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» A security framework for personal networks
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CCS
2006
ACM
15 years 10 months ago
Can machine learning be secure?
Machine learning systems offer unparalled flexibility in dealing with evolving input in a variety of applications, such as intrusion detection systems and spam e-mail filtering. H...
Marco Barreno, Blaine Nelson, Russell Sears, Antho...
ECBS
2008
IEEE
113views Hardware» more  ECBS 2008»
15 years 6 months ago
Towards Secure Mobile Payment Based on SIP
Mobile payment has some unique advantages over more traditional payment methods in, for example, TV shopping and mobile multimedia services. Unfortunately, most existing mobile pa...
Ge Zhang, Feng Cheng 0002, Christoph Meinel
SIN
2010
ACM
15 years 4 months ago
Analysis of privacy in online social networks of runet
In recent years, social networking sites (SNSs) gained high popularity among Internet users as they combine the best of both worlds: befriending people outside real life situation...
Slava Kisilevich, Florian Mansmann
SOSP
2003
ACM
16 years 3 months ago
Model-carrying code: a practical approach for safe execution of untrusted applications
This paper presents a new approach called model-carrying code (MCC) for safe execution of untrusted code. At the heart of MCC is the idea that untrusted code comes equipped with a...
R. Sekar, V. N. Venkatakrishnan, Samik Basu, Sande...
SP
2010
IEEE
165views Security Privacy» more  SP 2010»
15 years 10 months ago
A Practical Attack to De-anonymize Social Network Users
—Social networking sites such as Facebook, LinkedIn, and Xing have been reporting exponential growth rates. These sites have millions of registered users, and they are interestin...
Gilbert Wondracek, Thorsten Holz, Engin Kirda, Chr...