30833858
An Aspect-Oriented Approach to Declarative Access Control for Web Applications
This paper presents an aspect-oriented approach to declarative access control for Web applications that can not only realize fine-grained access control requirements but also accomplish it with very little runtime overhead. We devise a translation scheme that will automatically synthesize the desired aspect modules from access control rules in XML format and properly designed aspect templates. The generated aspect modules will then be compiled and integrated into the underlying application using standard aspect tools. At runtime, these aspect codes will be executed to enforce the required access control without any runtime interpretation overhead. Future changes of access control rules can also be effectively realized through these mechanisms without actual coding.
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.
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.
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.
18568401
Capture inter-speaker information with a neural network for speaker identification
Many speaker identification systems are created by model-based approaches, where a statistical model is used to characterize a speaker's voice and no inter-speaker information is used in parameter estimation. It is well known that inter-speaker information is very helpful in discrimination of different speakers. We propose a method for the use of inter-speaker information to improve performance of a model-based speaker identification system. A neural network is employed to capture inter-speaker information from output space of those statistical models. In order to sufficiently utilize inter-speaker information, a rival penalized encoding rule is proposed to design supervised learning pairs for training the neural network. Comparative results in the KING speech corpus show that our method leads to a considerable improvement for a model-based speaker identification system.
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.
29590146
Multi-proxy Signature and Proxy Multi-signature Schemes from Bilinear Pairings
In electronic world, proxy signature is a solution of delegation of signing capabilities. Proxy signatures can combine other special signatures to obtain some new types of proxy signatures. Due to the various applications of the bilinear pairings in cryptography, many pairing-based signature schemes have been proposed. In this paper, we propose a multi-proxy signature scheme and a proxy multi-signature scheme from bilinear pairings. We also show that both of them satisfy all the security properties required by proxy signatures.
32873189
A Typed Theory for Access Control and Information Flow Control in Mobile Systems
We propose a novel security type system for the π-calculus in which a fine-grained access control mechanism is guaranteed by static type checking and secure information flow can be characterized by a new form of non-interference property based on typed behavioral equivalence. In this paper, we present the syntax, subtyping rules, and typing rules of the type system, and explain how the secure data access can be controlled by typing. And then we elaborate a framework of typed level bisimulation to construct the secure information flow property named as non-interference at level. Moreover, some results are presented to indicate that our theory is an efficient enforceable model to support the specification and analysis of secure mobile systems.
15289343
A connectionist method for pattern classification with diverse features
A novel connectionist method is proposed to simultaneously use diverse features in an optimal way for pattern classification. Unlike methods of combining multiple classifiers, a modular neural network architecture is proposed through use of soft competition among diverse features. Parameter estimation in the proposed architecture is treated as a maximum likelihood problem, and an Expectation-Maximization (EM) learning algorithm is developed for adjusting the parameters of the architecture. Comparative simulation results are presented for the real world problem of speaker identification.