eBook
Cybersecurity Data Science
| Τίτλος: | Cybersecurity Data Science |
|---|---|
| Περιγραφή: | 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. |
| Συγγραφείς: | Scott Mongeau, Andrzej Hajdasinski |
| Resource Type: | eBook. |
| Θέματα: | Computer security--Statistical methods, Computer security |
| Categories: | COMPUTERS / General, BUSINESS & ECONOMICS / Information Management, COMPUTERS / Artificial Intelligence / General, COMPUTERS / Management Information Systems, MATHEMATICS / Probability & Statistics / General |
| Βάση Δεδομένων: | eBook Index |
| FullText | Text: Availability: 0 |
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| Header | DbId: edsebk DbLabel: eBook Index An: 3049525 RelevancyScore: 956 AccessLevel: 6 PubType: eBook PubTypeId: ebook PreciseRelevancyScore: 955.975708007813 |
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| Items | – Name: Title Label: Title Group: Ti Data: Cybersecurity Data Science – Name: Abstract Label: Description Group: Ab Data: 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. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Scott+Mongeau%22">Scott Mongeau</searchLink><br /><searchLink fieldCode="AR" term="%22Andrzej+Hajdasinski%22">Andrzej Hajdasinski</searchLink> – Name: TypePub Label: Resource Type Group: TypPub Data: eBook. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Computer+security--Statistical+methods%22">Computer security--Statistical methods</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+security%22">Computer security</searchLink> – Name: SubjectBISAC Label: Categories Group: Su Data: <searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+General%22">COMPUTERS / General</searchLink><br /><searchLink fieldCode="ZK" term="%22BUSINESS+%26+ECONOMICS+%2F+Information+Management%22">BUSINESS & ECONOMICS / Information Management</searchLink><br /><searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Artificial+Intelligence+%2F+General%22">COMPUTERS / Artificial Intelligence / General</searchLink><br /><searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Management+Information+Systems%22">COMPUTERS / Management Information Systems</searchLink><br /><searchLink fieldCode="ZK" term="%22MATHEMATICS+%2F+Probability+%26+Statistics+%2F+General%22">MATHEMATICS / Probability & Statistics / General</searchLink> |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=3049525 |
| RecordInfo | BibRecord: BibEntity: Classifications: – Code: 005.8 Scheme: ddc Type: prePub Languages: – Code: eng Text: English Subjects: – SubjectFull: Computer security--Statistical methods Type: general – SubjectFull: Computer security Type: general Titles: – TitleFull: Cybersecurity Data Science Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Scott Mongeau – PersonEntity: Name: NameFull: Andrzej Hajdasinski – PersonEntity: Name: NameFull: Scott Mongeau – PersonEntity: Name: NameFull: Andrzej Hajdasinski IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2021 – D: 04 M: 10 Type: profile Y: 2021 Identifiers: – Type: isbn-print Value: 9783030748951 – Type: isbn-electronic Value: 9783030748968 Titles: – TitleFull: Cybersecurity Data Science Type: main |
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