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Cybersecurity data sciencebest pract...

Hajdasinski, Andrzej.

Cybersecurity data sciencebest practices in an emerging profession /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Cybersecurity data scienceby Scott Mongeau, Andrzej Hajdasinski.
Reminder of title:	best practices in an emerging profession /
Author:	Mongeau, Scott.
other author:	Hajdasinski, Andrzej.
Published:	Cham :Springer International Publishing :2021.
Description:	xxvii, 388 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Computer security.
Online resource:	https://doi.org/10.1007/978-3-030-74896-8
ISBN:	9783030748968$q(electronic bk.)

Cybersecurity data sciencebest practices in an emerging profession /
Mongeau, Scott.

Cybersecurity data sciencebest practices in an emerging profession /[electronic resource] :by Scott Mongeau, Andrzej Hajdasinski. - Cham :Springer International Publishing :2021. - xxvii, 388 p. :ill., digital ;24 cm.

1. Summary Introduction -- 2. Phase I: CSDS as an Emerging Profession - Diagnostic Literature Analysis -- 3 Phase II: CSDS Practitioners - Diagnostic Opinion Research and Gap Analysis -- 4 Phase III: CSDS Gap-Prescriptions - Design Science Problem Solving -- 5. Research Conclusions and Discussion -- 6. Managerial Recommendations -- References.

This book encompasses a systematic exploration of Cybersecurity Data Science (CSDS) as an emerging profession, focusing on current versus idealized practice. This book also analyzes challenges facing the emerging CSDS profession, diagnoses key gaps, and prescribes treatments to facilitate advancement. Grounded in the management of information systems (MIS) discipline, insights derive from literature analysis and interviews with 50 global CSDS practitioners. CSDS as a diagnostic process grounded in the scientific method is emphasized throughout Cybersecurity Data Science (CSDS) is a rapidly evolving discipline which applies data science methods to cybersecurity challenges. CSDS reflects the rising interest in applying data-focused statistical, analytical, and machine learning-driven methods to address growing security gaps. This book offers a systematic assessment of the developing domain. Advocacy is provided to strengthen professional rigor and best practices in the emerging CSDS profession. This book will be of interest to a range of professionals associated with cybersecurity and data science, spanning practitioner, commercial, public sector, and academic domains. Best practices framed will be of interest to CSDS practitioners, security professionals, risk management stewards, and institutional stakeholders. Organizational and industry perspectives will be of interest to cybersecurity analysts, managers, planners, strategists, and regulators. Research professionals and academics are presented with a systematic analysis of the CSDS field, including an overview of the state of the art, a structured evaluation of key challenges, recommended best practices, and an extensive bibliography.

ISBN: 9783030748968$q(electronic bk.)

Standard No.: 10.1007/978-3-030-74896-8doiSubjects--Topical Terms:

184416
Computer security.

LC Class. No.: QA76.9.A25

Dewey Class. No.: 005.8

Cybersecurity data sciencebest practices in an emerging profession /
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505 0 $a 1. Summary Introduction -- 2. Phase I: CSDS as an Emerging Profession - Diagnostic Literature Analysis -- 3 Phase II: CSDS Practitioners - Diagnostic Opinion Research and Gap Analysis -- 4 Phase III: CSDS Gap-Prescriptions - Design Science Problem Solving -- 5. Research Conclusions and Discussion -- 6. Managerial Recommendations -- References.
520 $a This book encompasses a systematic exploration of Cybersecurity Data Science (CSDS) as an emerging profession, focusing on current versus idealized practice. This book also analyzes challenges facing the emerging CSDS profession, diagnoses key gaps, and prescribes treatments to facilitate advancement. Grounded in the management of information systems (MIS) discipline, insights derive from literature analysis and interviews with 50 global CSDS practitioners. CSDS as a diagnostic process grounded in the scientific method is emphasized throughout Cybersecurity Data Science (CSDS) is a rapidly evolving discipline which applies data science methods to cybersecurity challenges. CSDS reflects the rising interest in applying data-focused statistical, analytical, and machine learning-driven methods to address growing security gaps. This book offers a systematic assessment of the developing domain. Advocacy is provided to strengthen professional rigor and best practices in the emerging CSDS profession. This book will be of interest to a range of professionals associated with cybersecurity and data science, spanning practitioner, commercial, public sector, and academic domains. Best practices framed will be of interest to CSDS practitioners, security professionals, risk management stewards, and institutional stakeholders. Organizational and industry perspectives will be of interest to cybersecurity analysts, managers, planners, strategists, and regulators. Research professionals and academics are presented with a systematic analysis of the CSDS field, including an overview of the state of the art, a structured evaluation of key challenges, recommended best practices, and an extensive bibliography.
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