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The number of phishing attacks against web serviceshas seen a steady increase causing, for example, a negative effecton the ability of banking and financial institutions to deliverreliable services on the Internet. This paper presents an automaticapproach detecting phishing attacks. Our approach combinesa personalized whitelisting approach with machine learningtechniques. The whitelist is used as...
Social Networking Sites (SNS), such as Facebook and LinkedIn, have become the established place for keeping contact with old friends and meeting new acquaintances. As a result, a user leaves a big trail of personal information about him and his friends on the SNS, sometimes even without being aware of it. This information can lead to privacy drifts such as damaging his reputation and credibility,...
Since their introduction, SNS (Social Networking Sites) such as MySpace, Facebook and LinkedIn have attracted millions of users and have become established places for keeping contact with old acquaintances and meeting new ones. Nonetheless, due to lack of user awareness and proper privacy protection tools, huge quantities of user data, including personal information, pictures and videos are quickly...
Social networking sites (SNS) have become very popular during the past few years, as they allow users to both express their individuality and meet people with similar interests. Nonetheless, there are also many potential threats to privacy associated with these SNS such as identity theft and disclosure of sensitive information. However, many users still are not aware of these threats and the privacy...
In the context of a research and development department of an enterprise, researchers regularly access, review, and use large amounts of literature, yet none of the exiting tools and solutions provide the wide range of functionalities required to properly manage these resources. Indeed, bibliography management systems manage the references and citations but fail to help researchers handle and locate...
Recommender systems enable merchants to assist customers in finding products that best satisfy their needs. Unfortunately, current recommender systems suffer from various privacy-protection vulnerabilities. We report on the first experimental realization of a theoretical framework called ALAMBIC, which we had previously put forth to protect the privacy of customers and the commercial interests of...
E-learning systems have made considerable progress within the last few years. Nonetheless, the issue of learner privacy has been practically ignored. Existing E-learning standards offer some provisions for privacy and the security of E-learning systems offers some privacy protection, but remains unsatisfactory on several levels. On the other hand, privacy preserving solutions that are appropriate...
The rapid evolution of our world means that learning and knowledge sharing are fast becoming a key challenge for individuals and organizations. In this paper, we present a system called HELP, whose aim is to locate information and recommend experts in organizations. Each user is being viewed simultaneously as an expert and a learner. We use two approaches: The first one consists of making the system...
In the context of electronic commerce, recommender systems enable merchants to assist customers in finding available products that will best satisfy their need. However, a recommender system usually operates as a kind of black box from which customers receive recommendations for products. Of particular interest are recommender systems based on collaborative filtering, in which customers provide the...
Recommender systems have been widely used in commercial and research oriented systems. In this paper, we propose to develop an intelligent, Internet-based movie recommender system, to help moviegoers choose movies. Our system, COOP-R uses a hybrid recommendation technique based on collaborative and content based filtering. As opposed to previous work using the neighbourhood paradigm, our collaborative...
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