Towards Measuring and Mitigating Social Engineering Software Download Attacks

Presented on September 2, 2016 at 12:00 p.m. in the Klaus Advanced Computing Building, Room 1116W.

[1]  Stefan Savage,et al.  Manufacturing compromise: the emergence of exploit-as-a-service , 2012, CCS.

[2]  Niels Provos,et al.  CAMP: Content-Agnostic Malware Protection , 2013, NDSS.

[3]  William L. Simon,et al.  The Art of Deception: Controlling the Human Element of Security , 2001 .

[4]  Guofei Gu,et al.  WebPatrol: automated collection and replay of web-based malware scenarios , 2011, ASIACCS '11.

[5]  Christopher Krügel,et al.  The Underground Economy of Fake Antivirus Software , 2011, WEIS.

[6]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[7]  Richard Power,et al.  Social engineering: attacks have evolved, but countermeasures have not , 2006 .

[8]  Vinod Yegneswaran,et al.  BLADE: an attack-agnostic approach for preventing drive-by malware infections , 2010, CCS '10.

[9]  Roberto Perdisci,et al.  WebWitness: Investigating, Categorizing, and Mitigating Malware Download Paths , 2015, USENIX Security Symposium.

[10]  Juan Caballero,et al.  Driving in the Cloud: An Analysis of Drive-by Download Operations and Abuse Reporting , 2013, DIMVA.

[11]  Junjie Zhang,et al.  Detecting fake anti-virus software distribution webpages , 2015, Comput. Secur..

[12]  Niels Provos,et al.  The Ghost in the Browser: Analysis of Web-based Malware , 2007, HotBots.

[13]  Kang Li,et al.  Measuring and Detecting Malware Downloads in Live Network Traffic , 2013, ESORICS.

[14]  InduShobha N. Chengalur-Smith,et al.  An overview of social engineering malware: Trends, tactics, and implications , 2010 .

[15]  Charles Reis,et al.  Isolating web programs in modern browser architectures , 2009, EuroSys '09.

[16]  Leyla Bilge,et al.  The Dropper Effect: Insights into Malware Distribution with Downloader Graph Analytics , 2015, CCS.

[17]  Ron Kohavi,et al.  Wrappers for Feature Subset Selection , 1997, Artif. Intell..

[18]  Gianluca Stringhini,et al.  Shady paths: leveraging surfing crowds to detect malicious web pages , 2013, CCS.

[19]  Antonio Nucci,et al.  Detecting malicious HTTP redirections using trees of user browsing activity , 2014, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.

[20]  Helen J. Wang,et al.  The Multi-Principal OS Construction of the Gazelle Web Browser , 2009, USENIX Security Symposium.

[21]  Kang Li,et al.  ClickMiner: Towards Forensic Reconstruction of User-Browser Interactions from Network Traces , 2014, CCS.

[22]  Wei Meng,et al.  Understanding Malvertising Through Ad-Injecting Browser Extensions , 2015, WWW.

[23]  Samuel T. King,et al.  Secure Web Browsing with the OP Web Browser , 2008, 2008 IEEE Symposium on Security and Privacy (sp 2008).

[24]  Barton Whaley Toward a general theory of deception , 1982 .

[25]  Xin Zhao,et al.  The Nocebo Effect on the Web: An Analysis of Fake Anti-Virus Distribution , 2010, LEET.

[26]  William K. Robertson,et al.  TrueClick: automatically distinguishing trick banners from genuine download links , 2014, ACSAC '14.

[27]  Michalis Faloutsos,et al.  ReSurf: Reconstructing web-surfing activity from network traffic , 2013, 2013 IFIP Networking Conference.

[28]  Vern Paxson,et al.  Measuring Pay-per-Install: The Commoditization of Malware Distribution , 2011, USENIX Security Symposium.

[29]  R. Cialdini Influence: Science and Practice , 1984 .

[30]  Christopher Krügel,et al.  Detection and analysis of drive-by-download attacks and malicious JavaScript code , 2010, WWW '10.

[31]  Fang Yu,et al.  Knowing your enemy: understanding and detecting malicious web advertising , 2012, CCS '12.

[32]  Norbert Pohlmann,et al.  Exploiting visual appearance to cluster and detect rogue software , 2013, SAC '13.

[33]  Edgar R. Weippl,et al.  Advanced social engineering attacks , 2015, J. Inf. Secur. Appl..