دانلود رایگان مقاله انگلیسی آنالیز اطلاعات انگشت نگاری کردن کلان داده ها برای پایداری - الزویر 2018

Abstract

Web-based device fingerprinting is the process of collecting security information through the browser to perform stateless device identification. Fingerprints may then be used to identify and track computing devices in the web. There are various reasons why device-related information may be needed. Among the others, this technique could help to efficiently analyze security information for sustainability. In this paper we introduce a fingerprinting analytics tool that discovers the most appropriate device fingerprints and their corresponding optimal implementations. The fingerprints selected in the result of the performed analysis are used to enrich and improve an open-source fingerprinting analytics tool Fingerprintjs2, daily consumed by hundreds of websites. As a result, the paper provides a noticeable progress in analytics of dozens of values of device fingerprints, and enhances analysis of fingerprints security information.

Conclusions and Future Work

As digital transactions and interactions continue to grow in volume and importance, the necessity of authentication and verification of the identity of their 1060 participants will continue to grow. One of the mechanisms that can be utilized for this purpose is fingerprinting, which plays recently a more and more significant role in sustainable user authentication and web tracking. This techniques has a very broad scope of use cases, among which are fraud detection, adjusting security policies and management, identifying and blocking botnets, real-time 1065 target marketing, limiting access to services (for example when filling the surveys), to name just a few. Due to fingerprinting analytics linking a device to a user is possible, as well as identifying the user who uses multiple devices to access the same service. Despite the indisputable role of computing device fingerprinting in web track1070 ing, this paper proves that the application of fingerprinting technique is really demanding, and it requires a lot of effort to develop an efficient fingerprinting algorithm. The resulting solution presents satisfactory performance in terms of diversity, execution time and the length of the code bundle, yet demonstrates a need for improvement of its stability, which is essential in most of the usages. 1075 Except for the benefits coming from conducting the first evaluation of different fingerprint implementations and producing an optimal set of features, this work allows to draw many additional conclusions. The implication of the performed analysis of existing solutions is the revealment of some misconceptions that they introduce — creating artificial fingerprints like browser tempering is 1080 only exacerbating the overall efficiency. Some of the fingerprints (ad-block extension detection, flash-based) have been found to be unstable between regular browsing and private-mode, something that should not make a difference to a respectable algorithm. An instability of certain fingerprints was observed and discussed altogether with potential causes and possible improvements. Finally, 1085 the paper proves the superiority of CSS-based font probing over canvas-based solutions and allows to select a reference set of fonts providing the best detection performance. Additionally, some important objectives of an advanced server solution were pointed out. The outcome of our research provides a noticeable progress in the fingerprinting analytics. The discovered features and 1090 corresponding optimal implementations will enrich and improve an open-source fingerprinting library Fingerprintjs2 that is daily consumed by hundreds of websites.