@TechReport{Qadeer16a,
	author = 	"Abdul Qadeer and John Heidemann and Kensuke Fukuda",
	title = 	"Improving Long-term Accuracy of DNS
                  Backscatter for Monitoring of Internet-Wide Malicious Activity (poster)",
	institution = 	"USC/Information Sciences Institute",
	year = 		2016,
	sortdate = 		"2016-04-29", 
	project = "ant, lacrend, retrofuture",
	jsubject = "dns",
	number =	"ISI-TR-2016-707",
	month =		apr,
	jlocation =	"johnh: pafile",
	keywords =	"network outage detection, hurricane sandy",
	url =		"https://ant.isi.edu/%7ejohnh/PAPERS/Qadeer16a.html",
	pdfurl =	"https://ant.isi.edu/%7ejohnh/PAPERS/Qadeer16a.pdf",
	dataseturl = "https://ant.isi.edu/datasets/dns_backscatter/index.html",
	myorganization =	"USC/Information Sciences Institute",
	copyrightholder = "authors",
	abstract = "
Internet-wide malicious activities are prevalent on the Internet.  Such activities 
include the malicious, like spamming and scanning,
and the 
benign, like large e-mailing lists and content delivery networks.
We've previously shown that they can be detected centrally with 
DNS backscatter, and developed a classifier using supervised learning.
However, long-term detection is difficult because activities rapidly 
change with time to evade detection or as they naturally evolve, and 
manual training is expensive. 
Our solution: we extend backscatter-based detection by identifying: 
how behavior evolves, 
how often we need to retrain, 
and how to retrain without human supervision. 
Details are in the attached poster.
",
}

{"_id":"kBCiSyWxSu2ZuhMR2","bibbaseid":"qadeer-heidemann-fukuda-improvinglongtermaccuracyofdnsbackscatterformonitoringofinternetwidemaliciousactivityposter-2016","author_short":["Qadeer, A.","Heidemann, J.","Fukuda, K."],"bibdata":{"bibtype":"techreport","type":"techreport","author":[{"firstnames":["Abdul"],"propositions":[],"lastnames":["Qadeer"],"suffixes":[]},{"firstnames":["John"],"propositions":[],"lastnames":["Heidemann"],"suffixes":[]},{"firstnames":["Kensuke"],"propositions":[],"lastnames":["Fukuda"],"suffixes":[]}],"title":"Improving Long-term Accuracy of DNS Backscatter for Monitoring of Internet-Wide Malicious Activity (poster)","institution":"USC/Information Sciences Institute","year":"2016","sortdate":"2016-04-29","project":"ant, lacrend, retrofuture","jsubject":"dns","number":"ISI-TR-2016-707","month":"April","jlocation":"johnh: pafile","keywords":"network outage detection, hurricane sandy","url":"https://ant.isi.edu/%7ejohnh/PAPERS/Qadeer16a.html","pdfurl":"https://ant.isi.edu/%7ejohnh/PAPERS/Qadeer16a.pdf","dataseturl":"https://ant.isi.edu/datasets/dns_backscatter/index.html","myorganization":"USC/Information Sciences Institute","copyrightholder":"authors","abstract":"Internet-wide malicious activities are prevalent on the Internet. Such activities include the malicious, like spamming and scanning, and the benign, like large e-mailing lists and content delivery networks. We've previously shown that they can be detected centrally with DNS backscatter, and developed a classifier using supervised learning. However, long-term detection is difficult because activities rapidly change with time to evade detection or as they naturally evolve, and manual training is expensive. Our solution: we extend backscatter-based detection by identifying: how behavior evolves, how often we need to retrain, and how to retrain without human supervision. Details are in the attached poster. ","bibtex":"@TechReport{Qadeer16a,\n\tauthor = \t\"Abdul Qadeer and John Heidemann and Kensuke Fukuda\",\n\ttitle = \t\"Improving Long-term Accuracy of DNS\n Backscatter for Monitoring of Internet-Wide Malicious Activity (poster)\",\n\tinstitution = \t\"USC/Information Sciences Institute\",\n\tyear = \t\t2016,\n\tsortdate = \t\t\"2016-04-29\", \n\tproject = \"ant, lacrend, retrofuture\",\n\tjsubject = \"dns\",\n\tnumber =\t\"ISI-TR-2016-707\",\n\tmonth =\t\tapr,\n\tjlocation =\t\"johnh: pafile\",\n\tkeywords =\t\"network outage detection, hurricane sandy\",\n\turl =\t\t\"https://ant.isi.edu/%7ejohnh/PAPERS/Qadeer16a.html\",\n\tpdfurl =\t\"https://ant.isi.edu/%7ejohnh/PAPERS/Qadeer16a.pdf\",\n\tdataseturl = \"https://ant.isi.edu/datasets/dns_backscatter/index.html\",\n\tmyorganization =\t\"USC/Information Sciences Institute\",\n\tcopyrightholder = \"authors\",\n\tabstract = \"\nInternet-wide malicious activities are prevalent on the Internet. Such activities \ninclude the malicious, like spamming and scanning,\nand the \nbenign, like large e-mailing lists and content delivery networks.\nWe've previously shown that they can be detected centrally with \nDNS backscatter, and developed a classifier using supervised learning.\nHowever, long-term detection is difficult because activities rapidly \nchange with time to evade detection or as they naturally evolve, and \nmanual training is expensive. \nOur solution: we extend backscatter-based detection by identifying: \nhow behavior evolves, \nhow often we need to retrain, \nand how to retrain without human supervision. \nDetails are in the attached poster.\n\",\n}\n\n","author_short":["Qadeer, A.","Heidemann, J.","Fukuda, K."],"bibbaseid":"qadeer-heidemann-fukuda-improvinglongtermaccuracyofdnsbackscatterformonitoringofinternetwidemaliciousactivityposter-2016","role":"author","urls":{"Paper":"https://ant.isi.edu/%7ejohnh/PAPERS/Qadeer16a.html"},"keyword":["network outage detection","hurricane sandy"],"metadata":{"authorlinks":{}}},"bibtype":"techreport","biburl":"https://bibbase.org/f/dHevizJoWEhWowz8q/johnh-2023-2.bib","dataSources":["YLyu3mj3xsBeoqiHK","fLZcDgNSoSuatv6aX","fxEParwu2ZfurScPY","7nuQvtHTqKrLmgu99"],"keywords":["network outage detection","hurricane sandy"],"search_terms":["improving","long","term","accuracy","dns","backscatter","monitoring","internet","wide","malicious","activity","poster","qadeer","heidemann","fukuda"],"title":"Improving Long-term Accuracy of DNS Backscatter for Monitoring of Internet-Wide Malicious Activity (poster)","year":2016}