17604450
A Practical Aspect Framework for Enforcing Fine-Grained Access Control in Web Applications
Access control is a system-wide concern that has both a generic nature and an application dependent characteristic. It is generic as many functions must be protected with restricted access, yet the rule to grant a request is highly dependent on the application state. Hence it is common to see the code for implementing access control scattered over the system and tangled with the functional code, making the system difficult to maintain. This paper addresses this issue for Web applications by presenting a practical access control framework based on aspect-oriented programming (AOP). Our approach accommodates a wide range of access control requirements of different granularity. AOP supports the modular implementation of access control while still enables the code to get a hold of the application state. Moreover, framework technology offers a balanced view between reuse and customization. As a result, our framework is able to enforce fine-grained access control for Web applications in a highly adaptable manner.
13933896
Parametric type classes
We propose a generalization to Haskell's type classes where a class can have type parameters besides the placeholder variable. We show that this generalization is essential to represent container classes with overloaded data constructor and selector operations. We also show that the resulting type system has principal types and present unification and type reconstruction algorithms.
16803440
A Compilation Model for Aspect-Oriented Polymorphically Typed Functional Languages
Introducing aspect orientation to a polymorphically typed functional language strengthens the importance of type-scoped advices; i.e., advices with their effects harnessed by type constraints. As types are typically treated as compile time entities, it is highly desirable to be able to perform static weaving to determine at compile time the chaining of type-scoped advices to their associated join points. In this paper, we describe a compilation model, as well as its implementation, that supports static type inference and static weaving of programs in an aspect-oriented polymorphically typed lazy functional language, AspectFun. We present a type-directed weaving scheme that coherently weaves type-scoped advices into the base program at compile time. We state the correctness of the static weaving with respect to the operational semantics of AspectFun. We also demonstrate how control-flow based pointcuts (such as cflowbelow) are compiled away, and highlight several type-directed optimization strategies that can improve the efficiency of woven code.
10895534
Aspect-Based Instrumentation for Locating Memory Leaks in Java Programs
Despite the built-in garbage collector, Java programs can still suffer the memory leak problem resulted from the unhealthy programming style of retaining unwanted references. This paper presents an aspect-based tool for assisting programmers in locating such references to fix the problem. This tool, FindLeaks, utilizes an aspect to collect memory consumption statistics and object references created during a program's execution and analyzes them for detecting memory leaks. The distinctive feature of FindLeaks is that it reports not only suspected classes of leaking objects but also where in the source the unwanted references were created. Besides, this paper also reports some preliminary experience with FindLeaks.
11647155
Methods of Combining Multiple Classifiers with Different Features and Their Applications to Text-Independent Speaker Identification
In practical applications of pattern recognition, there are often different features extracted from raw data which needs recognizing. Methods of combining multiple classifiers with different features are viewed as a general problem in various application areas of pattern recognition. In this paper, a systematic investigation has been made and possible solutions are classified into three frameworks, i.e. linear opinion pools, winner-take-all and evidential reasoning. For combining multiple classifiers with different features, a novel method is presented in the framework of linear opinion pools and a modified training algorithm for associative switch is also proposed in the framework of winner-take-all. In the framework of evidential reasoning, several typical methods are briefly reviewed for use. All aforementioned methods have already been applied to text-independent speaker identification. The simulations show that results yielded by the methods described in this paper are better than not only the individual classifiers' but also ones obtained by combining multiple classifiers with the same feature. It indicates that the use of combining multiple classifiers with different features is an effective way to attack the problem of text-independent speaker identification.
9353133
Using information scent to model user information needs and actions and the Web
On the Web, users typically forage for information by navigating from page to page along Web links. Their surfing patterns or actions are guided by their information needs. Researchers need tools to explore the complex interactions between user needs, user actions, and the structures and contents of the Web. In this paper, we describe two computational methods for understanding the relationship between user needs and user actions. First, for a particular pattern of surfing, we seek to infer the associated information need. Second, given an information need, and some pages as starting pints, we attempt to predict the expected surfing patterns. The algorithms use a concept called “information scent”, which is the subjective sense of value and cost of accessing a page based on perceptual cues. We present an empirical evaluation of these two algorithms, and show their effectiveness.
7013408
Towards better making a decision in speaker verification
Speaker verification is a process that accepts or rejects the identity claim of a speaker. How to make a decision is a critical problem; a threshold for decision-making critically determines performance of a speaker verification system. Traditional threshold estimation methods take only information conveyed by training data into consideration and, to a great extent, do not relate it to production data. It turns out that a speaker verification system with such threshold estimation suffers from poor performance in reality due to mismatches. In this paper, we propose several methods towards better decision-making in a practical speaker verification system. Our methods include the use of additional reliable statistical information for threshold estimation, elimination of abnormal data for better estimation of underlying statistics, and on-line incremental threshold update. To evaluate the performance of our methods, we have done simulations based on a baseline system, Gaussian Mixture Model, in both text-dependent and text-independent modes. Comparative results show that in contrast to the recent threshold estimation methods our methods yield considerably better performance, especially on miscellaneous mismatch conditions, in terms of generalization. Thus our methods provide a promising way for real speaker verification applications.
1856874
Multiparty authentication services and key agreement protocols with semi-trusted third party
This paper introduces a new family of group key establishment protocols suitable for small or medium-sized groups. Five protocols are presented, using a semi-trusted server, with varying security service. The first one is a non-authenticated key agreement protocol suitable for applications with low security requirements. The second protocol adds an authenticated key agreement to provide collaborative authentication. The third and the fourth protocols provide key establishment with integrity and confirmation services, and the fifth protocol is the member adding protocol. A major advantage of the protocols is that they reduce the numbers of rounds fromn to 5.
204980217
Comments on a theorem on grid access control
We analyze the access control model that was proposed by Xu and Bu. We demonstrate the weaknesses of the model, and show that the model may be vulnerable to information disclosure attacks.