An Access Control System with Time-Constraint Using Neural Networks

分散式系統的一個重要的好處是提供資源的分享，然而若此系統沒有任何的保護措施，資源分享反而有可能會引發嚴重的安全問題。例如，系統中所儲存的商業機密或軍事地圖等機密檔案，一旦被未經授權的人所存取，則後果將不堪設想。存取控制機制便是電腦系統中用來定義哪些使用者可以使用哪些資源，用以判斷使用者是否有權力來存取系統中的資源。因此當一使用者用存取某一檔案，他必須要有能力向系統證明他是一個經授權的使用者。然而，在實際的狀況中的存取策略卻複雜的多，使用者的存取權限可能會依時間而有所異動。例如一個檔案在每天的一固定時段會被更新，此時系統管理者便不希望這個檔案被存取以確保資料的一致性。這種存取權限隨著時間區段而改變的特性將更符合現代電腦系統的需求。本計畫擬採用類神經網路來建置此一具有時間限制的存取控制系統。利用類神經網路良好的分群能力，本系統可以快速的判斷某一個使用者在某一時間區塊內是否具有某一資源的存取權限。本計畫所發展的具時間限制之存取控制機制將較傳統的存取控制機制更實用也更適合用於存取控制策略較複雜的電腦系統中

A New Key Assignment Scheme for Enforcing Complicated Access Control Policies in Hierarchy

[[abstract]]In a traditional key assignment scheme, an access control policy is used to solve the access control problem in a hierarchy. A higher security class can access lower security classes, but the opposite is not allowed. However, in some cases, this can be troublesome because of the lack of flexibility. In this paper, we shall propose a secure key assignment scheme which can be performed not only in a hierarchy but also in more complicated policies with anti-symmetrical and transitive exceptions

Efficient Access Control and Key Management Schemes for Mobile Agents

[[abstract]]The mobile agent is a promising trend of technology. It is designed for roaming around the Internet and to achieve the goal of autonomy. However, the Internet is an open and, in many cases, a hostile environment. Thus, how to enable the mobile agent to travel through the Internet in safety is an important issue. Recently, Volker and Mehrdad have proposed a structure that supports key management and access control for mobile agent. However, a large amount of storage for storing the secret keys is required in their scheme. In this paper, we will improve their structure and present two novel methods for key management and access control in a hierarchy. According to our security and performance analysis, our proposed scheme is more suitable for mobile agent environments

A User Authentication System Using Back-Propagation Network

[[abstract]]Information security has been a critical issue in the field of information systems. One of the key factors in the security of a computer system is how to identify the authorization of users. Password-based user authentication is widely used to authenticate a legitimate user in the current system. In conventional password-based user authentication schemes, a system has to maintain a password table or verification table which stores the information of users’ IDs and passwords. Although the one-way hash functions and encryption algorithms are applied to prevent the passwords from being disclosed, the password table or verification table is still vulnerable. In order to solve this problem, in this paper, we apply the technique of back-propagation network instead of the functions of the password table and verification table. Our proposed scheme is useful in solving the security problems that occurred in systems using the password table and verification table. Furthermore, our scheme also allows each user to select a username and password of his/her choice

The Novel Features for Phishing Based on User Device Detection

[[abstract]]Recent years the rapid developments of technology, Internet services are gradually depending on the environment to be able to provide different services. Due to the rise of mobile devices, in order to provide the most appropriate service to the users, in addition to desktop websites, the most popular sites are beginning to build a websites for mobile devices exclusive service users at the same time. However, phishing website, the phishers will not necessarily build two kinds of websites at the same time. In this paper, we propose the new phishing features through detect device according the situation. In the experiment, we through the transfer user agent of desktop and mobile to connect, and use SVM to classify, from the result, we find there are the mechanisms in most popular websites, but in phishing websites, the number of this mechanism is rarely

A Study on Halftoning and Inverse Halftoning Schemes Using Neural Networks

數位半色調影像處理方法是將高色階影像轉換為低色階影像，目標為保持低色階影像在人類視覺下能儘可能有類似高色階的影像品質，最初此技術是應用於印刷業。隨著半色調影像技術的發展，反半色調影像處理技術也開始被廣泛地討論，反半色調影像處理技術的目的是將半色調影像再回復成灰階影像，常被用於掃瞄或感應影像的強化等應用上。本計畫擬提出一系列有關半色調\反半色調的影像處理技術。首先開發一個具強化邊界能力的半色調影像處理技術，此技術可以加強由灰階轉換成半色調的影像品質。在反半色調技術方面，期望藉由類神經網路良好的分群、預測能力，來開發一個反半色調影像處理技術。我們將利用前一技術所得到的結果來訓練一類神經網路，再利用此訓練過的類神經網路來預測經反半色調轉換後的灰階像素值。本計畫將分析所提方法的特性，找出適用的類神經網路架構，並期望利用類神經網路來得到較高效率及較佳的轉換效果。本計畫期望能在半色調與反半色調影像技術及類神經網路應用等領域內，提出新的技術與貢獻