Biblio

The popularity of portable web browsers is increasing due to its convenient and compact nature along with the benefit of the data being stored and transferred easily using a USB drive. As technology gets updated frequently, developers are working on web browsers that can be portable in nature with additional security features like private mode browsing, built in ad blockers etc. The increased probability of using portable web browsers for carrying out nefarious activities is a result of cybercriminals with the thought that if they use portable web browsers in private mode it won't leave a digital footprint. Hence, the research paper aims at performing a comparative study of four portable web browsers namely Brave, TOR, Vivaldi, and Maxthon along with various memory acquisition tools to understand the quantity and quality of the data that can be recovered from the memory dump in two different conditions that is when the browser tabs were open and when the browser tabs were closed in a system to aid the forensic investigators.

The main threats in complex networks for large-scale information systems using web browsers or service browsers are analyzed. The necessary security features for these types of systems are compared. The advantages of systems developed with service-browser technology are shown.

Users rely on their web browser to provide information about the websites they are visiting, such as the security state of the web page their viewing. Current browsers do not differentiate between the live Web and the past Web. If a user loads an archived web page, known as a memento, they have to rely on user interface (UI) elements within the page itself to inform them that the page they are viewing is not the live Web. Memento-awareness extends beyond recognizing a page that has already been archived. The browser should give users the ability to easily archive live web pages as they are browsing. This report presents a proof-of-concept browser that is memento-aware and is created by extending Google's open-source web browser Chromium.

Internet browser is the most normally utilized customer application and speed and proficiency of our online work rely upon program generally. As the market is immersed with new programs there is a ton of disarray in everybody’s psyche regarding which is the best program. Our task intends to respond to this inquiry. We have done a relative investigation of the most well-known internet browsers specifically Google Chrome, Mozilla Firefox, Internet Explorer, Microsoft Edge, Opera, etc. In the main period of our task different correlation boundaries are chosen which can be comprehensively classified into - General Features, Security highlights, and program extensibility highlights. Utilizing the chose benchmarking instruments every program is tried. The main objective of this study is to identify the security vulnerabilities of popular web browsers. We have also discussed and analyzed each potential security vulnerability found in the web browsers. The study also tries to recommend viable measures to slow down the security breach in web browsers.

Cross-site scripting (XSS) is an often-occurring major attack that developers should consider when developing web applications. We develop a system that can provide practical exercises for learning how to create web applications that are secure against XSS. Our system utilizes free software and virtual machines, allowing low-cost, safe, and practical exercises. By using two virtual machines as the web server and the attacker host, the learner can conduct exercises demonstrating both XSS countermeasures and XSS attacks. In our system, learners use a web browser to learn and perform exercises related to XSS. Experimental evaluations confirm that the proposed system can support learning of XSS countermeasures.

Web browsers are primary targets of attacks because of their extensive uses and the fact that they interact with sensitive data. Vulnerabilities present in a web browser can pose serious risk to millions of users. Thus, it is pertinent to address these vulnerabilities to provide adequate protection for personally identifiable information. Research done in the past has showed that few vulnerability discovery models (VDMs) highlight the characterization of vulnerability discovery process. In these models, severity which is one of the most crucial properties has not been considered. Vulnerabilities can be categorized into different levels based on their severity. The discovery process of each kind of vulnerabilities is different from the other. Hence, it is essential to incorporate the severity of the vulnerabilities during the modelling of the vulnerability discovery process. This paper proposes a model to assess the vulnerabilities present in the software quantitatively with consideration for the severity of the vulnerabilities. It is possible to apply the proposed model to approximate the number of vulnerabilities along with vulnerability discovery rate, future occurrence of vulnerabilities, risk analysis, etc. Vulnerability data obtained from one of the major web browsers (Google Chrome) is deployed to examine goodness-of-fit and predictive capability of the proposed model. Experimental results justify the fact that the model proposed herein can estimate the required information better than the existing VDMs.

ARGOS is a web service we implemented to offer face recognition Authentication Services (AaaS) to mobile and desktop (via the web browser) end users. The Authentication Services may be used by 3rd party service organizations to enhance their service offering to their customers. ARGOS implements a secure face recognition-based authentication service aiming to provide simple and intuitive tools for 3rd party service providers (like PayPal, banks, e-commerce etc) to replace passwords with face biometrics. It supports authentication from any device with 2D or 3D frontal facing camera (mobile phones, laptops, tablets etc.) and almost any operating systems (iOS, Android, Windows and Linux Ubuntu).

The popularity of Web-based computing has given increase to browser-based cyberattacks. These cyberattacks use websites that exploit various web browser vulnerabilities. To help regular users avoid exploit websites and engage in safe online activities, we propose a methodology of building a machine learning-powered predictive analytical model that will measure the risk of attacks and privacy breaches associated with visiting different websites and performing online activities using web browsers. The model will learn risk levels from historical data and metadata scraped from web browsers.

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.

The Internet of Things (IoT) is changing the way we interact with everyday objects. "Smart" devices will reduce energy use, keep our homes safe, and improve our health. However, as recent attacks have shown, these devices also create tremendous security vulnerabilities in our computing networks. Securing all of these devices is a daunting task. In this paper, we argue that IoT device communications should be default-off and desired network communications must be explicitly enabled. Unlike traditional networked applications or devices like a web browser or PC, IoT applications and devices serve narrowly defined purposes and do not require access to all services in the network. Our proposal, Bark, a policy language and runtime for specifying and enforcing minimal access permissions in IoT networks, exploits this fact. Bark phrases access control policies in terms of natural questions (who, what, where, when, and how) and transforms them into transparently enforceable rules for IoT application protocols. Bark can express detailed rules such as "Let the lights see the luminosity of the bedroom sensor at any time" and "Let a device at my front door, if I approve it, unlock my smart lock for 30 seconds" in a way that is presentable and explainable to users. We implement Bark for Wi-Fi/IP and Bluetooth Low Energy (BLE) networks and evaluate its efficacy on several example applications and attacks.

Modern personal computers have embraced increasingly powerful Graphics Processing Units (GPUs). Recently, GPU-based graphics acceleration in web apps (i.e., applications running inside a web browser) has become popular. WebGL is the main effort to provide OpenGL-like graphics for web apps and it is currently used in 53% of the top-100 websites. Unfortunately, WebGL has posed serious security concerns as several attack vectors have been demonstrated through WebGL. Web browsers\guillemotright solutions to these attacks have been reactive: discovered vulnerabilities have been patched and new runtime security checks have been added. Unfortunately, this approach leaves the system vulnerable to zero-day vulnerability exploits, especially given the large size of the Trusted Computing Base of the graphics plane. We present Sugar, a novel operating system solution that enhances the security of GPU acceleration for web apps by design. The key idea behind Sugar is using a dedicated virtual graphics plane for a web app by leveraging modern GPU virtualization solutions. A virtual graphics plane consists of a dedicated virtual GPU (or vGPU) as well as all the software graphics stack (including the device driver). Sugar enhances the system security since a virtual graphics plane is fully isolated from the rest of the system. Despite GPU virtualization overhead, we show that Sugar achieves high performance. Moreover, unlike current systems, Sugar is able to use two underlying physical GPUs, when available, to co-render the User Interface (UI): one GPU is used to provide virtual graphics planes for web apps and the other to provide the primary graphics plane for the rest of the system. Such a design not only provides strong security guarantees, it also provides enhanced performance isolation.

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.

Trust in SSL-based communications is provided by Certificate Authorities (CAs) in the form of signed certificates. Checking the validity of a certificate involves three steps: (i) checking its expiration date, (ii) verifying its signature, and (iii) ensuring that it is not revoked. Currently, such certificate revocation checks are done either via Certificate Revocation Lists (CRLs) or Online Certificate Status Protocol (OCSP) servers. Unfortunately, despite the existence of these revocation checks, sophisticated cyber-attackers, may trick web browsers to trust a revoked certificate, believing that it is still valid. Consequently, the web browser will communicate (over TLS) with web servers controlled by cyber-attackers. Although frequently updated, nonced, and timestamped certificates may reduce the frequency and impact of such cyber-attacks, they impose a very large overhead to the CAs and OCSP servers, which now need to timestamp and sign on a regular basis all the responses, for every certificate they have issued, resulting in a very high overhead. To mitigate this overhead and provide a solution to the described cyber-attacks, we present CCSP: a new approach to provide timely information regarding the status of certificates, which capitalizes on a newly introduced notion called signed collections. In this paper, we present the design, preliminary implementation, and evaluation of CCSP in general, and signed collections in particular. Our preliminary results suggest that CCSP (i) reduces space requirements by more than an order of magnitude, (ii) lowers the number of signatures required by 6 orders of magnitude compared to OCSP-based methods, and (iii) adds only a few milliseconds of overhead in the overall user latency.

This paper discusses possible approaches to address the loss of user privacy when browsing the web and being tracked by websites which compute a browser fingerprint identifying the user computer. The key problem is that the current fingerprinting countermeasures are insufficient to prevent fingerprinting tracking and also frequently produce side-effects on the web browser. The advantages and disadvantages of possible countermeasures are discussed in the context of improving resistance against browser fingerprinting. Finally, using a new browser extension is proposed as the best way to inhibit fingerprinting as it could probably inhibit some of the fingerprinting techniques used and also diminish the side-effects on the user browser experience, compared with existing techniques.

Cross-site scripting (XSS) attacks keep plaguing the Web. Supported by most modern browsers, Content Security Policy (CSP) prescribes the browser to restrict the features and communication capabilities of code on a web page, mitigating the effects of XSS.

This paper puts a spotlight on the problem of data exfiltration in the face of CSP. We bring attention to the unsettling discord in the security community about the very goals of CSP when it comes to preventing data leaks.

As consequences of this discord, we report on insecurities in the known protection mechanisms that are based on assumptions about CSP that turn out not to hold in practice.

To illustrate the practical impact of the discord, we perform a systematic case study of data exfiltration via DNS prefetching and resource prefetching in the face of CSP.

Our study of the popular browsers demonstrates that it is often possible to exfiltrate data by both resource prefetching and DNS prefetching in the face of CSP. Further, we perform a crawl of the top 10,000 Alexa domains to report on the cohabitance of CSP and prefetching in practice. Finally, we discuss directions to control data exfiltration and, for the case study, propose measures ranging from immediate fixes for the clients to prefetching-aware extensions of CSP.

In the cyber crime huge log data, transactional data occurs which tends to plenty of data for storage and analyze them. It is difficult for forensic investigators to play plenty of time to find out clue and analyze those data. In network forensic analysis involves network traces and detection of attacks. The trace involves an Intrusion Detection System and firewall logs, logs generated by network services and applications, packet captures by sniffers. In network lots of data is generated in every event of action, so it is difficult for forensic investigators to find out clue and analyzing those data. In network forensics is deals with analysis, monitoring, capturing, recording, and analysis of network traffic for detecting intrusions and investigating them. This paper focuses on data collection from the cyber system and web browser. The FTK 4.0 is discussing for memory forensic analysis and remote system forensic which is to be used as evidence for aiding investigation.
 

Cross-Site Scripting (XSS) is a common attack technique that lets attackers insert the code in the output application of web page which is referred to the web browser of visitor and then the inserted code executes automatically and steals the sensitive information. In order to prevent the users from XSS attack, many client- side solutions have been implemented; most of them being used are the filters that sanitize the malicious input. However, many of these filters do not provide prevention to the newly designed sophisticated attacks such as multiple points of injection, injection into script etc. This paper proposes and implements an approach based on encoding unfiltered reflections for detecting vulnerable web applications which can be exploited using above mentioned sophisticated attacks. Results prove that the proposed approach provides accurate higher detection rate of exploits. In addition to this, an implementation of blocking the execution of malicious scripts have contributed to XSS-Me: an open source Mozilla Firefox security extension that detects for reflected XSS vulnerabilities which can be considered as an effective solution if it is integrated inside the browser rather than being enforced as an extension.

We are currently moving from the Internet society to a mobile society where more and more access to information is done by previously dumb phones. For example, the number of mobile phones using a full blown OS has risen to nearly 200% from Q3/2009 to Q3/2010. As a result, mobile security is no longer immanent, but imperative. This survey paper provides a concise overview of mobile network security, attack vectors using the back end system and the web browser, but also the hardware layer and the user as attack enabler. We show differences and similarities between "normal" security and mobile security, and draw conclusions for further research opportunities in this area.