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Socialbots

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References

  • Abokhodair N, Yoo D, McDonald DW (2015) Dissecting a social botnet: growth, content and influence in Twitter. In: Proceedings of the 18th ACM conference on computer supported cooperative work & social computing, pp 839–851

    Google Scholar 

  • Ahmad I (2015) How many internet and #SocialMedia users are fake? http://www.digitalinformationworld.com/2015/04/infographic-how-many-internets-users-are-fake.html. Accessed 2 Apr 2015

  • Aiello LM, Deplano M, Schifanella R, Ruffo G (2012) People are strange when you’re a stranger: impact and influence of bots on social networks. Links 697(483,151):1–566

    Google Scholar 

  • Ask M, Bondarenko P, Rekdal JE, Nordbø A, Bloemerus P, Piatkivskyi D (2013) Advanced persistent threat (APT) beyond the hype. Project report in IMT4582 Network security at GjoviN University College, Springer

    Google Scholar 

  • Benevenuto F, Magno G, Rodrigues T, Almeida V (2010) Detecting spammers on twitter. In: CEAS, The seventh annual collaboration, electronic messaging, anti-abuse and spam conference, July 2010, vol 6, p 12

    Google Scholar 

  • Berger JM, Morgan J (2015) The ISIS Twitter census: defining and describing the population of ISIS supporters on Twitter. The Brookings project on US relations with the Islamic World 3(20)

    Google Scholar 

  • Beutel A, Xu W, Guruswami V, Palow C, Faloutsos C (2013) Copycatch: stopping group attacks by spotting lockstep behavior in social networks. In: Proceedings of the 22nd international conference on World Wide Web, pp 119–130

    Google Scholar 

  • Bilge L, Strufe T, Balzarotti D, Kirda E (2009) All your contacts are belong to us: automated identity theft attacks on social networks. In: Proceedings of the 18th international conference on World wide web, pp 551–560

    Google Scholar 

  • Bokobza Y, Paradise A, Rapaport G, Puzis R, Shapira B, Shabtai A (2015) Leak sinks: the threat of targeted social eavesdropping. In: 2015 IEEE/ACM international conference on advances in social networks analysis and mining, pp 375–382

    Google Scholar 

  • Boshmaf Y, Muslukhov I, Beznosov K, Ripeanu M (2011) The socialbot network: when bots socialize for fame and money. In: Proceedings of the 27th annual computer security applications conference, pp 93–102

    Google Scholar 

  • Boshmaf Y, Muslukhov I, Beznosov K, Ripeanu M (2012) Key challenges in defending against malicious socialbots. In: Presented as part of the 5th USENIX workshop on large-scale exploits and emergent threats

    Google Scholar 

  • Boshmaf Y, Muslukhov I, Beznosov K, Ripeanu M (2013) Design and analysis of a social botnet. Comput Netw 57(2):556–578

    Article  Google Scholar 

  • Boshmaf Y, Ripeanu M, Beznosov K, Santos-Neto E (2015) Thwarting fake OSN profiles by predicting their victims. In: Proceedings of the 8th ACM workshop on artificial intelligence and security, pp 81–89

    Google Scholar 

  • Burghouwt P, Spruit M, Sips H (2011) Towards detection of botnet communication through social media by monitoring user activity. In: International conference on information systems security. Springer, Berlin/Heidelberg, pp 131–143

    Chapter  Google Scholar 

  • Cao Q, Sirivianos M, Yang X, Pregueiro T (2012) Aiding the detection of fake profiles in large scale social online services. In: Proceedings of the 9th USENIX conference on networked systems design and implementation, pp 15–15

    Google Scholar 

  • Cao Q, Yang X, Yu J, Palow C (2014) Uncovering large groups of active malicious profiles in online social networks. In: Proceedings of the 2014 ACM SIGSAC conference on computer and communications security, pp 477–488

    Google Scholar 

  • Chen P, Desmet L, Huygens C (2014) A study on advanced persistent threats. In: Communications and multimedia security, pp 63–72

    Google Scholar 

  • Chu Z, Gianvecchio S, Wang H, Jajodia S (2010) Who is tweeting on Twitter: human, bot, or cyborg? In: Proceedings of the 26th annual computer security applications conference, pp 21–30

    Google Scholar 

  • Danezis G, Mittal P (2009) SybilInfer: detecting sybil nodes using social networks. In: NDSS, presented at NDSS, California, 8–11 Feb 2009

    Google Scholar 

  • Davis CA, Varol O, Ferrara E, Flammini A, Menczer F (2016) Botornot: a system to evaluate social bots. In: Proceedings of the 25th international conference companion on World Wide Web, pp 273–274

    Google Scholar 

  • Dickerson JP, Kagan V, Subrahmanian VS (2014) Using sentiment to detect bots on Twitter: are humans more opinionated than bots? In: Advances in social networks analysis and mining (ASONAM), 2014 IEEE/ACM international conference on, pp 620–627

    Google Scholar 

  • Douceur JR (2002) The sybil attack. In: International workshop on peer-to-peer systems, pp 251–260

    Google Scholar 

  • Egele M, Stringhini G, Kruegel C, Vigna G (2015) Towards detecting compromised profiles on social networks. IEEE Trans Dependable Secure Comput

    Google Scholar 

  • Elyashar A, Fire M, Kagan D, Elovici Y (2013) Homing socialbots: intrusion on a specific organization’s employee using Socialbots. In: Proceedings of the 2013 IEEE/ACM international conference on ASONAM, pp 1358–1365

    Google Scholar 

  • Elyashar A, Fire M, Kagan D, Elovici Y (2014) Guided socialbots: infiltrating the social networks of specific organizations’ employees. AI Commun 29(1):87–106

    Article  MathSciNet  Google Scholar 

  • Ferrara E (2015) Manipulation and abuse on social media by Emilio Ferrara with Ching-man Au Yeung as coordinator. ACM SIGWEB Newsletter, (Spring):4

    Google Scholar 

  • Ferrara E, Varol O, Davis C, Menczer F, Flammini A (2014) The rise of social bots. arXiv preprint arXiv:1407.5225

    Google Scholar 

  • Finkle J (2014) “Pony” botnet steals bitcoins, digital currencies: Trustwave. http://www.reuters.com/article/us-bitcoin-security-idUSBREA1N1JO20140224. Accessed 1 Jan 2014

  • Fire M, Puzis R (2012) Organization mining using online. Netw Spatial Econ 16(2):545–578

    Article  MathSciNet  MATH  Google Scholar 

  • Freitas CA, Benevenuto F, Ghosh S, Veloso A (2014) Reverse engineering socialbot infiltration strategies in twitter. arXiv preprint arXiv:1405.4927

    Google Scholar 

  • Gee G, Teh H (2010) Twitter spammer profile detection. Unpublished

    Google Scholar 

  • Gilbert E, Karahalios K (2009) Predicting tie strength with social media. In: Proceedings of the SIGCHI conference on human factors in computing systems, pp 211–220

    Google Scholar 

  • Holz T, Steiner M, Dahl F, Biersack E, Freiling FC (2008) Measurements and mitigation of peer-to-peer-based botnets: a case study on storm worm. LEET 8(1):1–9

    Google Scholar 

  • Hwang T, Pearce I, Nanis M (2012) Socialbots: voices from the fronts. Interactions 19(2):38–45

    Article  Google Scholar 

  • Ji Y, He Y, Jiang X, Li Q (2014) Towards social botnet behavior detecting in the end host. In: 2014 20th IEEE international conference on parallel and distributed systems (ICPADS), pp 320–327

    Google Scholar 

  • Ji Y, He Y, Jiang X, Cao J, Li Q (2016) Combating the evasion mechanisms of social bots. Computers & Security 58:230–249

    Article  Google Scholar 

  • Jin X, Lin C, Luo J, Han J (2011) A data mining-based spam detection system for social media networks. Proceedings VLDB Endowment 4(12):1458–1461

    Google Scholar 

  • Jin L, Joshi JB, Anwar M (2013) Mutual-friend based attacks in social network systems. Comput Secur 37:15–30

    Article  Google Scholar 

  • Jurgens D (2013) That’s what friends are for: inferring location in online social media platforms based on social relationships. ICWSM 13:273–282

    Google Scholar 

  • Karlinsky A (2014) How cybercriminals monetize information obtained from social networks. https://securityintelligence.com/how-cybercriminals-monetize-information-obtained-from-social-networks/. Accessed 3 Sep 2014

  • Kim Y, Kim I, Park N (2014) Analysis of cyber attacks and security intelligence. In: Mobile, ubiquitous, and intelligent computing, pp 489–494

    Google Scholar 

  • Krombholz K, Merkl D, Weippl E (2012) Fake identities in social media: a case study on the sustainability of the Facebook business model. J Serv Sci Res 4(2):175–212

    Article  Google Scholar 

  • Kwak H, Lee C, Park H, Moon S (2010) What is Twitter, a social network or a news media? In: Proceedings of the 19th international conference on World wide web, pp 591–600

    Google Scholar 

  • Lee K, Caverlee J, Webb S (2010) Uncovering social spammers: social honeypots+ machine learning. In: Proceedings of the 33rd international ACM SIGIR conference on research and development in information retrieval, pp 435–442

    Google Scholar 

  • Lee K, Eoff BD, Caverlee J (2011) Seven months with the devils: a long-term study of content polluters on Twitter. Paper presented at the ICWSM, Barcelona, 17–21 Jul 2011

    Google Scholar 

  • Magdon-Ismail M, Orecchio B (2012) Guard your connections: infiltration of a trust/reputation based network. In: Proceedings of the 4th annual ACM web science conference, pp 195–204

    Google Scholar 

  • Mahmoud M, Nir M, Matrawy A (2015) A survey on botnet architectures, detection and defences. Int J Network Security 17(3):264–281

    Google Scholar 

  • Mccord M, Chuah M (2011) Spam detection on twitter using traditional classifiers. In: Autonomic and trusted computing, pp 175–186

    Google Scholar 

  • Messias J, Schmidt L, Oliveira R, Benevenuto F (2013) You followed my bot! Transforming robots into influential users in Twitter. First Monday, 18, 7–1 July 2013

    Google Scholar 

  • Mitter CW, Strohmaier M (2013) Understanding the impact of socialbot attacks in online social networks. arXiv preprint arXiv:1402.6289

    Google Scholar 

  • Mitter S, Wagner C, Strohmaier M (2014) A categorization scheme for socialbot attacks in online social networks. arXiv preprint arXiv:1402.6288

    Google Scholar 

  • Mohaisen A, Yun A, Kim Y (2010) Measuring the mixing time of social graphs. In: Proceedings of the 10th ACM SIGCOMM conference on internet measurement, pp 383–389

    Google Scholar 

  • Molok NA, Ahmad A, Chang S (2011) Information leakage through online social networking: opening the doorway for advanced persistence threats. J Aust Ins Profess Intellig Officer 19(2):38

    Google Scholar 

  • Mustafaraj E, Metaxas PT (2010) From obscurity to prominence in minutes: political speech and real-time search. Unpublished

    Google Scholar 

  • Nazario J (2009) Twitter-based Botnet Command Channel. https://www.arbornetworks.com/blog/asert/twitter-based-botnet-command-channel/. Accessed 13 Aug 2009

  • Osterman Research Consultants (2016) The need to manage social media properly. http://ostermanresearch.com/wordpress/?p=138. Accessed 17 Mar 2016

  • Paradise A, Puzis R, Shabtai A (2014) Anti-reconnaissance tools: detecting targeted socialbots. IEEE Internet Comput 18(5):11–19

    Article  Google Scholar 

  • Paradise A, Shabtai A, Puzis R (2015) Hunting organization-targeted socialbots. In: Proceedings of the 2015 IEEE/ACM international conference on advances in social networks analysis and mining 2015, pp 537–540

    Google Scholar 

  • Pernet C (2015) Reconnaissance via professional social networks. http://blog.trendmicro.com/trendlabs-security-intelligence/reconnaissance-via-professional-social-networks/. Accessed 2 Jun 2015

  • Pham CV, Hoang HX, Vu MM (2015) Preventing and detecting infiltration on online social networks. In: Computational social networks, pp 60–73

    Google Scholar 

  • Polakis I, Kontaxis G, Antonatos S, Gessiou E, Petsas T, Markatos EP (2010) Using social networks to harvest email addresses. In: Proceedings of the 9th annual ACM workshop on privacy in the electronic society, pp 11–20

    Google Scholar 

  • Puri R (2003) Bots & botnet: an overview. SANS Institute, 3:58

    Google Scholar 

  • Ratkiewicz J, Conover M, Meiss M, Gonçalves B, Patil S, Flammini A, Menczer F (2011) Truthy: mapping the spread of astroturf in microblog streams. In: Proceedings of the 20th international conference companion on World wide web, pp 249–252

    Google Scholar 

  • Ryan T, Mauch G (2010) Getting in bed with Robin Sage. Presented at Black Hat conference, Las Vegas, 24–27 Jul 2010

    Google Scholar 

  • Section 9 lab (2014) Automated linkedIn social engineering attacks. https://medium.com/section-9-lab/automated-linkedin-social-engineering-attacks-1c88573c577e. Accessed 1 Sep 2014

  • Song J, Lee S, Kim J (2011) Spam filtering in twitter using sender-receiver relationship. In: International workshop on recent advances in intrusion detection, pp 301–317

    Google Scholar 

  • Sophos Press Release (2007) Sophos Facebook ID probe shows 41% of users happy to reveal all to potential identity thieves. http://www.sophos.com/en-us/press-office/press-releases/2007/08/facebook.aspx. Accessed 14 Aug 2007

  • Stein T, Chen E, Mangla K (2011) Facebook immune system. In: Proceedings of the 4th workshop on social network systems, p 8

    Google Scholar 

  • Stringhini G, Kruegel C, Vigna G (2010) Detecting spammers on social networks. In: Proceedings of the 26th annual computer security applications conference, pp 1–9

    Google Scholar 

  • Stringhini G, Wang G, Egele M, Kruegel C, Vigna G, Zheng H, Zhao BY (2013) Follow the green: growth and dynamics in twitter follower markets. In: Proceedings of the 2013 conference on internet measurement conference, pp 163–176, ACM

    Google Scholar 

  • Subrahmanian VS, Azaria A, Durst S, Kagan V, Galstyan A, Lerman K, Waltzman R (2016) The darpa twitter bot challenge. arXiv preprint arXiv:1601.05140

    Google Scholar 

  • Sulick M (2016) Espionage and social media. https://www.thecipherbrief.com/article/espionage-and-social-media. Accessed 30 Jan 2016

  • The Web Ecology Project (2011) The 2011 socialbots competition. http://www.webecologyproject.org/category/competition

  • Thomas K, Grier C, Paxson V (2012) Adapting social spam infrastructure for political censorship. In: Presented as part of the 5th USENIX workshop on large-scale exploits

    Google Scholar 

  • Trend Micro (2015) Social media malware on the rise. http://blog.trendmicro.com/social-media-malware-on-the-rise/. Accessed 24 Feb 2015

  • Turing AM (1950) Computing machinery and intelligence. Mind 59(236):433–460

    Article  MathSciNet  Google Scholar 

  • Vogt R, Aycock J Jacobson MJ Jr (2007) Army of botnets. Presented at NDSS, California, 28 Feb–2 Mar 2007

    Google Scholar 

  • Wagner C, Mitter S, Körner C, Strohmaier M (2012) When social bots attack: modeling susceptibility of users in online social networks. In: Proceedings of the 2nd workshop on making sense of microposts (#MSM2012), pp 46–48

    Google Scholar 

  • Wang AH (2010) Detecting spam bots in online social networking sites: a machine learning approach. In: IFIP annual conference on data and applications security and privacy, pp 335–342

    Google Scholar 

  • Wang D, Irani D, Pu C (2011) A social-spam detection framework. In: 8th annual conference on collaboration, Electronic messaging, Anti-Abuse and Spam, pp 46–54

    Google Scholar 

  • Wang G, Mohanlal M, Wilson C, Wang X, Metzger M, Zheng H, Zhao BY (2012) Social turing tests: crowdsourcing sybil detection. arXiv preprint arXiv:1205.3856

    Google Scholar 

  • Wang G, Konolige T, Wilson C, Wang X, Zheng H, Zhao BY (2013) You are how you click: clickstream analysis for sybil detection. In: Presented as part of the 22nd USENIX security symposium (USENIX security 13), pp 241–256

    Google Scholar 

  • Webb S, Caverlee J, Pu C (2008) Social honeypots: making friends with a spammer near You. Presented at the CEAS, California

    Google Scholar 

  • Wei W, Xu F, Tan CC, Li Q (2012) Sybildefender: defend against sybil attacks in large social networks. In: INFOCOM, 2012 proceedings IEEE, pp 1951–1959

    Google Scholar 

  • Wuest C (2010) The risks of social networking. https://www.symantec.com/content

  • Xie Y, Yu F, Ke Q, Abadi M, Gillum E, Vitaldevaria K, Mao ZM (2012) Innocent by association: early recognition of legitimate users. In: Proceedings of the 2012 ACM conference on computer and communications security, pp 353–364

    Google Scholar 

  • Xue J, Yang, Z, Yang X, Wang X, Chen L, Dai Y (2013) Votetrust: leveraging friend invitation graph to defend against social network sybils. In: INFOCOM, 2013 proceedings IEEE, pp 2400–2408

    Google Scholar 

  • Yang Z, Wilson C, Wang X, Gao T, Zhao B, Dai Y (2011) Uncovering social network sybils in the wild. arXiv preprint arXiv:1106.5321

    Google Scholar 

  • Yu H, Kaminsky M, Gibbons PB, Flaxman AD (2006) Sybilguard: defending against sybil attacks via social networks. IEEE/ACM Trans Networking 16(3):576–589

    Article  Google Scholar 

  • Yu H et al (2008) Sybillimit: a near-optimal social network defense against sybil attacks. IEEE symposium on security and privacy

    Google Scholar 

  • Zhang X, Zhu S, Liang W (2012) Detecting spam and promoting campaigns in the twitter social network. In: 2012 I.E. 12th international conference on data mining, pp 1194–1199

    Google Scholar 

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Paradise, A., Puzis, R., Shabtai, A. (2018). Socialbots. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-7131-2_110212

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