| 000 | 02577nam a2200349 i 4500 | ||
|---|---|---|---|
| 001 | CR9781108231954 | ||
| 003 | UkCbUP | ||
| 005 | 20240906164935.0 | ||
| 006 | m|||||o||d|||||||| | ||
| 007 | cr|||||||||||| | ||
| 008 | 161123s2022||||enk o ||1 0|eng|d | ||
| 020 | _a9781108231954 (ebook) | ||
| 020 | _z9781108415279 (hardback) | ||
| 040 |
_aUkCbUP _beng _erda _cUkCbUP |
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| 050 | 0 | 0 |
_aQA76.9.A25 _bJ37 2022 |
| 082 | 0 | 0 |
_a005.8 _223/eng/20211122 |
| 100 | 1 |
_aJaneja, Vandana P., _d1976- _eauthor. |
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| 245 | 1 | 0 |
_aData analytics for cybersecurity / _cVandana P. Janeja. |
| 264 | 1 |
_aCambridge ; New York, NY : _bCambridge University Press, _c2022. |
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| 300 |
_a1 online resource (xiii, 192 pages) : _bdigital, PDF file(s). |
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| 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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| 500 | _aTitle from publisher's bibliographic system (viewed on 10 Aug 2022). | ||
| 505 | 0 | _aIntroduction - data analytics for cybersecurity -- Understanding sources of cybersecurity data -- Introduction to data mining : clustering, classification and association rule mining -- Big data analytics and its need for cybersecurity -- Types of cyber attacks -- Anomaly detection for cyber security -- Anomaly detection -- Cybersecurity through time series and spatial data -- Cybersecurity through network and graph data -- Human centered data analytics for cyber security -- Future directions in data analytics for cybersecurity. | |
| 520 | _aAs the world becomes increasingly connected, it is also more exposed to a myriad of cyber threats. We need to use multiple types of tools and techniques to learn and understand the evolving threat landscape. Data is a common thread linking various types of devices and end users. Analyzing data across different segments of cybersecurity domains, particularly data generated during cyber-attacks, can help us understand threats better, prevent future cyber-attacks, and provide insights into the evolving cyber threat landscape. This book takes a data oriented approach to studying cyber threats, showing in depth how traditional methods such as anomaly detection can be extended using data analytics and also applies data analytics to non-traditional views of cybersecurity, such as multi domain analysis, time series and spatial data analysis, and human-centered cybersecurity. | ||
| 650 | 0 |
_aComputer security _xData processing. |
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| 650 | 0 | _aData mining. | |
| 776 | 0 | 8 |
_iPrint version: _z9781108415279 |
| 856 | 4 | 0 | _uhttps://doi.org/10.1017/9781108231954 |
| 942 |
_2ddc _cEB |
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| 999 |
_c8968 _d8968 |
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