Xiaozhen Xue

Learn More
The effectiveness of coverage-based fault localizations in the presence of multiple faults has been a major concern for the software testing research community. A commonly held belief is that the fault localization techniques based on coverage statistics are less effective in the presence of multiple faults and their performance are deteriorated. The fault(More)
Intrusion detection is one of the most essential factors for security infrastructures in network environments, and it is widely used in detecting, identifying and tracking the intruders. To solve the drawback of the SVM algorithm to meet the requirements of the network intrusion detection, we propose network intrusion detection based on improved proximal(More)
—Although empirical studies have demonstrated the usefulness of statistical fault localizations based on code coverage, the effectiveness of these techniques may be degraded due to presence of some undesired circumstances such as the existence of coincidental correctness where one or more passing test cases exercise a faulty statement and thus causing some(More)
Internet traffic classification based on flow statistics using machine learning method has attracted great attention. To solve the drawback of the fuzzy K-Means clustering algorithm to meet the requirements of the Internet network classification, we propose Internet traffic classification based on fuzzy kernel K-Means clustering. This method overcomes the(More)
Accurate network traffic classification plays important roles in many areas such as traffic engineering, QoS and intrusion detection etc. Encrypted Peer-to-Peer (P2P) applications have dramatically grown in popularity over the past few years, and now constitute a significant share of the total traffic in many networks. To solve the drawback of the previous(More)