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The pervasive imbalanced class distribution occurring in real-world stream applications, such as surveillance, security and finance, in which data arrive continuously has sparked extensive interest in the study of imbalanced stream classification. In such applications, the evolution of unstable class concepts is always accompanied and complicated by the skewed class distribution. However, most of...
Since last decades, online technologies have revolutionized the modern computing world. However, as a result, security threats are increasing rapidly. A huge community is using the online services even from chatting to banking is done via online transactions. Customers of web technologies face various security threats and phishing is one of the most important threat that needs to be address. Therefore,...
During the past years, malicious PDF files have become a serious threat for the security of modern computer systems. They are characterized by a complex structure and their variety is considerably high. Several solutions have been academically developed to mitigate such attacks. However, they leveraged on information that were extracted from either only the structure or the content of the PDF file...
WebSocket is a promising technique to build a real-time low-cost bidirectional communication channel. It supports arbitrary application-layer protocols including privately designed ones. The use of WebSocket poses a new challenge to network traffic management and security inspection. To increase visibility for WebSocket traffic, this letter proposes an automatic keyword mining approach for protocols...
Anomaly detection in time series is one of the fundamental issues in data mining that addresses various problems in different domains such as intrusion detection in computer networks, irregularity detection in healthcare sensory data and fraud detection in insurance or securities. Although, there has been extensive work on anomaly detection, majority of the techniques look for individual objects that...
Security levels used in organizations today are typically course-grained, broad and distinct, using security levels such as "Confidential" and Secret". However, current research is advocating a move towards more fine-grained security models, e.g. Such as Attribute-Based Access Control, where information objects and end-users are characterized in terms of complex meta-data. One idea...
Advanced networking technology and increasing information services have led to extensive interconnection between Building Automation and Control (BAC) networks and Internet. The connection to Internet and public networks massively elevates the risk of the BAC networks being attacked. In this paper, we present a framework for a rule based anomaly detection of Building Automation and Control networks...
Market manipulation remains the biggest concern of investors in today's securities market, despite fast and strict responses from regulators and exchanges to market participants that pursue such practices. The existing methods in the industry for detecting fraudulent activities in securities market rely heavily on a set of rules based on expert knowledge. The securities market has deviated from its...
Due to great advances in computing and Internet technologies, organizations have been enabled to collect and generate a large amount of data. Most of these organizations tend to analyze their data to discover new patterns. Usually, analyzing such amount of data requires huge computational power and storage facilities that may not be available to these organizations. Cloud computing offers the best...
In this paper we present a fast, interactive method for collecting structural primitives from objects of interest contained within manually selected image regions. The input image is projected onto a Max-Tree and Min-Tree structure from which a pixel-to-node mapper marks the nodes of each tree that correspond to peak components explicitly contained within the selected window. In a pass through the...
This paper presents a VoIP Fraud Detection Framework by exploiting VoIP and/or network-OSS/BSS vulnerabilities. This can be accomplished by analyzing the behavior of the VoIP user using an ontology model so that different types of fraud scenarios could be identified. Using this ontology, an unsupervised learning algorithm has been implemented that describes the user behavior and/or the correlation...
A bug-tracking system such as Bugzilla contains bug reports (BRs) collected from various sources such as development teams, testing teams, and end users. When bug reporters submit bug reports to a bug-tracking system, the bug reporters need to label the bug reports as security bug reports (SBRs) or not, to indicate whether the involved bugs are security problems. These SBRs generally deserve higher...
It is important to do research on the source trustworthiness of the massive data under network environment. A detection method of source trustworthiness in text is proposed and designed based on cognitive hash. Based on the HowNet semantic features, this paper designs a text cognitive hash, and proposes a method evaluating feasible hash distance. Experimental results show the effectiveness of the...
Counterfeiting is a major concern for brand owners. Since printing is used to convey brands, brand owners should be able to analyze images of printed areas to gauge if the printing was performed by an authentic or a counterfeit printer/label converter. In this paper, we describe a system that uses a small set of pre-classified images (either authentic or counterfeit images from the same source) for...
Automatic detection of an unusual event in video sequence has an interesting application in security surveillance. This paper proposed a method to detect a gathering event without tracking individuals by using background subtracted blobs as the event feature and dividing the video frame into blocks. The feature sequences are encoded with hidden Markov model to detect the gathering event. The experimental...
The important issue in multi-class classification on support vector machines is the decision rule, which determines whether an input pattern belongs to a predicted class. To enhance the accuracy of multi-class classification, this study proposes a multi-weighted majority voting algorithm of support vector machine (SVM), and applies it to overcome complex facial security application. The proposed algorithm...
This article has conducted the research to food security risk early warning under the supplied chain environment by the BP neural network. The paper has constructed food security risk early warning model and simulated to it. The result has proven BP neural network model serviceability and the feasibility.
Aging or sedentary behavior can decrease motor capabilities causing a loss of autonomy. Prevention or re-adaptation programs that involve practice of physical activities can be precious tools to fight against this phenomenon. ??Serious?? video game have the potential to help people to train their body mainly due to the immersion of the participant in a motivating interaction with virtual environments...
In order to synthetically utilize the multi-steganalysis algorithms, and ulteriorly enhance the detection accuracy, the united-judgment methods based on parameter-estimation were proposed for image steganalysis. According to two types of universal blind detection and specific steganalysis, a united-judgment method based on weight and threshold, and also a method based on segment were proposed in this...
This paper discusses covert testing data and key human factors. First, different reasons why airport security screeners sometimes fail to detect threats when covert tests are conducted at airports are discussed. Key human factors are identified and analyzed with regard to covert test results. It is explained that pre-employment selection and training are indispensable prerequisites for good operational...
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