List of Articles

• Open Access Article
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  1 - Challenges in Integrity of E-voting Systems: Important Properties, Threats, and Solutions
  Mohsen Borousan Mostafa Kateb
  Today, developed and developing countries are moving more and more towards e-government systems to deliver integrated, fast, and cheaper services to their citizens. Electronic voting is one of the crucial domains in this area, as the results of the elections profoun More

  Today, developed and developing countries are moving more and more towards e-government systems to deliver integrated, fast, and cheaper services to their citizens. Electronic voting is one of the crucial domains in this area, as the results of the elections profoundly affect the future of the nation and even other countries. Confidentiality, integrity, and availability are the three sides of the CIA triangle that are the principal measurements for evaluating the security of the employed e-voting systems. Since system and data integrity are crucial factors for preserving the security of the designed and developed systems, this study explores the properties, threats, solutions, and unresolved challenges in integrity of e-voting systems, to help researchers, designers, and developers evaluate their systems in term of integrity. Manuscript profile
• Open Access Article
  • Abstract Page
  • Full-Text
  
  2 - Constructing New Features for Spam Detection on Twitter
  Arash  Erami Elham  Parvinnia
  Nowadays, by the growth of the internet, social networks are attracting unprecedented attention to themselves. Most people are at least active in one social network. Users in social networks follow their favorite people and topics to discover the latest news about the More

  Nowadays, by the growth of the internet, social networks are attracting unprecedented attention to themselves. Most people are at least active in one social network. Users in social networks follow their favorite people and topics to discover the latest news about them. This rising number of users has made social networks fertile grounds for advertising and finding the bait. Social networks also become celebrities’ popularity criterion. The problem is that some accounts created to spread malicious links, steal user’s information, and display advertising. These accounts are mainly controlled and supervised by an automatic program. Not only the increase in fake accounts has costs for social networks companies, but it also influences network quality. In this paper, we offer some new and low-cost features to distinguish spam accounts on Twitter. This paper offers some low cost and a new feature to distinguish spam accounts of Twitter. We apply machine learning algorithms to predestined datasets, and by looking at the characteristics of the accounts, then we anticipate class of users by the accuracy of 99.18%. Manuscript profile