000 04238nam a22005295i 4500
001 978-3-319-75868-8
003 DE-He213
005 20210201191438.0
007 cr nn 008mamaa
008 180307s2018 gw | s |||| 0|eng d
020 _a9783319758688
_9978-3-319-75868-8
050 4 _aTK1-9971
072 7 _aTJK
_2bicssc
072 7 _aTEC041000
_2bisacsh
072 7 _aTJK
_2thema
082 0 4 _a621.382
_223
100 1 _aHe, Xiaofan.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aAdversary Detection For Cognitive Radio Networks
_h[electronic resource] /
_cby Xiaofan He, Huaiyu Dai.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aX, 74 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Electrical and Computer Engineering,
_x2191-8112
500 _aAcceso multiusuario
520 _aThis SpringerBrief provides a comprehensive study of the unique security threats to cognitive radio (CR) networks and a systematic investigation of the state-of-the-art in the corresponding adversary detection problems. In addition, detailed discussions of the underlying fundamental analytical tools and engineering methodologies of these adversary detection techniques are provided, considering that many of them are quite general and have been widely employed in many other related fields. The exposition of this book starts from a brief introduction of the CR technology and spectrum sensing in Chapter 1. This is followed by an overview of the relevant security vulnerabilities and a detailed discussion of two security threats unique to CR networks, namely, the primary user emulation (PUE) attack and the Byzantine attack. To better prepare the reader for the discussions in later chapters, preliminaries of analytic tools related to adversary detection are introduced in Chapter 2. In Chapter 3, a suite of cutting-edge adversary detection techniques tailor-designed against the PUE and the Byzantine attacks are reviewed to provide a clear overview of existing research in this field. More detailed case studies are presented in Chapters 4 - 6. Specifically, a physical-layer based PUE attack detection scheme is presented in Chapter 4, while Chapters 5 and 6 are devoted to the illustration of two novel detection techniques against the Byzantine attack. Concluding remarks and outlooks for future research are provided in Chapter 7. The primary audience for this SpringerBrief include network engineers interested in addressing adversary detection issues in cognitive radio networks, researchers interested in the state-of-the-art on unique security threats to cognitive radio networks and the corresponding detection mechanisms. Also, graduate and undergraduate students interested in obtaining comprehensive information on adversary detection in cognitive radio networks and applying the underlying techniques to address relevant research problems can use this SpringerBrief as a study guide. .
541 _fUABC ;
_cTemporal ;
_d01/01/2021-12/31/2023.
650 0 _aElectrical engineering.
650 0 _aData protection.
650 1 4 _aCommunications Engineering, Networks.
_0https://scigraph.springernature.com/ontologies/product-market-codes/T24035
650 2 4 _aSecurity.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I28000
700 1 _aDai, Huaiyu.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319758671
776 0 8 _iPrinted edition:
_z9783319758695
830 0 _aSpringerBriefs in Electrical and Computer Engineering,
_x2191-8112
856 4 0 _zLibro electrónico
_uhttp://148.231.10.114:2048/login?url=https://doi.org/10.1007/978-3-319-75868-8
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cLIBRO_ELEC
999 _c243581
_d243580