On the other hand, we find that FLIS parties are often reported for copyright violations and host their infrastructure predominantly in Europe and Belize. On the one hand, our analysis reveals that users of FLIS websites are generally exposed to deceptive advertisements, malware, malicious browser extensions, and fraudulent scams. We develop an infrastructure that enables us to perform more than 850,000 visits by identifying 5,685 free live streaming domains, and analyze more than 1 Terabyte of traffic to map the parties that constitute the FLIS ecosystem. This paper presents a comprehensive analysis of the FLIS ecosystem by mapping all parties involved in the anonymous broadcast of live streams, discovering their modus operandi, and quantifying the consequences for common Internet users who utilize these services. Despite the immense popularity of these services, little is known about the parties that facilitate it and maintain webpages to index links for free viewership. Free live streaming (FLIS) services attract millions of viewers and make heavy use of deceptive advertisements. Recent years have seen extensive growth of services enabling free broadcasts of live streams on the Web. The Bagged Trees classifier exhibited the highest accuracy of 90.1% and reported 96.24% true positive and 26.07% false positive rate. We develop a graphical user interface program to allow the end user to examine the URL before visiting the website. The approach is expected to serve as a base for implementing and developing anti drive-by download programs. We test 23 different machine learning classifiers using data set of 5435 webpages and based on the detection accuracy we selected the top five to build our detection model. In this paper, we propose a novel approach to detect drive-by download infected web pages based on extracted features from their source code. However, a few proposed dynamic classification techniques, which suffer from clear shortcomings. Researchers proposed plenty of detection approaches mostly passive blacklisting. Traditional antivirus and intrusion detection systems are not efficient against such attacks. The damage may include data leakage leading to financial loss. This type of attack is accomplished by exploiting web browsers and plugins vulnerabilities. Drive-by download refers to attacks that automatically download malwares to user's computer without his knowledge or consent.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |