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1.
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Forecasting Suspicious Account Activity at Large-Scale Online Service Providers
/ Hassan Halawa ; Konstantin Beznosov ; Baris Coskun ; Meizhu Liu ; et al
[LERSSE-RefConfPaper-2018-003]
In the face of large-scale automated social engineering attacks to large online services, fast detection and remediation of compromised accounts are crucial to limit the spread of the attack and to mitigate the overall damage to users, companies, and the public at large. [...]
Published in In the proceedings of Twenty-Third International Conference on Financial Cryptography and Data Security (FC'19), St. Kitts, 2019:
Fulltext: Final-verson -  PDF; FC19-1-CameraReady-a - PDF PDF (PDFA);
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2.
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Analysis of Data-At-Rest Security In Smartphones
/ Ildar Muslukhov
[LERSSE-THESIS-2018-003]
With almost two billion users worldwide, smartphones are used for almost everything – booking a hotel, ordering a cup of coffee, or paying in a shop. [...]
Published in Ildar Muslukhov, "Analysis of Data-At-Rest Security In Smartphones", PhD Dissertation, Department of Electrical and Computer Engineering, THE UNIVERSITY OF BRITISH COLUMBIA, August, 2018:
Fulltext: PDF PDF (PDFA);
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3.
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Contextual Permission Models for Better Privacy Protection
/ Primal Wijesekera
[LERSSE-THESIS-2018-002]
Despite corporate cyber intrusions attracting all the attention, privacy breaches that we, as ordinary users, should be worried about occur every day without any scrutiny. [...]
Published in Primal Wijesekera, "Contextual Permission Models for Better Privacy Protection", PhD Dissertation, Department of Electrical and Computer Engineering, THE UNIVERSITY OF BRITISH COLUMBIA, June, 2018:
Fulltext: PDF PDF (PDFA);
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4.
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Advancing the Understanding of Android Unlocking and Usage
/ Lina Qiu
[LERSSE-THESIS-2018-001]
Research efforts have been made towards creating mobile authentication systems to better serve users’ concerns regarding usability and security. [...]
Published in Lina Qiu, "Advancing the Understanding of Android Unlocking and Usage", MASc Thesis, Department of Electrical and Computer Engineering, THE UNIVERSITY OF BRITISH COLUMBIA, May, 2018:
Fulltext: PDF PDF (PDFA);
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5.
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Source Attribution of Cryptographic API Misuse in Android Applications
/ Ildar Muslukhov ; Yazan Boshmaf ; Konstantin Beznosov
[LERSSE-RefConfPaper-2018-002]
Recent research suggests that 88% of Android applications that use Java cryptographic APIs make at least one mistake, which results in an insecure implementation. [...]
Published in Ildar Muslukhov, Yazan Boshmaf, Konstantin Beznosov. Source Attribution of Cryptographic API Misuse in Android Applications. Proceedings of the 13th ACM ASIA Conference on Information, Computer and Communications Security (ACM ASIACCS '18), 2018.:
Fulltext: PDF PDF (PDFA);
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6.
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Forecasting Suspicious Account Activity at Large-Scale Online Service Providers
/ Hassan Halawa ; Matei Ripeanu ; Konstantin Beznosov ; Baris Coskun ; et al
[LERSSE-REPORT-2018-001]
In the face of large-scale automated social engineering attacks to large online services, fast detection and remediation of compromised accounts are crucial to limit the spread of new attacks and to mitigate the overall damage to users, companies, and the public at large. [...]
Published in H. Halawa, M. Ripeanu, K. Beznosov, B. Coskun, and M. Liu "Forecasting Suspicious Account Activity at Large-Scale Online Service Providers", published in arXiv https://arxiv.org/abs/1801.08629v1:
Fulltext: PDF PDF (PDFA);
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7.
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Dynamically Regulating Mobile Application Permissions
/ Primal Wijesekera ; Arjun Baokar ; Lynn Tsai ; Joel Reardon ; et al
[LERSSE-etc-2018-001]
Current smartphone operating systems employ permission systems to regulate how apps access sensitive resources. [...]
Published in P. Wijesekera et al., "Dynamically Regulating Mobile Application Permissions," in IEEE Security & Privacy, vol. 16, no. 1, pp. 64-71, January/February 2018. doi: 10.1109/MSP.2018.1331031 keywords: {Computer security;Medical devices;Mobile communication;Privacy;Smart phones;IEEE Symposium on Security and Privacy;machine learning;mobile privacy;permission systems;security}, URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8283440&isnumber=8283426:
Fulltext: PDF PDF (PDFA);
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8.
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Contextualizing Privacy Decisions for Better Prediction (and Protection)
/ Primal Wijesekera ; Joel Reardon ; Irwin Reyes ; Lynn Tsai ; et al
[LERSSE-RefConfPaper-2018-001]
Modern mobile operating systems implement an ask-on-first-use policy to regulate applications’ access to private user data: the user is prompted to allow or deny access to a sensitive resource the first time an app attempts to use it. [...]
Published in Primal Wijesekera, Joel Reardon, Irwin Reyes, Lynn Tsai, Jung-Wei Chen, Nathan Good, David Wagner, Konstantin Beznosov, and Serge Egelman. Contextualizing Privacy Decisions for Better Prediction (and Protection). Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’18), 2018.:
Fulltext: PDF PDF (PDFA);
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