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In order to solve the problem of the lack of prior knowledge in intrusion detection, as an unsupervised learning algorithm, the clustering algorithm is applied to intrusion detection. Aiming at the shortcomings of intrusion detection algorithm based on traditional hierarchical clustering, such as high time complexity and high false positive rate, a new clustering algorithm for intrusion detection...
This paper addresses the problem of transferring CNNs pre-trained for face recognition to a face attribute prediction task. To transfer an off-the-shelf CNN to a novel task, a typical solution is to fine-tune the network towards the novel task. As demonstrated in the state-of-the-art face attribute prediction approach, fine-tuning the high-level CNN hidden layer by using labeled attribute data leads...
Predicting facial attributes from faces in the wild is very challenging due to pose and lighting variations in the real world. The key to this problem is to build proper feature representations to cope with these unfavourable conditions. Given the success of Convolutional Neural Network (CNN) in image classification, the high-level CNN feature, as an intuitive and reasonable choice, has been widely...
Predicting attributes from face images in the wild is a challenging computer vision problem. To automatically describe face attributes from face containing images, traditionally one needs to cascade three technical blocks — face localization, facial descriptor construction, and attribute classification — in a pipeline. As a typical classification problem, face attribute prediction has been addressed...
Web attacks that exploit vulnerabilities of web applications are still major problems. The number of attacks that maliciously manipulate parameters of web applications such as SQL injections and command injections is increasing nowadays. Anomaly detection is effective for detecting these attacks, particularly in the case of unknown attacks. However, existing anomaly detection methods often raise false...
According to the situation that speech authentication algorithms are not appropriated for real-time speech content authentication, a novel speech perceptual hashing authentication algorithm based on discrete wavelet transform with combination of time-frequency domain features was proposed. Firstly, by discrete wavelet transform (DWT), a new signal in frequency domain is generated from the original...
It is required in the first step of malware analysis to determine whether a given malware program is a variant of known ones. If it is surely not a variant, manual analysis against it is required. However, it is impossible to perform manual analysis, the cost of which is very high, over all the enormous number of newly found malware programs. An automatic and accurate malware program classification...
Malicious software (Malware) in form of Internet worms, computer viruses, and trojan horses poses a major threat to the security of network systems. Identification of malware variants provides great benefit in early detection. Taking into account that variants of malware families share similar functions reflecting its origin and purpose, we propose a method focusing on the features of functions that...
To defend a network system from security risks, intrusion detection systems (IDSs) have been playing an important role in recent years. There are two types of detection algorithms of IDSs: misuse detection and anomaly detection. Because misuse detection is based on a signature which is created from the features of attack traffic by security experts, it can achieve accurate and stable detection. However,...
This paper discusses the vision-based UAV formation flight methods, describes the critical section-formation guidance, moving object extracting, object tracking in detail. At the same time, we propose a real-time video drawing method to apply to flying vehicle object extracting, and introduce the unscented Kalman filtering(UKF) into object tracking to improve the often-used extended Kalman filtering(EKF)...
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