000 04216nam a22005775i 4500
001 978-3-030-61431-7
003 DE-He213
005 20240423125435.0
007 cr nn 008mamaa
008 210104s2021 sz | s |||| 0|eng d
020 _a9783030614317
_9978-3-030-61431-7
024 7 _a10.1007/978-3-030-61431-7
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
100 1 _aAlvari, Hamidreza.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aIdentification of Pathogenic Social Media Accounts
_h[electronic resource] :
_bFrom Data to Intelligence to Prediction /
_cby Hamidreza Alvari, Elham Shaabani, Paulo Shakarian.
250 _a1st ed. 2021.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2021.
300 _aIX, 95 p. 25 illus., 19 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Computer Science,
_x2191-5776
520 _aThis book sheds light on the challenges facing social media in combating malicious accounts, and aims to introduce current practices to address the challenges. It further provides an in-depth investigation regarding characteristics of “Pathogenic Social Media (PSM),”by focusing on how they differ from other social bots (e.g., trolls, sybils and cyborgs) and normal users as well as how PSMs communicate to achieve their malicious goals. This book leverages sophisticated data mining and machine learning techniques for early identification of PSMs, using the relevant information produced by these bad actors. It also presents proactive intelligence with a multidisciplinary approach that combines machine learning, data mining, causality analysis and social network analysis, providing defenders with the ability to detect these actors that are more likely to form malicious campaigns and spread harmful disinformation. Over the past years, social media has played a major role in massive dissemination of misinformation online. Political events and public opinion on the Web have been allegedly manipulated by several forms of accounts including “Pathogenic Social Media (PSM)” accounts (e.g., ISIS supporters and fake news writers). PSMs are key users in spreading misinformation on social media - in viral proportions. Early identification of PSMs is thus of utmost importance for social media authorities in an effort toward stopping their propaganda. The burden falls to automatic approaches that can identify these accounts shortly after they began their harmful activities. Researchers and advanced-level students studying and working in cybersecurity, data mining, machine learning, social network analysis and sociology will find this book useful. Practitioners of proactive cyber threat intelligence and social media authorities will also find this book interesting and insightful, as it presents an important andemerging type of threat intelligence facing social media and the general public.
650 0 _aArtificial intelligence.
650 0 _aData mining.
650 0 _aMachine learning.
650 0 _aComputer networks
_xSecurity measures.
650 1 4 _aArtificial Intelligence.
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aMachine Learning.
650 2 4 _aMobile and Network Security.
700 1 _aShaabani, Elham.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aShakarian, Paulo.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030614300
776 0 8 _iPrinted edition:
_z9783030614324
830 0 _aSpringerBriefs in Computer Science,
_x2191-5776
856 4 0 _uhttps://doi.org/10.1007/978-3-030-61431-7
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c177968
_d177968