| 000 | 03915nam a22005295i 4500 | ||
|---|---|---|---|
| 001 | 978-3-030-74896-8 | ||
| 003 | DE-He213 | ||
| 005 | 20240423125443.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 211001s2021 sz | s |||| 0|eng d | ||
| 020 |
_a9783030748968 _9978-3-030-74896-8 |
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| 024 | 7 |
_a10.1007/978-3-030-74896-8 _2doi |
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| 050 | 4 | _aQA75.5-76.95 | |
| 072 | 7 |
_aUY _2bicssc |
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_aCOM000000 _2bisacsh |
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| 082 | 0 | 4 |
_a004 _223 |
| 100 | 1 |
_aMongeau, Scott. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
| 245 | 1 | 0 |
_aCybersecurity Data Science _h[electronic resource] : _bBest Practices in an Emerging Profession / _cby Scott Mongeau, Andrzej Hajdasinski. |
| 250 | _a1st ed. 2021. | ||
| 264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2021. |
|
| 300 |
_aXXVII, 388 p. 99 illus. _bonline resource. |
||
| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
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| 505 | 0 | _a1. 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 | _aThis 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. | ||
| 650 | 0 | _aComputer science. | |
| 650 | 0 | _aBusiness information services. | |
| 650 | 0 | _aMachine learning. | |
| 650 | 1 | 4 | _aComputer Science. |
| 650 | 2 | 4 | _aIT in Business. |
| 650 | 2 | 4 | _aMachine Learning. |
| 700 | 1 |
_aHajdasinski, Andrzej. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer Nature eBook | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030748951 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030748975 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030748982 |
| 856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-030-74896-8 |
| 912 | _aZDB-2-SCS | ||
| 912 | _aZDB-2-SXCS | ||
| 942 | _cSPRINGER | ||
| 999 |
_c178104 _d178104 |
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