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Data fragment classification is an important problem in many fields, such as intrusion detection, reverse engineering, data recovery, digital forensics and so on. Most of the existing methods try to classify the fragment depending on file type. But the results are poor, because compound file types can contain many other file types, and some file types use the similar data encoding scheme. In this...
We propose three regularization techniques to overcome drawbacks of local winner-take-all methods used in deep convolutional networks. Channel-Max inherits the max activation unit from Maxout networks, but otherwise adopts complementary subsets of input and filters with different kernel sizes as better companions to the max function. To balance the training on different pathways, Channel-Drop is employed...
Online hot topic detection is a significant research field in web data mining, which can help people make policy decision or benefit to people's daily life. Actually, in recent years more and more hot topics are arising from BBS, often referred as online forum. BBS provide a communication platform for people to discuss and express their views. It's obvious that forecasting the hotness topics on BBS...
This paper introduces an integrated maintenance solution called Integrated Equipment Reliability Programme, which is developed by Asset Management Services of SKF* Reliability Systems. The programme is a proactive maintenance programme - customized for combined cycle power plants. The paper also shows successful cases that SKF uses the programme globally to help clients to increase machine reliability...
Malware is an increasingly important problem that threatens the security of computer systems. The new concept of cloud security require rapid and automated detection and classification of malicious software. In this paper,we propose a behavior-based automated classification method. Depends on behavioral analysis we characterize malware behavioral profile in a trace report. This report contains the...
Malware obfuscation is defined as a program transformation. It is always used in malware to evade detection from anti-malware software. In this paper, we propose a method to detect malware obfuscation using maximal patterns. Maximal pattern is a subsequence in malware's runtime system call sequence, which frequently appears in program execution, and can be used to describe the program specific behavior...
In this paper a novel text classification method based on biomimetic pattern recognition (BPR) is proposed. And we implement a BPR text classifier with multi-weight neural network; the model of three-weight neural network and its construction method are described in detail. Some text classification experiments have been done to test the performance of our BPR text classifier; experimental results...
Traditional anti-virus scanner employs static features to detect malicious executables. Unfortunately, this content-based approach can be obfuscated by techniques such as polymorphism and metamorphism. In this paper, we propose a malicious executable detecting method using 35-dimension feature vector. Each dimension stands for a malicious run-time behavior feature represented by corresponding Win32...
The most common task for a forensic investigator is to search a hard disk to find interesting evidences. While, the most search tools in digital forensic field fundamentally utilize text string match and index technology, which produce high recall (100%) and low precision. Investigators frequently waste vast time on huge irrelevant search hits. In this paper, we propose an improved method for ranking...
Facial attribute-specific subspace-based PCA (FASS-based PCA) considers the information of class labels, and the discriminant power can be improved. However, it doesn't consider the outliers which are .common in realistic training sets. To address this problem, we propose robust facial attribute-specific subspace-based PCA (robust FASS-based PCA) algorithm in this paper, which gives a new weighted...
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