Paper Info
Title
Macroscopic view of malware in home networks
Abstract
Malicious activities on the Web are increasingly threatening users in the Internet. Home networks are one of the prime targets of the attackers to host malware, commonly exploited as a stepping stone to further launch a variety of attacks. Due to diversification, existing security solutions often fail to detect malicious activities that remain hidden and pose threats to users' security and privacy. Characterizing behavioral patterns of known malware can help to improve the classification accuracy of threats. More importantly, as different malware might share commonalities, studying the behavior of known malware could help the detection of previously unknown malicious activities. We pose the research question if it is possible to characterize such behavioral patterns analyzing the traffic from known infected clients. We present our quest to discover such characterizations. Results show that commonalities arise but their identification may require some ingenuity. We also present our discovery of malicious activities that were left undetected by commercial IDS.
Year
DOI
Venue
2015
10.1109/CCNC.2015.7157987
2015 12th Annual IEEE Consumer Communications and Networking Conference (CCNC)
Keywords
Field
DocType
malware,home networks,malicious activity detection,Web,Internet,users security,users privacy,classification accuracy improvement,traffic analysis,behavioral pattern characterization
Behavioral pattern,Cryptovirology,Internet privacy,Research question,Computer science,Computer security,Server,Computer network,Home automation,Ingenuity,Malware,The Internet
Conference
ISSN
Citations 
PageRank 
2331-9852
1
0.35
References 
Authors
10
8
Name
Order
Citations
PageRank
Alessandro Finamore170042.23
Sabyasachi Saha216517.74
Gaspar Modelo-Howard3234.00
Sung-Ju Lee43511278.11
Enrico Bocchi5413.69
Luigi Grimaudo6687.86
Marco Mellia72748204.65
Elena Baralis81319186.33