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Denizens of the Internet are coming under a barrage of phishing attacks of increasing frequency and sophistication. Emails accompanied by authentic looking websites are ensnaring users who, unwittingly, hand over their credentials compromising both their privacy and security. Methods such as the blacklisting of these phishing websites become untenable and cannot keep pace with the explosion of fake...
Online reviews are becoming one of the vital components of e-commerce in recent years as so many people consider having different opinions prior to buying online products or apprehending any online service. Nowadays, in the era of web 2.0, it is completely understandable that people rely on online reviews more than ever while taking a decision. However, guaranteeing the authenticity of these sensitive...
Demographic attributes of customers such as gender, age, etc. provide important information for e-commerce service providers in marketing and personalization of web applications. However, online customers often do not provide this kind of information due to privacy issues and other security-related reasons. In this paper, we proposed a method for predicting the gender of customers based on their catalog...
Numerous databases of DNA-microarrays are now widely available on the internet. Recently, there has been increasing interest in the analysis of microarray data using machine-learning techniques due to the amount of data, which is too massive for researchers to analyze using conventional techniques. In this study, we propose a method of finding a disease-related gene from microarray data using random...
An online auction is an auction held over the internet. In today's era of the internet, economies have changed the way than they were a few years back. The scope and reach of online auctions have been propelled by internet to the prominent level because online auctions break down and remove the physical limitations of traditional auctions such as geography, presence, time, space, etc. As online auction...
Discovering user intentions behind Web search queries is key to improving user experience. Usually, this task is seen as a classification problem, in which a sample of annotated user query intentions are provided to a supervised machine learning algorithm or classifier that learns from these examples and then can classify unseen user queries. This article proposes a new approach based on an ensemble...
With the increasing risk of data leakage, information guards have emerged as a novel concept in the field of security which bears similarity to spam filter that examine the content of the exchanged messages. A guard is defined as a high-assurance device used to control the information flow, typically from a domain with a "high" level of confidentiality, such as a corporate or military network,...
Android is one of the most popular open-source smartphone operating system and its access control permission mechanisms cannot detect any malware behavior. In this paper, new software behavior-based anomaly detection system is proposed to detect anomaly caused by malware. It works by analyzing anomalies on power consumption, battery temperature and network traffic data using machine learning classification...
After lung cancer, breast cancer is known to be the greatest cause for death among females [20]. The improving effectiveness of machine learning approaches is being given a lot of importance by medical practitioners for breast cancer diagnosis. The paper proposes an effective hybridized classifier for breast cancer diagnosis. The classifier is made by combining an unsupervised artificial neural network...
To alleviate the loads of tracking web log file by human effort, machine learning methods are now commonly used to analyze log data and to identify the pattern of malicious activities. Traditional kernel based techniques, like the neural network and the support vector machine (SVM), typically can deliver higher prediction accuracy. However, the user of a kernel based techniques normally cannot get...
Changes in the network topology such as large-scale power outages or Internet worm attacks are events that may induce routing information updates. Border Gateway Protocol (BGP) is by Autonomous Systems (ASes) to address these changes. Network reachability information, contained in BGP update messages, is stored in the Routing Information Base (RIB). Recent BGP anomaly detection systems employ machine...
The researchers have started looking for Internet traffic recognition techniques that are independent of ‘well known’ TCP or UDP port numbers, or interpreting the contents of packet payloads. Newer approaches classify traffic by recognizing statistical patterns in externally observable attributes of the traffic (such as typical packet lengths and inter-arrival times). The main goal is to cluster or...
The Internet contains potentially harmful or inappropriate content in web pages that parents may not wish their children to access. A possible solution is an internet content filter, to block prohibitive content. This paper proposes a system called SMART SAINT, which can deliver high accuracy classifiers using a welcome combination of active semi-supervised learning and feature selection. The system...
Traffic classification plays an important role in many short to medium term network management tasks and in long term network dimensioning/planning. In recent years a number of traffic classifiers have been proposed, in particular classifiers based on machine learning techniques exhibit high levels of accuracy. However, in practice, even if classifiers can be accurately trained at a given time, their...
Research of sentence orientation is aim to obtain the useful orientation information, it becomes a research focus in the nature language processing, especially in Micro-blog. Based on the existed How Net semantic similarity, this paper presents a sentence orientation identification method taking advantage of an improved algorithm for calculating Chinese term semantic orientation value. Firstly, this...
In this paper a new method to detect cross-language plagiarism in electronic documents is presented. The method is based on natural language processing techniques and machine learning methods. Preliminary results show that the system is able to identify the Internet sources of plagiarism of texts written in Spanish that have been copied (by humans and machines) from English sources.
The increase of malware that are exploiting the Internet daily has become a serious threat. The manual heuristic inspection of malware analysis is no longer considered effective and efficient compared against the high spreading rate of malware. Hence, automated behavior-based malware detection using machine learning techniques is considered a profound solution. The behavior of each malware on an emulated...
With the development of Internet, the increasing volume of information posted on micro-blogging sites like Twitter necessitates the need for efficient information filtering. In conventional text classification problems, it is assumed that the feature vectors extracted from the available documents are sufficient to learn good classifiers. However, this conventional approach is not likely to work for...
The increased number of documents in digital format available on the Web and its useful information for different purposes entail an essential need to organize them. However, this task must be automated in order to save costs and manpower. In the community research, the main approach to face this problem is based on the application of machine learning techniques. This article studies the main machine...
Obfuscated and encrypted protocols hinder traffic classification by classical techniques such as port analysis or deep packet inspection. Therefore, there is growing interest for classification algorithms based on statistical analysis of the length of the first packets of flows. Most classifiers proposed in literature are based on machine learning techniques and consider each flow independently of...
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