DNS rule-based schema to botnet detection
暂无分享,去创建一个
Rosni Abdullah | Mohammed Anbar | Brij B. Gupta | Ammar Almomani | Mohammad Alauthman | Kamal Alieyan | Mohammed Anbar | B. Gupta | R. Abdullah | Ammar Almomani | Mohammad Alauthman | Kamal Alieyan
[1] Van-Hau Pham,et al. Honeypot trace forensics: The observation viewpoint matters , 2011, Future Gener. Comput. Syst..
[2] Farnam Jahanian,et al. Shades of grey: On the effectiveness of reputation-based “blacklists” , 2008, 2008 3rd International Conference on Malicious and Unwanted Software (MALWARE).
[3] Mohammad Alauthman,et al. A proposed framework for Botnet Spam-email Filtering using , 2018 .
[4] Felix C. Freiling,et al. Measuring and Detecting Fast-Flux Service Networks , 2008, NDSS.
[5] Shijie Zhou. A Survey on Fast-flux Attacks , 2015, Inf. Secur. J. A Glob. Perspect..
[6] Thomas Sinkjær,et al. Cortical excitability changes following grasping exercise augmented with electrical stimulation , 2008, Experimental Brain Research.
[7] Mohammed Azmi Al-Betar,et al. Spam E-mail Filtering using ECOS Algorithms , 2015 .
[8] K. E. Silva. How industry can help us fight against botnets: notes on regulating private-sector intervention , 2017 .
[9] Zhen Xu,et al. CMDHunter: Finding malicious domains from cyclical communication , 2016, 2016 5th International Conference on Computer Science and Network Technology (ICCSNT).
[10] Brij B. Gupta,et al. Classification of various attacks and their defence mechanism in online social networks: a survey , 2019, Enterp. Inf. Syst..
[11] Rosni Abdullah,et al. Botnets Detecting Attack Based on DNS Features , 2018, 2018 International Arab Conference on Information Technology (ACIT).
[12] G. Kirubavathi,et al. Botnets: A Study and Analysis , 2014 .
[13] Martin Roesch,et al. Snort - Lightweight Intrusion Detection for Networks , 1999 .
[14] Mouhammd Alkasassbeh,et al. An empirical evaluation for the intrusion detection features based on machine learning and feature selection methods , 2017, ArXiv.
[15] Nor Badrul Anuar,et al. Botnet detection techniques: review, future trends, and issues , 2014, Journal of Zhejiang University SCIENCE C.
[16] K. Rameshkumar,et al. A review on taxonomy of botnet detection , 2014, 2014 International Conference on Advances in Engineering and Technology (ICAET).
[17] Shivangi Garg,et al. Classification Based Network Layer Botnet Detection , 2017 .
[18] C. Ng,et al. Ice cream scoop test: a novel clinical test to diagnose extensor carpi ulnaris instability , 2013, The Journal of hand surgery, European volume.
[19] Chun-Ying Huang,et al. A fuzzy pattern-based filtering algorithm for botnet detection , 2011, Comput. Networks.
[20] Heejo Lee,et al. Identifying botnets by capturing group activities in DNS traffic , 2012, Comput. Networks.
[21] Andrzej Żyluk,et al. Development of carpal tunnel syndrome after repair of the median nerve in the distal forearm , 2018, The Journal of hand surgery, European volume.
[22] Maurizio Mongelli,et al. DNS tunneling detection through statistical fingerprints of protocol messages and machine learning , 2015, Int. J. Commun. Syst..
[23] Jignesh Vania,et al. A Review on Botnet and Detection Technique , 2013 .
[24] Lawrence K. Saul,et al. Beyond blacklists: learning to detect malicious web sites from suspicious URLs , 2009, KDD.
[25] Etienne Stalmans,et al. A framework for DNS based detection and mitigation of malware infections on a network , 2011, 2011 Information Security for South Africa.
[26] Maurizio Mongelli,et al. Supervised Learning Approaches with Majority Voting for DNS Tunneling Detection , 2014, SOCO-CISIS-ICEUTE.
[27] Farid Meziane,et al. Fast flux botnet detection framework using adaptive dynamic evolving spiking neural network algorithm , 2018, 2018 9th International Conference on Information and Communication Systems (ICICS).
[28] Maninder Singh,et al. Detecting bot-infected machines using DNS fingerprinting , 2019, Digit. Investig..
[29] Ali A. Ghorbani,et al. Detecting P2P botnets through network behavior analysis and machine learning , 2011, 2011 Ninth Annual International Conference on Privacy, Security and Trust.
[30] Rajdeep Niyogi,et al. Network forensic frameworks: Survey and research challenges , 2010, Digit. Investig..
[31] T. Marwick,et al. Strain rate evaluation of phasic atrial function in hypertension , 2009, Heart.
[32] Harun Uguz,et al. A hybrid system based on information gain and principal component analysis for the classification of transcranial Doppler signals , 2012, Comput. Methods Programs Biomed..
[33] Nick Feamster,et al. Revealing Botnet Membership Using DNSBL Counter-Intelligence , 2006, SRUTI.
[34] Wenke Lee,et al. Modeling Botnet Propagation Using Time Zones , 2006, NDSS.
[35] Firas AlBalas,et al. An Online Intrusion Detection System to Cloud Computing Based on Neucube Algorithms , 2018, Int. J. Cloud Appl. Comput..
[36] Leyla Bilge,et al. Exposure: A Passive DNS Analysis Service to Detect and Report Malicious Domains , 2014, TSEC.
[37] Jetzabel M. Serna,et al. Benchmarking IP blacklists for financial botnet detection , 2010, 2010 Sixth International Conference on Information Assurance and Security.
[38] Syed Ali Khayam,et al. A Taxonomy of Botnet Behavior, Detection, and Defense , 2014, IEEE Communications Surveys & Tutorials.
[39] Jing Tao,et al. Accurate DNS query characteristics estimation via active probing , 2015, J. Netw. Comput. Appl..
[40] S. R. Selamat,et al. Revealing the Criterion on Botnet Detection Technique , 2013 .
[41] Hossein Rouhani Zeidanloo,et al. A taxonomy of Botnet detection techniques , 2010, 2010 3rd International Conference on Computer Science and Information Technology.
[42] Ammar Almomani,et al. Fast-flux hunter: a system for filtering online fast-flux botnet , 2018, Neural Computing and Applications.
[43] Heejo Lee,et al. BotGAD: detecting botnets by capturing group activities in network traffic , 2009, COMSWARE '09.
[44] Heejo Lee,et al. PsyBoG: A scalable botnet detection method for large-scale DNS traffic , 2016, Comput. Networks.
[45] Leyla Bilge,et al. EXPOSURE: Finding Malicious Domains Using Passive DNS Analysis , 2011, NDSS.
[46] Sureswaran Ramadass,et al. Detecting Botnet Activities Based on Abnormal DNS traffic , 2009, ArXiv.
[47] S. D. Middleton,et al. The epidemiology of fractures of the hand and the influence of social deprivation , 2011, The Journal of hand surgery, European volume.
[48] N. S. Raghava,et al. Classification of Botnet Detection Based on Botnet Architechture , 2012, 2012 International Conference on Communication Systems and Network Technologies.
[49] Andreas Terzis,et al. A multifaceted approach to understanding the botnet phenomenon , 2006, IMC '06.
[50] Ali A. Ghorbani,et al. Clustering botnet communication traffic based on n-gram feature selection , 2011, Comput. Commun..
[51] Ronaldo M. Salles,et al. Botnets: A survey , 2013, Comput. Networks.
[52] R. Villamarin-Salomon,et al. Identifying Botnets Using Anomaly Detection Techniques Applied to DNS Traffic , 2008, 2008 5th IEEE Consumer Communications and Networking Conference.
[53] Vern Paxson,et al. Automating analysis of large-scale botnet probing events , 2009, ASIACCS '09.
[54] Vinod Yegneswaran,et al. BotHunter: Detecting Malware Infection Through IDS-Driven Dialog Correlation , 2007, USENIX Security Symposium.
[55] K. K. e Silva. How industry can help us fight against botnets: notes on regulating private-sector intervention† , 2017 .
[56] Aneel Rahim,et al. Discovering the Botnet Detection Techniques , 2010, FGIT-SecTech/DRBC.
[57] Balachander Krishnamurthy,et al. Characterizing large DNS traces using graphs , 2001, IMW '01.
[58] Zhuoqing Morley Mao,et al. Characterizing Dark DNS Behavior , 2007, DIMVA.
[59] Yang Wang,et al. Visual Detection of Anomalies in DNS Query Log Data , 2014, 2014 IEEE Pacific Visualization Symposium.