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Showing 3 results for Hb
Doctor Nasoor Bagheri, Mr Reza Aghamohammadi,
Volume 3, Issue 2 (3-2015)
Abstract
Shadi Azizi, Maede Ashouri-Talouki, Hamid Mala,
Volume 5, Issue 2 (3-2017)
Abstract
Location-based services (LBSs) provide appropriate information based on users’ locations. These services can be invoked by an individual user or a group of users. Using these services requires users to reveal their locations; thus, providing uses’ location privacy during the use of these services is an important issue. There are many works to protect users’ location privacy. In this paper, we have reviewed the related works to provide the location privacy for a group of users during the use of LBSs. We have classified them into two categories: the first category consists of the solutions that protect an individual user location privacy through group formation, while the second category contains the specific solutions to provide group location privacy. We have then analyzed and compared the performance and security properties of the related works, and have identified the open issues and future works in this field.
Atefeh Mortazavi, Dr Farhad Soleimanian Gharehchopogh,
Volume 8, Issue 1 (9-2019)
Abstract
Emails are one of the fastest economic communications. Increasing email users has caused the increase of spam in recent years. As we know, spam not only damages user’s profits, time-consuming and bandwidth, but also has become as a risk to efficiency, reliability, and security of a network. Spam developers are always trying to find ways to escape the existing filters, therefore new filters to detect spams need to be developed. Most of these filters take advantage of a combination of several methods, such as black or white lists, using keywords, rule-based filters, machine learning methods and so on, to identify spams more accurately. many approaches about email spam detection exhausted up to now. In this paper, we propose a new approach for spam detection based on Particle Swarm Optimization Algorithm and K-Nearest Neighbor optimization, and we measure performance based on Accuracy, Precision, Recall, And f-measure. The results show that the proposed approach has a better performance than other models and the basic algorithms.
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