BOTNET

• Al Ebri N, Otrok H, Mourad A, Al-Hammadi Y (2013) Botnet detection: a cooperative game theoretical correlation-based model. In: Third international conference on communications and information technology (ICCIT)

  Google Scholar 

• Alzahrani AJ, Ghorbani AA (2014) SMS mobile botnet detection using a multi-agent system: research in progress. A CySe’14, ACM, France

  Google Scholar 

• Badis H, Doyen G, Khatoun R (2014) Understanding Botclouds from a system perspective: a principal component analysis. In: IEEE network operations and management symposium (NOMS)

  Google Scholar 

• Binkley JR, Singh S (2006) An algorithm for anomaly-based botnet detection. In: Proceedings of USENIX steps to reducing unwanted traffic on the internet workshop

  Google Scholar 

• Choi H, Lee H, Lee H, Kim H (2007) Botnet detection by monitoring group activities in DNS traffic. In: Proceedings of 7th IEEE international conference on computer and information technology

  Google Scholar 

• Cooke E, Jahanian F, McPherson D (2005) The zombie roundup: understanding, detecting, and disrupting botnets. In: ACM USENIX workshop on steps to reducing unwanted trace on the internet SRUTI, vol 7, pp 39–44

  Google Scholar 

• Dagon D (2005) Botnet detection and response, the network is the infection. In: OARC workshop

  Google Scholar 

• Davis JJ, Clark AJ (2011) Data preprocessing for anomaly based network intrusion detection: A review. Comput Secur 30(6–7):353–375

  Article  Google Scholar 

• Derhab A, Fahad AB, Khurram BMM, Xiang KY (2014) Spam trapping system: novel security framework to fight against spam botnets. In: IEEE 21st international conference on telecommunications (ICT)

  Google Scholar 

• Feily M, Shahrestani A (2009) A survey of botnet and botnet detection. In: NAv6 IMPACT research team Kuala Lumpur, Malaysia

  Google Scholar 

• Garant D, Lu W, Keene USNH (2013) Mining botnet behaviors on the large-scale web application community. In: 27th international conference on advanced information networking and applications workshops (WAINA)

  Google Scholar 

• Geers K (2011) Strategic cyber security. CCDCOE, NATO Cooperative Cyber Defense Center of Excellence, 19–22 June 2011

  Google Scholar 

• Goebel J, Holz T (2007) Rishi: identify bot contaminated hosts by IRC nickname evaluation. In: Proceedings of 1st workshop on hot topics in understanding botnets

  Google Scholar 

• Gu G, Porras P, Yegneswaran V, Fong M, Lee W (2007) BotHunter: detecting malware infection through IDS-driven dialog correlation. In: SS’07 proceedings of 16th USENIX security symposium

  Google Scholar 

• Gu D, Zhang J, Lee W (2008) Botsniffer: detecting botnet command and control channels in network traffic. In: Proceedings of 15th annual network and distributed system security symposium (NDSS’08)

  Google Scholar 

• Gu G, Perdisci R, Zhang J, Lee W (2008) Botminer: clustering analysis of network traffic for protocol- and structure independent botnet detection

  Google Scholar 

• Ji Y, He Y, Li Q, Guo D (2013) BotCatch: a behavior and signature correlated bot detection approach. Jilin University

  Google Scholar 

• Karasaridis A, Rexroad B, Hoeflin D (2006) Wide-scale botnet detection and characterization. In: Proceedings of 1st workshop on hot topics in understanding botnets

  Google Scholar 

• Khosroshahy M, Qiu D, Mehmet Ali MK (2013) Botnets in 4G cellular networks: platforms to launch DDoS attacks against the air interface. In: 2013 international conference on selected topics in mobile and wireless networking (MoWNeT)

  Google Scholar 

• Kim W, Jeong O-R, Kim C, So J, Seongnam G-D (2010) On botnets, Korea, ii WAS-2010, Paris, France, pp 461–701

  Google Scholar 

• Klaper D, Hovy E (2014) A taxonomy and a knowledge portal for cybersecurity. In: ACM proceedings of the 15th annual international conference on digital government research, pp 79–85

  Google Scholar 

• Kristoff J (2004) Botnets. In: 32nd meeting of the North American network operators group

  Google Scholar 

• Lu C, Brooks RR (2012) Timing analysis in P2P botnet traffic using probabilistic context-free grammars. In: CSIIRW ’12, USA

  Google Scholar 

• Lu W, Rammidi G, Ghorbani AA (2011) Clustering botnet communication traffic based on n-gram feature selection. Comput Commun 34:502–514

  Article  Google Scholar 

• Lu Z, Wang W, Wang C (2014) How can botnets cause storms? Understanding the evolution and impact of mobile botnets. In: Proceedings of IEEE conference on computer communications (INFOCOM ‘14)

  Google Scholar 

• Masud MM, Gao J, Khan L, Han J (2008) Peer to Peer botnet detection for cybersecurity: a data mining approach. In: CSIIRW 2008

  Google Scholar 

• Masud MM, Al-khateeb T, Khan L, Thuraisingham B, Hamlen KW (2008) Flow-based identification of Botnet traffic by mining multiple log file. In: Proceedings international conference on distributed frameworks and applications

  Google Scholar 

• Mendonça L, Santos H (2012) Botnets: a heuristic-based detection framework. In: SIN’12, India, pp 25–27

  Google Scholar 

• Narang P, Reddy JM, Hota C (2013) Feature selection for detection of Peer-to-Peer botnet traffic. In: COMPUTE’13, Vellore, Tamil Nadu, India, pp 22–24

  Google Scholar 

• Ollmann G, Damballa Inc (2009) Botnet Communication Topologies—Understanding the intricacies of botnet Command-and-Control. In: WP Botnet Communication Primer

  Google Scholar 

• Pieterse H, Olivier MS (2012) Android botnets on the rise: trends and characteristics. In: IEEE information security for South Africa (ISSA)

  Google Scholar 

• Ramachandran NFA, Dagon D (2006) Revealing botnet membership using DNSBL counter-intelligence. In: Proceedings of 2nd workshop on steps to reducing unwanted traffic on the internet

  Google Scholar 

• Rodrıguez Gomez RA, Macia Fernandez G, Garcia-Teodoro P (2013) Survey and taxonomy of botnet research through life-cycle. ACM Comput Surv 45(4):10

  Google Scholar 

• Sadeghian A, Zamani M (2014) Detecting and preventing DDoS attacks in botnets by the help of self triggered black holes. In: 2014 Asia-Pacific conference on computer aided system engineering (APCASE)

  Google Scholar 

• Savenko O, Lysenko S, Kryshchuk A, Klots Y (2013) Botnet detection technique for corporate area network. In: IEEE 7th international conference on intelligent data acquisition and advanced computing systems (IDAACS)

  Google Scholar 

• Schonewille A, van Helmond DJ (2006) The domain name service as an IDS. Master’s Project, University of Amsterdam, Netherlands

  Google Scholar 

• Seals T (2017) Leet IoT botnet bursts on the scene with massive DDoS attack. Infosecurity Magazine News, 3 Jan 2017. https://www.infosecurity-magazine.com/news/leet-iot-botnet-bursts-on-the-scene/

• Snort IDS (2006) Snort IDS web page. http://www.snort.org

• Stawowski M (2014) Practical defense-in-depth protection against botnets. ISSA Senior Member, Poland Chapter

  Google Scholar 

• Stevanovic M, Pedersen JM (2014) An efficient flow-based botnet detection using supervised machine learning. In: International conference on computing, networking and communications (ICNC)

  Google Scholar 

• Strayer W, Lapsely D, Walsh R (2008) Botnet detection based on network behavior. In: Botnet detection, Springer, Berlin, pp 1–24

  Google Scholar 

• Strayer W, Lapsley D, Walsh B, Livadas C (2008) Botnet detection based on network behavior. In: Advances in information security. Springer, Berlin

  Google Scholar 

• Thomas K (2015) Nine bad botnets and the damage they did, we live security blog on security news, views, and insight from the ESET experts, 25 Feb 2015. http://www.welivesecurity.com/2015/02/25/nine-bad-botnets-damage/

• Ullah I, Khan N, Aboalsamh HA (2013) Survey on botnet: its architecture, detection, prevention and mitigation. In: 10th IEEE international conference on networking, sensing and control (ICNSC)

  Google Scholar 

• Valeur F, Vigna G, Kruegel C, Kemmerer R (2004) Comprehensive approach to intrusion detection alert correlation. IEEE Trans Dependable Secure Comput 1(3):146–169

  Article  Google Scholar 

• Wang B, Li Z, Tu H, Ma J (2009) Measuring Peer-to-Peer botnets using control flow stability. In: IEEE international conference on availability, reliability and security

  Google Scholar 

• Zade AR, Patil SH (2011) A survey on various defense mechanisms against application layer distributed denial of service attack. Int J Comput Sci Eng (IJCSE) 3(11)

  Google Scholar 

• Zand A, Vigna G, Yan X, Kruegel C (2014) Extracting probable command and control signatures for detecting botnets. In: SAC’14, Gyeongju, Korea, pp 24–28

  Google Scholar 

• Zargar ST, Joshi J, Tipper D (2013) A survey of defense mechanisms against distributed denial of service (DDoS) flooding attacks. In: IEEE communications surveys and tutorials

  Google Scholar 

• Zarras A, Papadogiannakis A, Gawlik R, Holz T (2014) Automated Generation of models for fast and precise detection of HTTP-based malware. In: Twelfth annual international conference on privacy, security and trust (PST)

  Google Scholar 

Download references