635214
Security Properties of Software Components
This paper classifies security properties of software components into two broad categories: (1) non-functional security (NFS) properties, and (2) properties as security function (SF). Non-functional security properties are codified and embedded with the component functionality, whereas, properties as security functions are employed as external protection to the component. In most cases, users may add additional external protection to the binary form of the component. This classification could be used to determine how much the overall security of the component is dependent on the non-functional security properties of the component and to what extent the additional external protections are required in order to use the component in their specific application environment.
1659291
A Software Engineering Perspective for Services Security
Services are usually developed and deployed independently; and systems can be formed by composing relevant services to achieve set goals. In such an open and dynamic environment, security is of paramount importance. We have seen much work in the traditional area of information and network security, focusing on developing various security techniques. More recently, there have been efforts in integrating the security techniques into languages and infrastructural support that are used for developing services and systems. In fact, the development of services and the composition of service-based systems are software engineering activities. As such, they need to be viewed from a software engineering perspective. In this paper, we introduce an approach to services security engineering, to answer the questions like what the security properties of services and service-based systems are and how they meet the user’s security requirements. It deals with the issues of (1) security property characterisation for services, (2) compositional security analysis for service-based systems, and (3) certification of services.
10149363
A comparative analysis of architecture frameworks
Architecture frameworks are methods used in architecture modeling. They provide a structured and systematic approach to designing systems. To date there has been little analysis on their roles in system and software engineering and if they are satisfactory. This study provides a model of understanding through analyzing the goals, inputs and outcomes of six architecture frameworks. It characterizes two classes of architecture frameworks and identifies some of their deficiencies. To overcome these deficiencies, we propose to use costs, benefits and risks for architecture analysis. We also propose a method to delineate architecture activities from detailed design activities.
629310
Semantic and Usage Packaging for Software Components
Current models for software components have made component-based software engineering practical. However, these models are limited in the sense that their support for the specification of software components primarily deals with syntactic issues. To facilitate interoperability and proper use of software components, more comprehensive specification of these components is required. In this paper, we present an approach to software component packaging aimed at comprehensive component specification, especially its support for semantic and usage specification.
52184467
International workshop on service oriented software engineering (IW-SOSE'06)
International workshop on service oriented software engineering (IW-SOSE'06) : In Proceeding of the 28th international Conference on Software Engineering (Shanghai, China, May 20 - 28, 2006). ICSE '06.
3251598
TRAM: a tool for requirements and architecture management
Management of system requirements and system architectures is part of any software engineering project. But it is usually very tedious and error prone. In particular, managing the traceability between system requirements and system architectures is critical but difficult. The article introduces a tool, TRAM, for managing system requirements, system architectures and more importantly the traceability between them. Its primary design objective is "being practical" and ready for practitioners to use without much overhead. The issues discussed in the paper include an information model that underlies the capture of requirements, architectures and their traceability, a set of document templates implementing the information model, and the support tool.
1695422
New Public-Key Cryptosystem Using Braid Groups
The braid groups are infinite non-commutative groups naturally arising from geometric braids. The aim of this article is twofold. One is to show that the braid groups can serve as a good source to enrich cryptography. The feature that makes the braid groups useful to cryptography includes the followings: (i) The word problem is solved via a fast algorithm which computes the canonical form which can be efficiently manipulated by computers. (ii) The group operations can be performed efficiently. (iii) The braid groups have many mathematically hard problems that can be utilized to design cryptographic primitives. The other is to propose and implement a new key agreement scheme and public key cryptosystem based on these primitives in the braid groups. The efficiency of our systems is demonstrated by their speed and information rate. The security of our systems is based on topological, combinatorial and group-theoretical problems that are intractible according to our current mathematical knowledge. The foundation of our systems is quite different from widely used cryptosystems based on number theory, but there are some similarities in design.
43532686
AIM: Approximate Intelligent Matching for Time Series Data
Time-series data mining presents many challenges due to the intrinsic large scale and high dimensionality of the data sets. Subsequence similarity matching has been an active research area driven by the need to analyse large data sets in the financial, biomedical and scientific databases. In this paper, we investigate an intelligent subsequence similarity matching of time series queries based on efficient graph traversal. We introduce a new problem, the approximate partial matching of a query sequence in a time series database. Our system can address such queries with high specificity and minimal time and space overhead. The performance bottleneck of the current methods were analysed and we show our method can improve the performance of the time series queries significantly. It is general and flexible enough to find the best approximate match query without specifying a tolerance Ɛ parameter.
6059661
Mining frequent patterns without candidate generation
Mining frequent patterns in transaction databases, time-series databases, and many other kinds of databases has been studied popularly in data mining research. Most of the previous studies adopt an Apriori-like candidate set generation-and-test approach. However, candidate set generation is still costly, especially when there exist prolific patterns and/or long patterns.
In this study, we propose a novel frequent pattern tree (FP-tree) structure, which is an extended prefix-tree structure for storing compressed, crucial information about frequent patterns, and develop an efficient FP-tree-based mining method, FP-growth, for mining the complete set of frequent patterns by pattern fragment growth. Efficiency of mining is achieved with three techniques: (1) a large database is compressed into a highly condensed, much smaller data structure, which avoids costly, repeated database scans, (2) our FP-tree-based mining adopts a pattern fragment growth method to avoid the costly generation of a large number of candidate sets, and (3) a partitioning-based, divide-and-conquer method is used to decompose the mining task into a set of smaller tasks for mining confined patterns in conditional databases, which dramatically reduces the search space. Our performance study shows that the FP-growth method is efficient and scalable for mining both long and short frequent patterns, and is about an order of magnitude faster than the Apriori algorithm and also faster than some recently reported new frequent pattern mining methods.
17887061
Popularity Biased Hybrid Search in P2P Systems
Hybrid search, which combines the flooding and DHT techniques, has been employed for efficient content-locating in peer-to-peer (P2P) systems. Choosing a flooding or a DHT subjects to the population of desired data. However, existing studies summarizes the popularity only based on local information, or does not take into account the dynamic factor of P2P systems. Thus, the users suffer from long search latency when performing hybrid search due to inaccurate estimations of the resource popularity. In this paper, we propose a popularity biased hybrid search method in systems. Our model allows the P2P systems dynamically detect the content popularity, and accurately make a decision of search methods. In this way, our work effectively reduces the query traffic cost and response time. The result our trace-driven simulations report shows that our model outperforms existing approaches in search efficiency
29673478
Exploring the Power of Links in Data Mining
Algorithms like PageRank and HITS have been developed in late 1990s to explore links among Web pages to discover authoritative pages and hubs. Links have also been popularly used in citation analysis and social network analysis. We show that the power of links can be explored thoroughly in data mining, such as classification, clustering, information integration, and object distinction. Some recent results of our research that explore the crucial information hidden inside links will be introduced, including (1) multi-relational classification, (2) user-guided clustering, (3) link-based clustering, and (4) object distinction analysis. The power of links in other analysis tasks will also be discussed in the talk.