Publications of the Laboratory for Education and Research in Secure Systems Engineering (LERSSE) 9 records found  Search took 0.00 seconds. 
1.
Thwarting Fake OSN Accounts by Predicting their Victims / Yazan Boshmaf ; Matei Ripeanu ; Konstantin Beznosov [LERSSE-RefConfPaper-2015-005]
Traditional defense mechanisms for fighting against automated fake accounts in online social networks are victim-agnostic. [...]
Published in Yazan Boshmaf, Matei Ripeanu, Konstantin Beznosov. Thwarting Fake OSN Accounts by Predicting their Victims. In Proceedings of the 2015 Workshop on Artificial Intelligent and Security Workshop (AISec'15), Denver, Colorado, USA, Oct, 2015:
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2.
Thwarting fake accounts by predicting their victims / Yazan Boshmaf ; Dionysios Logothetis ; Georgos Siganos ; Matei Ripeanu ; et al [LERSSE-PRESENTATION-2014-001]
Traditional fake account detection systems employed by today's online social networks rely on either features extracted from user activities, or ranks computed from the underlying social graph. [...]
Published in Boshmaf et al. Thwarting fake accounts by predicting their victims. Invited talk at AAAI 2014 Spring Symposia, Social Hacking and Cognitive Security on the Internet and New Media, Stanford, CA, March, 2014.:
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3.
Integro: Leveraging Victim Prediction for Robust Fake Account Detection in OSNs / Yazan Boshmaf ; Dionysios Logothetis ; Georgos Siganos ; Jorge Leria ; et al [LERSSE-PRESENTATION-2015-001]
Detecting fake accounts in online social networks (OSNs) protects OSN operators and their users from various malicious activities. [...]
Published in Boshmaf et al. "Integro: Leveraging Victim Prediction for Robust Fake Account Detection in OSNs" In proceedings the 2015 Network and Distributed System Security Symposium (NDSS'15), San Diego, USA.:
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4.
Integro: Leveraging Victim Prediction for Robust Fake Account Detection in OSNs / Yazan Boshmaf ; Dionysios Logothetis ; Georgos Siganos ; Jorge Leria ; et al [LERSSE-RefConfPaper-2014-004]
Detecting fake accounts in online social networks (OSNs) protects OSN operators and their users from various malicious activities. [...]
Published in Boshmaf et al. "Integro: Leveraging Victim Prediction for Robust Fake Account Detection in OSNs" In proceedings the 2015 Network and Distributed System Security Symposium (NDSS'15), San Diego, USA.:
Fulltext: NDSS_260_Final - Download fulltextPDF Download fulltextPDF (PDFA); boshmaf_ndss_2015 - Download fulltextPDF Download fulltextPDF (PDFA);
5.
Security Analysis of Malicious Socialbots on the Web / Yazan Boshmaf [LERSSE-THESIS-2015-002]
The open nature of the Web, online social networks (OSNs) in particular, makes it possible to design socialbots—automation software that controls fake accounts in a target OSN, and has the ability to perform basic activities similar to those of real users. [...]
Published in Yazan Boshmaf, Security Analysis of Malicious Socialbots on the Web, PhD Dissertation, UBC, 2015:
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6.
Creation and Evaluation of SQL Injection Security Tools / Fabrizio Monticelli [LERSSE-THESIS-2008-005]
This work summarizes our research on the topic of the creation and evaluation of security tools against SQL injection attacks (SQLIAs) [...]
Published in Fabrizio Monticelli, "Creation and Evaluation of SQL Injection Security Tools," Master thesis, Milano (MI), Italia, Department of Computer Engineering, Politecnico di Milano Technical University, Oct, 2008, pp.184. :
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7.
Human, Organizational and Technological Factors of IT Security / Kasia Muldner [LERSSE-PRESENTATION-2008-065]
Given that Information Technology (IT) has become pervasive in today’s organizations, properly securing systems is critical. [...]
Published in Kasia Muldner, " Human, Organizational and Technological Factors of IT Security", Invited Talk at Acadia University, Wofville, N.S., Canada, 25 January, 2007.:
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8.
Harvesting the Low-hanging Fruits: Defending Against Automated Large-Scale Cyber-Intrusions
by Focusing on the Vulnerable Population / Hassan Halawa ; Konstantin Beznosov ; Yazan Boshmaf ; Baris Coskun ; et al [LERSSE-RefConfPaper-2016-003]
The orthodox paradigm to defend against automated social-engineering attacks in large-scale socio-technical systems is reactive and victim-agnostic [...]
Published in In Proceedings of the New Security Paradigms Workshop (NSPW), September 26-29, 2016, Granby, CO, USA.:
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9.
Augur: Aiding Malware Detection Using Large-Scale Machine Learning / Yazan Boshmaf ; Matei Ripeanu ; Konstantin Beznosov ; Kyle Zeeuwen ; et al [LERSSE-POSTER-2012-001]
We present Augur: a large-scale machine learning system that uses malware static and dynamic analyses to predict the maliciousness of new files. [...]
Published in Yazan Boshmaf, Matei Ripeanu, Konstantin Beznosov, Kyle Zeeuwen, David Cornell, Dmitry Samosseiko. Augur: Aiding Malware Detection Using Large-Scale Machine Learning. At the Poster Session of the 21st Usenix Security Symposium, Bellevue, WA, 2012:
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