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دسته بندی:
امنیت - Security
سال انتشار:
2017
عنوان انگلیسی مقاله:
The Social Relation Key: A new paradigm for security
ترجمه فارسی عنوان مقاله:
کلید ارتباط اجتماعی: یک نمونه جدید برای امنیت
منبع:
Sciencedirect - Elsevier - Information Systems, 71 (2017) 68-77. doi:10.1016/j.is.2017.07.003
نویسنده:
Sihyun Jeong, Jaehoon Lee, Junhyun Park, Chong-kwon Kim
چکیده انگلیسی:
Article history:Received 23 June 2017Revised 7 July 2017Accepted 7 July 2017Available online 18 July 2017Keywords:Online social network Security keySMSTwitter SpamAuthenticationFor the last decade, online social networking services have consistently shown explosive annual growth, and have become some of the most widely used applications and services. Large amounts of social re- lation information accumulate on these platforms, and advanced services, such as targeted advertising and viral marketing, have been introduced to exploit this social information. Although many prior social relation-based services have been commerce oriented, we propose employing social relations to improve online security. Specifically, we propose that real social networks possess unique characteristics that are difficult to imitate through random or artificial networks. Also, the social relations of each individual are unique, like a fingerprint or an iris. These observations thus lead to the development of the Social Rela- tion Key (SRK) concept. We applied the SRK concept in different use cases in the real world, including in the detection of spam SMSes, and another in pinpointing fraud in Twitter followers. Since spammers multicast the same SMS to multiple, randomly-selected receivers and normal users multicast an SMS to friends or acquaintances who know each other, we devise a detection scheme that makes use of a clustering coefficient. We conducted a large scale experiment using an SMS log obtained from a major cellular network operator in Korea, and observed that the proposed scheme performs significantly better than the conventional content-based Naive Bayesian Filtering (NBF). To detect fraud in Twitter followers, we use different social network signatures, namely isomorphic triadic counts, and the property of social status. The experiment based on a Twitter dataset again confirmed the feasibility of the SRK. Our codes are available on a website1 .© 2017 Published by Elsevier Ltd.
Keywords: Online social network | Security key | SMS | Twitter | Spam | Authentication
قیمت: رایگان
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