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Paschalides, Demetris, Christodoulou, Chrysovalantis, Andreou, Rafael, Pallis, George, Dikaiakos, Marios D., Kornilakis, Alexandros, Markatos, Evangelos.  2019.  Check-It: A plugin for Detecting and Reducing the Spread of Fake News and Misinformation on the Web. 2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI). :298–302.
Over the past few years, we have been witnessing the rise of misinformation on the Internet. People fall victims of fake news continuously, and contribute to their propagation knowingly or inadvertently. Many recent efforts seek to reduce the damage caused by fake news by identifying them automatically with artificial intelligence techniques, using signals from domain flag-lists, online social networks, etc. In this work, we present Check-It, a system that combines a variety of signals into a pipeline for fake news identification. Check-It is developed as a web browser plugin with the objective of efficient and timely fake news detection, while respecting user privacy. In this paper, we present the design, implementation and performance evaluation of Check-It. Experimental results show that it outperforms state-of-the-art methods on commonly-used datasets.
Yulianto, Arief Dwi, Sukarno, Parman, Warrdana, Aulia Arif, Makky, Muhammad Al.  2019.  Mitigation of Cryptojacking Attacks Using Taint Analysis. 2019 4th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE). :234—238.

Cryptojacking (also called malicious cryptocurrency mining or cryptomining) is a new threat model using CPU resources covertly “mining” a cryptocurrency in the browser. The impact is a surge in CPU Usage and slows the system performance. In this research, in-browsercryptojacking mitigation has been built as an extension in Google Chrome using Taint analysis method. The method used in this research is attack modeling with abuse case using the Man-In-The-Middle (MITM) attack as a testing for mitigation. The proposed model is designed so that users will be notified if a cryptojacking attack occurs. Hence, the user is able to check the script characteristics that run on the website background. The results of this research show that the taint analysis is a promising method to mitigate cryptojacking attacks. From 100 random sample websites, the taint analysis method can detect 19 websites that are infcted by cryptojacking.

Tahir, Rashid, Durrani, Sultan, Ahmed, Faizan, Saeed, Hammas, Zaffar, Fareed, Ilyas, Saqib.  2019.  The Browsers Strike Back: Countering Cryptojacking and Parasitic Miners on the Web. IEEE INFOCOM 2019 - IEEE Conference on Computer Communications. :703—711.

With the recent boom in the cryptocurrency market, hackers have been on the lookout to find novel ways of commandeering users' machine for covert and stealthy mining operations. In an attempt to expose such under-the-hood practices, this paper explores the issue of browser cryptojacking, whereby miners are secretly deployed inside browser code without the knowledge of the user. To this end, we analyze the top 50k websites from Alexa and find a noticeable percentage of sites that are indulging in this exploitative exercise often using heavily obfuscated code. Furthermore, mining prevention plug-ins, such as NoMiner, fail to flag such cleverly concealed instances. Hence, we propose a machine learning solution based on hardware-assisted profiling of browser code in real-time. A fine-grained micro-architectural footprint allows us to classify mining applications with \textbackslashtextgreater99% accuracy and even flags them if the mining code has been heavily obfuscated or encrypted. We build our own browser extension and show that it outperforms other plug-ins. The proposed design has negligible overhead on the user's machine and works for all standard off-the-shelf CPUs.

Attarian, Reyhane, Hashemi, Sattar.  2019.  Investigating the Streaming Algorithms Usage in Website Fingerprinting Attack Against Tor Privacy Enhancing Technology. 2019 16th International ISC (Iranian Society of Cryptology) Conference on Information Security and Cryptology (ISCISC). :33–38.
Website fingerprinting attack is a kind of traffic analysis attack that aims to identify the URL of visited websites using the Tor browser. Previous website fingerprinting attacks were based on batch learning methods which assumed that the traffic traces of each website are independent and generated from the stationary probability distribution. But, in realistic scenarios, the websites' concepts can change over time (dynamic websites) that is known as concept drift. To deal with data whose distribution change over time, the classifier model must update its model permanently and be adaptive to concept drift. Streaming algorithms are dynamic models that have these features and lead us to make a comparison of various representative data stream classification algorithms for website fingerprinting. Given to our experiments and results, by considering streaming algorithms along with statistical flow-based network traffic features, the accuracy grows significantly.
Zollner, Stephan, Choo, Kim-Kwang Raymond, Le-Khac, Nhien-An.  2019.  An Automated Live Forensic and Postmortem Analysis Tool for Bitcoin on Windows Systems. IEEE Access. 7:158250—158263.

Bitcoin is popular not only with consumers, but also with cybercriminals (e.g., in ransomware and online extortion, and commercial online child exploitation). Given the potential of Bitcoin to be involved in a criminal investigation, the need to have an up-to-date and in-depth understanding on the forensic acquisition and analysis of Bitcoins is crucial. However, there has been limited forensic research of Bitcoin in the literature. The general focus of existing research is on postmortem analysis of specific locations (e.g. wallets on mobile devices), rather than a forensic approach that combines live data forensics and postmortem analysis to facilitate the identification, acquisition, and analysis of forensic traces relating to the use of Bitcoins on a system. Hence, the latter is the focus of this paper where we present an open source tool for live forensic and postmortem analysing automatically. Using this open source tool, we describe a list of target artifacts that can be obtained from a forensic investigation of popular Bitcoin clients and Web Wallets on different web browsers installed on Windows 7 and Windows 10 platforms.

Mueller, Tobias, Klotzsche, Daniel, Herrmann, Dominik, Federrath, Hannes.  2019.  Dangers and Prevalence of Unprotected Web Fonts. 2019 International Conference on Software, Telecommunications and Computer Networks (SoftCOM). :1—5.
Most Web sites rely on resources hosted by third parties such as CDNs. Third parties may be compromised or coerced into misbehaving, e.g. delivering a malicious script or stylesheet. Unexpected changes to resources hosted by third parties can be detected with the Subresource Integrity (SRI) mechanism. The focus of SRI is on scripts and stylesheets. Web fonts cannot be secured with that mechanism under all circumstances. The first contribution of this paper is to evaluates the potential for attacks using malicious fonts. With an instrumented browser we find that (1) more than 95% of the top 50,000 Web sites of the Tranco top list rely on resources hosted by third parties and that (2) only a small fraction employs SRI. Moreover, we find that more than 60% of the sites in our sample use fonts hosted by third parties, most of which are being served by Google. The second contribution of the paper is a proof of concept of a malicious font as well as a tool for automatically generating such a font, which targets security-conscious users who are used to verifying cryptographic fingerprints. Software vendors publish such fingerprints along with their software packages to allow users to verify their integrity. Due to incomplete SRI support for Web fonts, a third party could force a browser to load our malicious font. The font targets a particular cryptographic fingerprint and renders it as a desired different fingerprint. This allows attackers to fool users into believing that they download a genuine software package although they are actually downloading a maliciously modified version. Finally, we propose countermeasures that could be deployed to protect the integrity of Web fonts.
Joseph, Justin, Bhadauria, Saumya.  2019.  Cookie Based Protocol to Defend Malicious Browser Extensions. 2019 International Carnahan Conference on Security Technology (ICCST). :1—6.
All popular browsers support browser extensions. They are small software module for customizing web browsers. It provides extra features like user interface modifications, ad blocking, cookie management and so on. As features increase, security becomes more difficult. The impact of malicious browser extensions is also enormous. More than 1 million Chrome users got affected by extensions from Chrome store itself. [1] The risk further increases with offline extension installations. The privileges browser extensions have, pave the path for many kinds of attacks. Replay attack and session hijacking are two of these attacks we are dealing here. Here we propose a defence system based on dynamic encrypted cookies to defend these attacks. We use cookies as token for continuous authentication, which protects entire communication. Static cookies are prone for session hijacking, and therefore we use dynamic cookies which are sealed with encryption. It also protects from replay attack by changing itself, making previous message obsolete. This essentially solves both of the problems.
Burgess, Jonah, Carlin, Domhnall, O'Kane, Philip, Sezer, Sakir.  2019.  MANiC: Multi-step Assessment for Crypto-miners. 2019 International Conference on Cyber Security and Protection of Digital Services (Cyber Security). :1—8.

Modern Browsers have become sophisticated applications, providing a portal to the web. Browsers host a complex mix of interpreters such as HTML and JavaScript, allowing not only useful functionality but also malicious activities, known as browser-hijacking. These attacks can be particularly difficult to detect, as they usually operate within the scope of normal browser behaviour. CryptoJacking is a form of browser-hijacking that has emerged as a result of the increased popularity and profitability of cryptocurrencies, and the introduction of new cryptocurrencies that promote CPU-based mining. This paper proposes MANiC (Multi-step AssessmeNt for Crypto-miners), a system to detect CryptoJacking websites. It uses regular expressions that are compiled in accordance with the API structure of different miner families. This allows the detection of crypto-mining scripts and the extraction of parameters that could be used to detect suspicious behaviour associated with CryptoJacking. When MANiC was used to analyse the Alexa top 1m websites, it detected 887 malicious URLs containing miners from 11 different families and demonstrated favourable results when compared to related CryptoJacking research. We demonstrate that MANiC can be used to provide insights into this new threat, to identify new potential features of interest and to establish a ground-truth dataset, assisting future research.

Mohsen, Fadi, Jafaarian, Haadi.  2019.  Raising the Bar Really High: An MTD Approach to Protect Data in Embedded Browsers. 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC). 1:786—794.
The safety of web browsers is essential to the privacy of Internet users and the security of their computing systems. In the last few years, there have been several cyber attacks geared towards compromising surfers' data and systems via exploiting browser-based vulnerabilities. Android and a number of mobile operating systems have been supporting a UI component called WebView, which can be embedded in any mobile application to render the web contents. Yet, this mini-browser component has been found to be vulnerable to various kinds of attacks. For instance, an attacker in her WebView-Embedded app can inject malicious JavaScripts into the WebView to modify the web contents or to steal user's input values. This kind of attack is particularly challenging due to the full control of attackers over the content of the loaded pages. In this paper, we are proposing and testing a server-side moving target defense technique to counter the risk of JavaScript injection attacks on mobile WebViews. The solution entails creating redundant HTML forms, randomizing their attributes and values, and asserting stealthy prompts for the user data. The solution does not dictate any changes to the browser or applications codes, neither it requires key sharing with benign clients. The results of our performance and security analysis suggest that our proposed approach protects the confidentiality and integrity of user input values with minimum overhead.
Stark, Emily, Sleevi, Ryan, Muminovic, Rijad, O'Brien, Devon, Messeri, Eran, Felt, Adrienne Porter, McMillion, Brendan, Tabriz, Parisa.  2019.  Does Certificate Transparency Break the Web? Measuring Adoption and Error Rate 2019 IEEE Symposium on Security and Privacy (SP). :211—226.
Certificate Transparency (CT) is an emerging system for enabling the rapid discovery of malicious or misissued certificates. Initially standardized in 2013, CT is now finally beginning to see widespread support. Although CT provides desirable security benefits, web browsers cannot begin requiring all websites to support CT at once, due to the risk of breaking large numbers of websites. We discuss challenges for deployment, analyze the adoption of CT on the web, and measure the error rates experienced by users of the Google Chrome web browser. We find that CT has so far been widely adopted with minimal breakage and warnings. Security researchers often struggle with the tradeoff between security and user frustration: rolling out new security requirements often causes breakage. We view CT as a case study for deploying ecosystem-wide change while trying to minimize end user impact. We discuss the design properties of CT that made its success possible, as well as draw lessons from its risks and pitfalls that could be avoided in future large-scale security deployments.
Wang, Congli, Lin, Jingqiang, Li, Bingyu, Li, Qi, Wang, Qiongxiao, Zhang, Xiaokun.  2019.  Analyzing the Browser Security Warnings on HTTPS Errors. ICC 2019 - 2019 IEEE International Conference on Communications (ICC). :1—6.
HTTPS provides authentication, data confidentiality, and integrity for secure web applications in the Internet. In order to establish secure connections with the target website but not a man-in-the-middle or impersonation attacker, a browser shows security warnings to users, when different HTTPS errors happen (e.g., it fails to build a valid certificate chain, or the certificate subject does not match the domain visited). Each browser implements its own design of warnings on HTTPS errors, to balance security and usability. This paper presents a list of common HTTPS errors, and we investigate the browser behaviors on each error. Our study discloses browser defects on handling HTTPS errors in terms of cryptographic algorithm, certificate verification, name validation, HPKP, and HSTS.
Szabo, Roland, Gontean, Aurel.  2019.  The Creation Process of a Secure and Private Mobile Web Browser with no Ads and no Popups. 2019 IEEE 25th International Symposium for Design and Technology in Electronic Packaging (SIITME). :232—235.
The aim of this work is to create a new style web browser. The other web browsers can have safety issues and have many ads and popups. The other web browsers can fill up cache with the logging of big history of visited web pages. This app is a light-weight web browser which is both secure and private with no ads and no popups, just the plain Internet shown in full screen. The app does not store all user data, so the navigation of webpages is done in incognito mode. The app was made to open any new HTML5 web page in a secure and private mode with big focus on loading speed of the web pages.
Pewny, Jannik, Koppe, Philipp, Holz, Thorsten.  2019.  STEROIDS for DOPed Applications: A Compiler for Automated Data-Oriented Programming. 2019 IEEE European Symposium on Security and Privacy (EuroS P). :111–126.
The wide-spread adoption of system defenses such as the randomization of code, stack, and heap raises the bar for code-reuse attacks. Thus, attackers utilize a scripting engine in target programs like a web browser to prepare the code-reuse chain, e.g., relocate gadget addresses or perform a just-in-time gadget search. However, many types of programs do not provide such an execution context that an attacker can use. Recent advances in data-oriented programming (DOP) explored an orthogonal way to abuse memory corruption vulnerabilities and demonstrated that an attacker can achieve Turing-complete computations without modifying code pointers in applications. As of now, constructing DOP exploits requires a lot of manual work-for every combination of application and payload anew. In this paper, we present novel techniques to automate the process of generating DOP exploits. We implemented a compiler called STEROIDS that leverages these techniques and compiles our high-level language SLANG into low-level DOP data structures driving malicious computations at run time. This enables an attacker to specify her intent in an application-and vulnerability-independent manner to maximize reusability. We demonstrate the effectiveness of our techniques and prototype implementation by specifying four programs of varying complexity in SLANG that calculate the Levenshtein distance, traverse a pointer chain to steal a private key, relocate a ROP chain, and perform a JIT-ROP attack. STEROIDS compiles each of those programs to low-level DOP data structures targeted at five different applications including GStreamer, Wireshark and ProFTPd, which have vastly different vulnerabilities and DOP instances. Ultimately, this shows that our compiler is versatile, can be used for both 32-bit and 64-bit applications, works across bug classes, and enables highly expressive attacks without conventional code-injection or code-reuse techniques in applications lacking a scripting engine.
Chen, Ping, Yu, Han, Zhao, Min, Wang, Jinshuang.  2018.  Research and Implementation of Cross-site Scripting Defense Method Based on Moving Target Defense Technology. 2018 5th International Conference on Systems and Informatics (ICSAI). :818–822.

The root cause of cross-site scripting(XSS) attack is that the JavaScript engine can't distinguish between the JavaScript code in Web application and the JavaScript code injected by attackers. Moving Target Defense (MTD) is a novel technique that aim to defeat attacks by frequently changing the system configuration so that attackers can't catch the status of the system. This paper describes the design and implement of a XSS defense method based on Moving Target Defense technology. This method adds a random attribute to each unsafe element in Web application to distinguish between the JavaScript code in Web application and the JavaScript code injected by attackers and uses a security check function to verify the random attribute, if there is no random attribute or the random attribute value is not correct in a HTML (Hypertext Markup Language) element, the execution of JavaScript code will be prevented. The experiment results show that the method can effectively prevent XSS attacks and have little impact on the system performance.

Bukhari, Syed Nisar, Ahmad Dar, Muneer, Iqbal, Ummer.  2018.  Reducing attack surface corresponding to Type 1 cross-site scripting attacks using secure development life cycle practices. 2018 Fourth International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB). :1–4.

While because the range of web users have increased exponentially, thus has the quantity of attacks that decide to use it for malicious functions. The vulnerability that has become usually exploited is thought as cross-site scripting (XSS). Cross-site Scripting (XSS) refers to client-side code injection attack whereby a malicious user will execute malicious scripts (also usually stated as a malicious payload) into a legitimate web site or web based application. XSS is amongst the foremost rampant of web based application vulnerabilities and happens once an internet based application makes use of un-validated or un-encoded user input at intervals the output it generates. In such instances, the victim is unaware that their data is being transferred from a website that he/she trusts to a different site controlled by the malicious user. In this paper we shall focus on type 1 or "non-persistent cross-site scripting". With non-persistent cross-site scripting, malicious code or script is embedded in a Web request, and then partially or entirely echoed (or "reflected") by the Web server without encoding or validation in the Web response. The malicious code or script is then executed in the client's Web browser which could lead to several negative outcomes, such as the theft of session data and accessing sensitive data within cookies. In order for this type of cross-site scripting to be successful, a malicious user must coerce a user into clicking a link that triggers the non-persistent cross-site scripting attack. This is usually done through an email that encourages the user to click on a provided malicious link, or to visit a web site that is fraught with malicious links. In this paper it will be discussed and elaborated as to how attack surfaces related to type 1 or "non-persistent cross-site scripting" attack shall be reduced using secure development life cycle practices and techniques.

Li, X., Cui, X., Shi, L., Liu, C., Wang, X..  2018.  Constructing Browser Fingerprint Tracking Chain Based on LSTM Model. 2018 IEEE Third International Conference on Data Science in Cyberspace (DSC). :213-218.
Web attacks have increased rapidly in recent years. However, traditional methods are useless to track web attackers. Browser fingerprint, as a stateless tracking technique, can be used to solve this problem. Given browser fingerprint changes easily and frequently, it is easy to lose track. Therefore, we need to improve the stability of browser fingerprint by linking the new one to the previous chain. In this paper, we propose LSTM model to learn the potential relationship of browser fingerprint evolution. In addition, we adjust the input feature vector to time series and construct training set to train the model. The results show that our model can construct the tracking chain perfectly well with average ownership up to 99.3%.
Huang, M. Chiu, Wan, Y., Chiang, C., Wang, S..  2018.  Tor Browser Forensics in Exploring Invisible Evidence. 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC). :3909-3914.
Given the high frequency of information security incidents, feeling that we may soon become innocent victims of these events may be justified. Perpetrators of information security offenses take advantage of several methods to leave no evidence of their crimes, and this pattern of hiding tracks has caused difficulties for investigators searching for digital evidence. Use of the onion router (Tor) is a common way for criminals to conceal their identities and tracks. This paper aims to explain the composition and operation of onion routing; we conduct a forensic experiment to detect the use of the Tor browser and compare several browser modes, including incognito and normal. Through the experimental method described in this paper, investigators can learn to identify perpetrators of Internet crimes, which will be helpful in future endeavors in digital forensics.
Vastel, A., Rudametkin, W., Rouvoy, R..  2018.  FP -TESTER : Automated Testing of Browser Fingerprint Resilience. 2018 IEEE European Symposium on Security and Privacy Workshops (EuroS PW). :103-107.
Despite recent regulations and growing user awareness, undesired browser tracking is increasing. In addition to cookies, browser fingerprinting is a stateless technique that exploits a device's configuration for tracking purposes. In particular, browser fingerprinting builds on attributes made available from Javascript and HTTP headers to create a unique and stable fingerprint. For example, browser plugins have been heavily exploited by state-of-the-art browser fingerprinters as a rich source of entropy. However, as browser vendors abandon plugins in favor of extensions, fingerprinters will adapt. We present FP-TESTER, an approach to automatically test the effectiveness of browser fingerprinting countermeasure extensions. We implement a testing toolkit to be used by developers to reduce browser fingerprintability. While countermeasures aim to hinder tracking by changing or blocking attributes, they may easily introduce subtle side-effects that make browsers more identifiable, rendering the extensions counterproductive. FP-TESTER reports on the side-effects introduced by the countermeasure, as well as how they impact tracking duration from a fingerprinter's point-of-view. To the best of our knowledge, FP-TESTER is the first tool to assist developers in fighting browser fingerprinting and reducing the exposure of end-users to such privacy leaks.
Vastel, A., Laperdrix, P., Rudametkin, W., Rouvoy, R..  2018.  FP-STALKER: Tracking Browser Fingerprint Evolutions. 2018 IEEE Symposium on Security and Privacy (SP). :728-741.
Browser fingerprinting has emerged as a technique to track users without their consent. Unlike cookies, fingerprinting is a stateless technique that does not store any information on devices, but instead exploits unique combinations of attributes handed over freely by browsers. The uniqueness of fingerprints allows them to be used for identification. However, browser fingerprints change over time and the effectiveness of tracking users over longer durations has not been properly addressed. In this paper, we show that browser fingerprints tend to change frequently-from every few hours to days-due to, for example, software updates or configuration changes. Yet, despite these frequent changes, we show that browser fingerprints can still be linked, thus enabling long-term tracking. FP-STALKER is an approach to link browser fingerprint evolutions. It compares fingerprints to determine if they originate from the same browser. We created two variants of FP-STALKER, a rule-based variant that is faster, and a hybrid variant that exploits machine learning to boost accuracy. To evaluate FP-STALKER, we conduct an empirical study using 98,598 fingerprints we collected from 1, 905 distinct browser instances. We compare our algorithm with the state of the art and show that, on average, we can track browsers for 54.48 days, and 26 % of browsers can be tracked for more than 100 days.
Wang, M., Zhu, W., Yan, S., Wang, Q..  2018.  SoundAuth: Secure Zero-Effort Two-Factor Authentication Based on Audio Signals. 2018 IEEE Conference on Communications and Network Security (CNS). :1-9.

Two-factor authentication (2FA) popularly works by verifying something the user knows (a password) and something she possesses (a token, popularly instantiated with a smart phone). Conventional 2FA systems require extra interaction like typing a verification code, which is not very user-friendly. For improved user experience, recent work aims at zero-effort 2FA, in which a smart phone placed close to a computer (where the user enters her username/password into a browser to log into a server) automatically assists with the authentication. To prove her possession of the smart phone, the user needs to prove the phone is on the login spot, which reduces zero-effort 2FA to co-presence detection. In this paper, we propose SoundAuth, a secure zero-effort 2FA mechanism based on (two kinds of) ambient audio signals. SoundAuth looks for signs of proximity by having the browser and the smart phone compare both their surrounding sounds and certain unpredictable near-ultrasounds; if significant distinguishability is found, SoundAuth rejects the login request. For the ambient signals comparison, we regard it as a classification problem and employ a machine learning technique to analyze the audio signals. Experiments with real login attempts show that SoundAuth not only is comparable to existent schemes concerning utility, but also outperforms them in terms of resilience to attacks. SoundAuth can be easily deployed as it is readily supported by most smart phones and major browsers.

Varshney, G., Bagade, S., Sinha, S..  2018.  Malicious browser extensions: A growing threat: A case study on Google Chrome: Ongoing work in progress. 2018 International Conference on Information Networking (ICOIN). :188–193.

Browser extensions are a way through which third party developers provide a set of additional functionalities on top of the traditional functionalities provided by a browser. It has been identified that the browser extension platform can be used by hackers to carry out attacks of sophisticated kinds. These attacks include phishing, spying, DDoS, email spamming, affiliate fraud, mal-advertising, payment frauds etc. In this paper, we showcase the vulnerability of the current browsers to these attacks by taking Google Chrome as the case study as it is a popular browser. The paper also discusses the technical reason which makes it possible for the attackers to launch such attacks via browser extensions. A set of suggestions and solutions that can thwart the attack possibilities has been discussed.

Sivanesan, A. P., Mathur, A., Javaid, A. Y..  2018.  A Google Chromium Browser Extension for Detecting XSS Attack in HTML5 Based Websites. 2018 IEEE International Conference on Electro/Information Technology (EIT). :0302–0304.

The advent of HTML 5 revives the life of cross-site scripting attack (XSS) in the web. Cross Document Messaging, Local Storage, Attribute Abuse, Input Validation, Inline Multimedia and SVG emerge as likely targets for serious threats. Introduction of various new tags and attributes can be potentially manipulated to exploit the data on a dynamic website. The XSS attack manages to retain a spot in all the OWASP Top 10 security risks released over the past decade and placed in the seventh spot in OWASP Top 10 of 2017. It is known that XSS attempts to execute scripts with untrusted data without proper validation between websites. XSS executes scripts in the victim's browser which can hijack user sessions, deface websites, or redirect the user to the malicious site. This paper focuses on the development of a browser extension for the popular Google Chromium browser that keeps track of various attack vectors. These vectors primarily include tags and attributes of HTML 5 that may be used maliciously. The developed plugin alerts users whenever a possibility of XSS attack is discovered when a user accesses a particular website.

Baykara, M., Güçlü, S..  2018.  Applications for detecting XSS attacks on different web platforms. 2018 6th International Symposium on Digital Forensic and Security (ISDFS). :1–6.

Today, maintaining the security of the web application is of great importance. Sites Intermediate Script (XSS) is a security flaw that can affect web applications. This error allows an attacker to add their own malicious code to HTML pages that are displayed to the user. Upon execution of the malicious code, the behavior of the system or website can be completely changed. The XSS security vulnerability is used by attackers to steal the resources of a web browser such as cookies, identity information, etc. by adding malicious Java Script code to the victim's web applications. Attackers can use this feature to force a malicious code worker into a Web browser of a user, since Web browsers support the execution of embedded commands on web pages to enable dynamic web pages. This work has been proposed as a technique to detect and prevent manipulation that may occur in web sites, and thus to prevent the attack of Site Intermediate Script (XSS) attacks. Ayrica has developed four different languages that detect XSS explanations with Asp.NET, PHP, PHP and Ruby languages, and the differences in the detection of XSS attacks in environments provided by different programming languages.

Eskandari, S., Leoutsarakos, A., Mursch, T., Clark, J..  2018.  A First Look at Browser-Based Cryptojacking. 2018 IEEE European Symposium on Security and Privacy Workshops (EuroS PW). :58–66.

In this paper, we examine the recent trend to- wards in-browser mining of cryptocurrencies; in particular, the mining of Monero through Coinhive and similar code- bases. In this model, a user visiting a website will download a JavaScript code that executes client-side in her browser, mines a cryptocurrency - typically without her consent or knowledge - and pays out the seigniorage to the website. Websites may consciously employ this as an alternative or to supplement advertisement revenue, may offer premium content in exchange for mining, or may be unwittingly serving the code as a result of a breach (in which case the seigniorage is collected by the attacker). The cryptocurrency Monero is preferred seemingly for its unfriendliness to large-scale ASIC mining that would drive browser-based efforts out of the market, as well as for its purported privacy features. In this paper, we survey this landscape, conduct some measurements to establish its prevalence and profitability, outline an ethical framework for considering whether it should be classified as an attack or business opportunity, and make suggestions for the detection, mitigation and/or prevention of browser-based mining for non- consenting users.

Larisch, J., Choffnes, D., Levin, D., Maggs, B. M., Mislove, A., Wilson, C..  2017.  CRLite: A Scalable System for Pushing All TLS Revocations to All Browsers. 2017 IEEE Symposium on Security and Privacy (SP). :539–556.

Currently, no major browser fully checks for TLS/SSL certificate revocations. This is largely due to the fact that the deployed mechanisms for disseminating revocations (CRLs, OCSP, OCSP Stapling, CRLSet, and OneCRL) are each either incomplete, insecure, inefficient, slow to update, not private, or some combination thereof. In this paper, we present CRLite, an efficient and easily-deployable system for proactively pushing all TLS certificate revocations to browsers. CRLite servers aggregate revocation information for all known, valid TLS certificates on the web, and store them in a space-efficient filter cascade data structure. Browsers periodically download and use this data to check for revocations of observed certificates in real-time. CRLite does not require any additional trust beyond the existing PKI, and it allows clients to adopt a fail-closed security posture even in the face of network errors or attacks that make revocation information temporarily unavailable. We present a prototype of name that processes TLS certificates gathered by Rapid7, the University of Michigan, and Google's Certificate Transparency on the server-side, with a Firefox extension on the client-side. Comparing CRLite to an idealized browser that performs correct CRL/OCSP checking, we show that CRLite reduces latency and eliminates privacy concerns. Moreover, CRLite has low bandwidth costs: it can represent all certificates with an initial download of 10 MB (less than 1 byte per revocation) followed by daily updates of 580 KB on average. Taken together, our results demonstrate that complete TLS/SSL revocation checking is within reach for all clients.