| 000 | 03382nam a22005295i 4500 | ||
|---|---|---|---|
| 001 | 978-3-030-37962-9 | ||
| 003 | DE-He213 | ||
| 005 | 20220801214717.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 200208s2020 sz | s |||| 0|eng d | ||
| 020 |
_a9783030379629 _9978-3-030-37962-9 |
||
| 024 | 7 |
_a10.1007/978-3-030-37962-9 _2doi |
|
| 050 | 4 | _aTK7867-7867.5 | |
| 072 | 7 |
_aTJFC _2bicssc |
|
| 072 | 7 |
_aTEC008010 _2bisacsh |
|
| 072 | 7 |
_aTJFC _2thema |
|
| 082 | 0 | 4 |
_a621.3815 _223 |
| 100 | 1 |
_aRokka Chhetri, Sujit. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _939967 |
|
| 245 | 1 | 0 |
_aData-Driven Modeling of Cyber-Physical Systems using Side-Channel Analysis _h[electronic resource] / _cby Sujit Rokka Chhetri, Mohammad Abdullah Al Faruque. |
| 250 | _a1st ed. 2020. | ||
| 264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2020. |
|
| 300 |
_aXVI, 235 p. 111 illus., 106 illus. in color. _bonline resource. |
||
| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
||
| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
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| 520 | _aThis book provides a new perspective on modeling cyber-physical systems (CPS), using a data-driven approach. The authors cover the use of state-of-the-art machine learning and artificial intelligence algorithms for modeling various aspect of the CPS. This book provides insight on how a data-driven modeling approach can be utilized to take advantage of the relation between the cyber and the physical domain of the CPS to aid the first-principle approach in capturing the stochastic phenomena affecting the CPS. The authors provide practical use cases of the data-driven modeling approach for securing the CPS, presenting novel attack models, building and maintaining the digital twin of the physical system. The book also presents novel, data-driven algorithms to handle non- Euclidean data. In summary, this book presents a novel perspective for modeling the CPS. · Provides an introduction to the data-driven modeling of cyber-physical systems (CPS), to aid in capturing the stochastic phenomenon affecting CPS; · Describes practical applications for securing the CPS as well as building the digital twin of the physical twin of CPS; · Includes coverage of machine learning and artificial intelligence algorithms for data-driven modeling of the CPS; Provides novel algorithms for handling not just Euclidean data, but also non-Euclidean data. | ||
| 650 | 0 |
_aElectronic circuits. _919581 |
|
| 650 | 0 |
_aCooperating objects (Computer systems). _96195 |
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| 650 | 0 |
_aMicroprocessors. _939968 |
|
| 650 | 0 |
_aComputer architecture. _93513 |
|
| 650 | 1 | 4 |
_aElectronic Circuits and Systems. _939969 |
| 650 | 2 | 4 |
_aCyber-Physical Systems. _932475 |
| 650 | 2 | 4 |
_aProcessor Architectures. _939970 |
| 700 | 1 |
_aAl Faruque, Mohammad Abdullah. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _939971 |
|
| 710 | 2 |
_aSpringerLink (Online service) _939972 |
|
| 773 | 0 | _tSpringer Nature eBook | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030379612 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030379636 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030379643 |
| 856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-030-37962-9 |
| 912 | _aZDB-2-ENG | ||
| 912 | _aZDB-2-SXE | ||
| 942 | _cEBK | ||
| 999 |
_c76659 _d76659 |
||