Access and usage control is a major challenge in information and computer security in a distributed network connected environment. Many models have been proposed such as traditional access control and UCONABC. Though these models have achieved their objectives in some areas, there are some issues both have not dealt with. The issue of what happens to a resource once it has been accessed rightfully. In view of this, this paper comes out with how to control resource usage by a concept known as the package concept. This concept can be implemented both with internet connection and without the internet connection to ensure continual control of resource. It packages the various types of resources with the required policies and obligations that pertain to the use of these different resources. The package concept of ensuring usage control focuses on resource by classifying them into three: Intellectual, sensitive and non-sensitive resources. Also this concept classifies access or right into three as: access to purchase, access to use temporally online and access to modify. The concept also uses biometric mechanism such as fingerprints for authentication to check redistribution of resource and a logic bomb to help ensure the fulfillment of obligations.
Computer and information technology has evaded our every aspect of life. Information technology is seen in all aspect of the individual from banking and investing to shopping and communicating through the use of the internet services such as emails and chat rooms. Organizations and industries also utilize computer and information technology to collect information on individuals leading to the creation of warehouse of databases that enable them to achieve their objectives. In a distributed network environment today, information security is a very important issue in ensuring a safe computing environment.
In order to cope with the problem of spam soaring, a personalized e-mail filtering method based on UCON is proposed. E-mails from different senders were classified as junk e-mail, suspicious e-mail and normal e-mail by trust third-party according to the maintained blacklist and embedded machine learning technology online. Suspicious e-mails will be classified further from users’ point of view manually. Then the incoming e-mails would be sifted and processed differently according to their classification. Experiments results illustrate the method of the paper not only provide a personalization filtering but also more accurate and effective than the popular statistical spam filtering system
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