X-Secure:protecting users from big bad wolves

In 2014 over 70% of people in Great Britain accessed the Internet every day. This resource is an optimal vector for malicious attackers to penetrate home computers and as such compromised pages have been increasing in both number and complexity. This paper presents X-Secure, a novel browser plug-in designed to present and raise the awareness of inexperienced users by analysing web-pages before malicious scripts are executed by the host computer. X-Secure was able to detect over 90% of the tested attacks and provides a danger level based on cumulative analysis of the source code, the URL, and the remote server, by using a set of heuristics, hence increasing the situational awareness of users browsing the internet

Web Security Detection Tool

According to Government Computer News (GCN) web attacks have been marked as all- time high this year. GCN says that some of the leading security software like SOPHOS detected about 15,000 newly infected web pages daily in initial three months of 2008 [13]. This has lead to the need of efficient software to make web applications robust and sustainable to these attacks. While finding information on different types of attacks, I found that SQL injection and cross site scripting are the most famous among attackers. These attacks are used extensively since, they can be performed using different techniques and it is difficult to make a web application completely immune to these attacks. There are myriad detection tools available which help to detect vulnerabilities in web applications. These tools are mainly categorized as white-box and black-box testing tools. In this writing project, we aim to develop a detection tool which would be efficient and helpful for the users to pinpoint possible vulnerabilities in his/her PHP scripts. We propose a technique to integrate the aforementioned categories of tools under one framework to achieve better detection against possible vulnerabilities. Our system focuses on giving the developer a simple and concise tool which would help him/her to correct possible loopholes in the PHP code snippets

Automated Website Fingerprinting through Deep Learning

Several studies have shown that the network traffic that is generated by a visit to a website over Tor reveals information specific to the website through the timing and sizes of network packets. By capturing traffic traces between users and their Tor entry guard, a network eavesdropper can leverage this meta-data to reveal which website Tor users are visiting. The success of such attacks heavily depends on the particular set of traffic features that are used to construct the fingerprint. Typically, these features are manually engineered and, as such, any change introduced to the Tor network can render these carefully constructed features ineffective. In this paper, we show that an adversary can automate the feature engineering process, and thus automatically deanonymize Tor traffic by applying our novel method based on deep learning. We collect a dataset comprised of more than three million network traces, which is the largest dataset of web traffic ever used for website fingerprinting, and find that the performance achieved by our deep learning approaches is comparable to known methods which include various research efforts spanning over multiple years. The obtained success rate exceeds 96% for a closed world of 100 websites and 94% for our biggest closed world of 900 classes. In our open world evaluation, the most performant deep learning model is 2% more accurate than the state-of-the-art attack. Furthermore, we show that the implicit features automatically learned by our approach are far more resilient to dynamic changes of web content over time. We conclude that the ability to automatically construct the most relevant traffic features and perform accurate traffic recognition makes our deep learning based approach an efficient, flexible and robust technique for website fingerprinting.Comment: To appear in the 25th Symposium on Network and Distributed System Security (NDSS 2018

Escrow: A large-scale web vulnerability assessment tool

The reliance on Web applications has increased rapidly over the years. At the same time, the quantity and impact of application security vulnerabilities have grown as well. Amongst these vulnerabilities, SQL Injection has been classified as the most common, dangerous and prevalent web application flaw. In this paper, we propose Escrow, a large-scale SQL Injection detection tool with an exploitation module that is light-weight, fast and platform-independent. Escrow uses a custom search implementation together with a static code analysis module to find potential target web applications. Additionally, it provides a simple to use graphical user interface (GUI) to navigate through a vulnerable remote database. Escrow is implementation-agnostic, i.e. It can perform analysis on any web application regardless of the server-side implementation (PHP, ASP, etc.). Using our tool, we discovered that it is indeed possible to identify and exploit at least 100 databases per 100 minutes, without prior knowledge of their underlying implementation. We observed that for each query sent, we can scan and detect dozens of vulnerable web applications in a short space of time, while providing a means for exploitation. Finally, we provide recommendations for developers to defend against SQL injection and emphasise the need for proactive assessment and defensive coding practices

Web Vulnerability Study of Online Pharmacy Sites

Consumers are increasingly using online pharmacies, but these sites may not provide an adequate level of security with the consumers’ personal data. There is a gap in this research addressing the problems of security vulnerabilities in this industry. The objective is to identify the level of web application security vulnerabilities in online pharmacies and the common types of flaws, thus expanding on prior studies. Technical, managerial and legal recommendations on how to mitigate security issues are presented. The proposed four-step method first consists of choosing an online testing tool. The next steps involve choosing a list of 60 online pharmacy sites to test, and then running the software analysis to compile a list of flaws. Finally, an in-depth analysis is performed on the types of web application vulnerabilities. The majority of sites had serious vulnerabilities, with the majority of flaws being cross-site scripting or old versions of software that have not been updated. A method is proposed for the securing of web pharmacy sites, using a multi-phased approach of technical and managerial techniques together with a thorough understanding of national legal requirements for securing systems

Privacy protocols

Security protocols enable secure communication over insecure channels. Privacy protocols enable private interactions over secure channels. Security protocols set up secure channels using cryptographic primitives. Privacy protocols set up private channels using secure channels. But just like some security protocols can be broken without breaking the underlying cryptography, some privacy protocols can be broken without breaking the underlying security. Such privacy attacks have been used to leverage e-commerce against targeted advertising from the outset; but their depth and scope became apparent only with the overwhelming advent of influence campaigns in politics. The blurred boundaries between privacy protocols and privacy attacks present a new challenge for protocol analysis. Covert channels turn out to be concealed not only below overt channels, but also above: subversions, and the level-below attacks are supplemented by sublimations and the level-above attacks.Comment: 38 pages, 6 figure