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As the amount of crimes involving the digital dimension grows, an ever increasing number of digital artifacts collected from a forensic investigation needs plenty of resources to process in a forensically sound manner. Digital forensic triage provides a way to deal with this scalability problem, as it is tailored to maximize the utilization of resources based on a priority system. Unfortunately, the...
With one class outnumbering another, many real classification tasks show imbalanced class distributions, which brings big trouble to standard classification models: they usually intend to recognize a minority instance as a majority one. The data gravitation based classification (DGC) model, a newly developed physical-inspired supervised learning model, has been proven effective for standard supervised...
Traditional machine learning traffic identification techniques usually use the features of a whole Internet flow, which makes such techniques few sense in engineering practices. Therefore, recent years, an increasing number of researchers turn to build effective machine learning models to identify traffics with the few packets at the early stage. In this paper, data gravitation based classification...
Software development methodology is a proposition that is used to structure, plan, and control the process of developing a system. However, traditional methods, such as waterfall-like model, component-based programming, software architecture method and agile method, have encountered more fundamental difficulties in processing complex system development. To address this challenge, we have witnessed...
According to the similarities between biological growth and product architecture evolution, the key procedures of biological growth are introduced into product design. The self-organizing design strategy and its implementation methods are proposed by applying the product genes obtainment technology, amplification technology and translation technology into product growth design. Complexity strategy...
Traditional traffic classification techniques like port-based and payload-based techniques are becoming ineffective owning to more and more Internet applications using dynamic port number and encryption techniques. Therefore, in the past few years, many researches have addressed machine learning-based techniques. Most researches of machine learning-based traffic identification use traffic samples...
Web Services (WS) is a popular way of implementing SOA-based software, which gained rapid progress. Several Web Services are usually combined to create new services by a mechanism named Composite Web Service. Composite Web Service is one of the most important components to WS.Composite Web Services testing is a difficult topic in WS testing. In this paper, we present a regression testing method for...
Classification of network traffic is basic and essential for many network researches and managements. However, classification of network traffic using port-based and simple payload-based methods is diminished with the rapid development of peer-to-peer (P2P) application using dynamic port, disguising techniques and encryption to avoid detection. An alternative method based on statistics and machine...
Phasor measurement has previously been used for sub-system model validation, which enables rigorous comparison of model simulation and recorded dynamics and facilitates identification of problematic model components. Recent work extends the sub-system model validation approach with a focus on how model parameters may be calibrated to match recorded dynamics. In this paper, a calibration method using...
The FDD (fault detection and diagnosis)expert system of rockets must diagnose quickly with pre-launch testing data. Therefore, it needs a fast inference algorithm that is capable of dealing with mass data. Algorithm Rete, when facing mass data and rules to be tested, has the disadvantages, such as the great consumption of system resource, and deteriorates its inference efficiency. Using bit vectors...
For a software development project, when to stop testing the software and release it for operation is of great importance as it impacts both the software reliability and the total cost of the project. Software release time determination, therefore, has attracted a lot of research in the past two decades and several new cost models have been developed in the literature recently. In most research on...
Many existing software reliability models are based on the assumption of statistical independence among successive software failures. In reality, this assumption could be easily violated. In recent years, efforts have been made to relax this unrealistic assumption and a software reliability modeling framework considering failure correlation was developed by Goseva-Popstojanova and Trivedi. However,...
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