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Recently, the threat of Android malware is spreading rapidly, especially those repackaged Android malware. Although understanding Android malware using dynamic analysis can provide a comprehensive view, it is still subjected to high cost in environment deployment and manual efforts in investigation. In this study, we propose a static feature-based mechanism(More)
This paper proposes using the inter-cluster distance between class means in the feature space to help choose parameters for a kernel function when training a support vector machine (SVM). With the proposed method, the square values of the distance between the two class means of the training data in different feature spaces are calculated. These values are(More)
A CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) is a security mechanism that can be used to distinguish between humans and machines. Most existing CAPTCHA systems are vulnerable against a so-called "third party human attack." The third party human attack employs hired human to solve challenges so that the CAPTCHA(More)
In this paper we present a model to predict the stock trend based on a combination of sequential chart pattern, K-means and AprioriAll algorithm. The stock price sequence is truncated to charts by sliding window, then the charts are clustered by K-means algorithm to form chart patterns. Therefore, the chart sequences are converted to chart pattern(More)
The High Energy and Nuclear Physics Data Access Grand Challenge project has developed an optimizing storage access software system that was prototyped at RHIC. It is currently undergoing integration with the STAR experiment in preparation for data taking that starts in mid-2000. The behavior and lessons learned in the RHIC Mock Data Challenge exercises are(More)
The current malicious URLs detecting techniques based on whole URL information are hard to detect the obfuscated malicious URLs. The most precise way to identify a malicious URL is verifying the corresponding web page contents. However, it costs very much in time, traffic and computing resource. Therefore, a filtering process that detecting more suspicious(More)
Fast-flux service networks (FFSNs), broadly used by botnets, are an evasive technique for conducting malicious behavior via rapid activities. FFSN detection easily fails in the case of poor performance and causes a high incidence of false positives due to the similarity of an FFSN to a content distribution network (CDN), a normal behavior for load balance.(More)