needle in a haystack is an important task in several contexts of data analysis and decision-making. Examples include identifying the insider threat within an organization, the prediction of failure in industrial production or pinpointing the unique signature of a solo perpetrator, such as school shooter or a lone wolf terrorist.
Acknowledgments vii
Preface ix
1 The Needle Challenge: From Shipping Vessels to the Insider Threat
1(10)
2 What Is a Needle in a Haystack?: A Lesson from Miss Lucy and Vladimir Putin
11(10)
3 How Are Rare Events Formed?: Modeling through the Galton Machine
21(10)
4 Crying Wolf: False Alarms and Their Price
31(12)
5 Why Is It Difficult to Find the Needle?: On Rare and Common Paths
43(8)
6 Why Do We Fail to Find the Needle?: The Binary Fallacy and the Bayesian Approach
51(14)
7 How to Reduce the Size of the Haystack: On Impostors, Cats, and False Positives
65(20)
8 Needles in the Wild: Some Lessons from Nature
85(6)
9 Lupus and the Needle: A Contextual-Dynamic Approach to the Needle Challenge
91(6)
10 How to Deal with Tiny Datasets: The Power of Al
97(18)
11 Concluding Discussion: Isolated Lights in the Abyss of Ignorance
115(4)
Index 119
Yair Neuman is a full professor at Ben-Gurion University of the Negev. He is the author of numerous papers and eight books published by leading academic publishers from Cambridge University Press to Brill and Springer Nature. He is consistently ranked within the top 3% of researchers on Academia.edu (https://bgu.academia.edu/YairNeuman). Prof. Neumans computational and data analytics projects have been supported by government agencies (e.g. IARPA the Intelligence Advanced Research Projects Activity) and world-leading banks, and he has served as a scientific advisor to various clients in the private sector. His novel data analysis methodologies have been published in leading journals and cover human, industrial, medical, and financial data.