66 research outputs found
Web Tracking: Mechanisms, Implications, and Defenses
This articles surveys the existing literature on the methods currently used
by web services to track the user online as well as their purposes,
implications, and possible user's defenses. A significant majority of reviewed
articles and web resources are from years 2012-2014. Privacy seems to be the
Achilles' heel of today's web. Web services make continuous efforts to obtain
as much information as they can about the things we search, the sites we visit,
the people with who we contact, and the products we buy. Tracking is usually
performed for commercial purposes. We present 5 main groups of methods used for
user tracking, which are based on sessions, client storage, client cache,
fingerprinting, or yet other approaches. A special focus is placed on
mechanisms that use web caches, operational caches, and fingerprinting, as they
are usually very rich in terms of using various creative methodologies. We also
show how the users can be identified on the web and associated with their real
names, e-mail addresses, phone numbers, or even street addresses. We show why
tracking is being used and its possible implications for the users (price
discrimination, assessing financial credibility, determining insurance
coverage, government surveillance, and identity theft). For each of the
tracking methods, we present possible defenses. Apart from describing the
methods and tools used for keeping the personal data away from being tracked,
we also present several tools that were used for research purposes - their main
goal is to discover how and by which entity the users are being tracked on
their desktop computers or smartphones, provide this information to the users,
and visualize it in an accessible and easy to follow way. Finally, we present
the currently proposed future approaches to track the user and show that they
can potentially pose significant threats to the users' privacy.Comment: 29 pages, 212 reference
JShelter: Give Me My Browser Back
The Web is used daily by billions. Even so, users are not protected from many
threats by default. This position paper builds on previous web privacy and
security research and introduces JShelter, a webextension that fights to return
the browser to users. Moreover, we introduce a library helping with common
webextension development tasks and fixing loopholes misused by previous
research. JShelter focuses on fingerprinting prevention, limitations of rich
web APIs, prevention of attacks connected to timing, and learning information
about the computer, the browser, the user, and surrounding physical environment
and location. We discovered a loophole in the sensor timestamps that lets any
page observe the device boot time if sensor APIs are enabled in Chromium-based
browsers. JShelter provides a fingerprinting report and other feedback that can
be used by future security research and data protection authorities. Thousands
of users around the world use the webextension every day
XSS Vulnerabilities in Cloud-Application Add-Ons
Cloud-application add-ons are microservices that extend the functionality of
the core applications. Many application vendors have opened their APIs for
third-party developers and created marketplaces for add-ons (also add-ins or
apps). This is a relatively new phenomenon, and its effects on the application
security have not been widely studied. It seems likely that some of the add-ons
have lower code quality than the core applications themselves and, thus, may
bring in security vulnerabilities. We found that many such add-ons are
vulnerable to cross-site scripting (XSS). The attacker can take advantage of
the document-sharing and messaging features of the cloud applications to send
malicious input to them. The vulnerable add-ons then execute client-side
JavaScript from the carefully crafted malicious input. In a major analysis
effort, we systematically studied 300 add-ons for three popular application
suites, namely Microsoft Office Online, G Suite and Shopify, and discovered a
significant percentage of vulnerable add-ons in each marketplace. We present
the results of this study, as well as analyze the add-on architectures to
understand how the XSS vulnerabilities can be exploited and how the threat can
be mitigated
Computational Resource Abuse in Web Applications
Internet browsers include Application Programming Interfaces (APIs) to support Web applications that require complex functionality, e.g., to let end users watch videos, make phone calls, and play video games. Meanwhile, many Web applications employ the browser APIs to rely on the user's hardware to execute intensive computation, access the Graphics Processing Unit (GPU), use persistent storage, and establish network connections.
However, providing access to the system's computational resources, i.e., processing, storage, and networking, through the browser creates an opportunity for attackers to abuse resources. Principally, the problem occurs when an attacker compromises a Web site and includes malicious code to abuse its visitor's computational resources. For example, an attacker can abuse the user's system networking capabilities to perform a Denial of Service (DoS) attack against third parties. What is more, computational resource abuse has not received widespread attention from the Web security community because most of the current specifications are focused on content and session properties such as isolation, confidentiality, and integrity.
Our primary goal is to study computational resource abuse and to advance the state of the art by providing a general attacker model, multiple case studies, a thorough analysis of available security mechanisms, and a new detection mechanism. To this end, we implemented and evaluated three scenarios where attackers use multiple browser APIs to abuse networking, local storage, and computation. Further, depending on the scenario, an attacker can use browsers to perform Denial of Service against third-party Web sites, create a network of browsers to store and distribute arbitrary data, or use browsers to establish anonymous connections similarly to The Onion Router (Tor). Our analysis also includes a real-life resource abuse case found in the wild, i.e., CryptoJacking, where thousands of Web sites forced their visitors to perform crypto-currency mining without their consent. In the general case, attacks presented in this thesis share the attacker model and two key characteristics: 1) the browser's end user remains oblivious to the attack, and 2) an attacker has to invest little resources in comparison to the resources he obtains.
In addition to the attack's analysis, we present how existing, and upcoming, security enforcement mechanisms from Web security can hinder an attacker and their drawbacks. Moreover, we propose a novel detection approach based on browser API usage patterns. Finally, we evaluate the accuracy of our detection model, after training it with the real-life crypto-mining scenario, through a large scale analysis of the most popular Web sites
The Proceedings of 15th Australian Information Security Management Conference, 5-6 December, 2017, Edith Cowan University, Perth, Australia
Conference Foreword
The annual Security Congress, run by the Security Research Institute at Edith Cowan University, includes the Australian Information Security and Management Conference. Now in its fifteenth year, the conference remains popular for its diverse content and mixture of technical research and discussion papers. The area of information security and management continues to be varied, as is reflected by the wide variety of subject matter covered by the papers this year. The papers cover topics from vulnerabilities in “Internet of Things” protocols through to improvements in biometric identification algorithms and surveillance camera weaknesses. The conference has drawn interest and papers from within Australia and internationally. All submitted papers were subject to a double blind peer review process. Twenty two papers were submitted from Australia and overseas, of which eighteen were accepted for final presentation and publication. We wish to thank the reviewers for kindly volunteering their time and expertise in support of this event. We would also like to thank the conference committee who have organised yet another successful congress. Events such as this are impossible without the tireless efforts of such people in reviewing and editing the conference papers, and assisting with the planning, organisation and execution of the conference. To our sponsors, also a vote of thanks for both the financial and moral support provided to the conference. Finally, thank you to the administrative and technical staff, and students of the ECU Security Research Institute for their contributions to the running of the conference
UNCOVERING AND MITIGATING UNSAFE PROGRAM INTEGRATIONS IN ANDROID
Android’s design philosophy encourages the integration of resources and functionalities from multiple parties, even with different levels of trust. Such program integrations, on one hand, connect every party in the Android ecosystem tightly on one single device. On the other hand, they can also pose severe security problems, if the security design of the underlying integration schemes is not well thought-out. This dissertation systematically evaluates the security design of three integration schemes on Android, including framework module, framework proxy and 3rd-party code embedding. With the security risks identified in each scheme, it concludes that program integrations on Android are unsafe. Furthermore, new frameworks have been designed and implemented to detect and mitigate the threats. The evaluation results on the prototypes have demonstrated their effectiveness
Traçage en ligne : démystification et contrôle
It is no surprise, given smartphones convenience and utility, to see their wide adoption worldwide. Smartphones are naturally gathering a lot of personal information as the user communicates, browses the web and runs various Apps. They are equipped with GPS, NFC and digital camera facilities and therefore smartphones generate new personal information as they are used. Since they are almost always connected to the Internet, and are barely turned off, they can potentially reveal a lot of information about the activities of their owners. The close arrival of smart-‐watches and smart-‐glasses will just increase the amount of personal information available and the privacy leakage risks. This subject is closely related to the Mobilitics project that is currently conducted by Inria/Privatics and CNIL, the French data protection authority [1][2][3]. Therefore, the candidate will benefit from the investigations that are on progress in this context, in order to understand the situation and the trends. The candidate will also benefit from all the logging and analysis tools we developed for the iOS and Android Mobile OSes, as well as the experienced gained on the subject. Another question is the arrival of HTML5 based Mobile OSes, like Firefox OS: it clearly opens new directions as it "uses completely open standards and there’s no proprietary software or technology involved" (Andreas Gal, Mozilla). But what are the implications from a Mobile OS privacy point of view? That's an important topic to analyze. Beyond understanding the situation, the candidate will also explore several directions in order to improve the privacy control of mobile devices. First of all, a privacy-‐by-‐design approach, when feasible, is an excellent way to tackle the problem. For instance the current trend is to rely more and more on cloud-‐based services, either directly (e.g., via Dropbox, Instagram, Social Networks, or similar services), or indirectly (e.g., when a backup of the contact, calendar, accounts databases is needed). But pushing data on cloud-‐based systems, somewhere on the Internet, is in total contradiction with our privacy considerations. Therefore, an idea is to analyze and experiment with personal cloud services (e.g., ownCLoud, diaspora) that are fully managed by the user. Here the goal is to understand the possibilities, the opportunities, and the usability of such systems, either as a replacement or in association with commercial cloud services. Another direction is to carry out behavioral analyses. Indeed, in order to precisely control the privacy aspects, at one extreme, the user may have to deeply interact with the device (e.g., through pop-ups each time a potential privacy leak is identified), which negatively impacts the usability of the device. At the other extreme, the privacy control may be oversimplified, in the hope not to interfere too much with the user, as is the case with the Android static authorizations or the one-‐time pop-‐ups of iOS6. This is not appropriate either, since using private information once is not comparable to using it every minute. A better approach could be to perform, with the help of a machine learning system for instance, a dynamic analysis of the Mobile OS or App behavior from a privacy perspective and to interfere with the user only when it is deemed appropriate. This could enable a good tradeoff between privacy control and usability, with user actions only when meaningful. How far such a behavioral analysis can go and what are the limitations of the approach (e.g., either from a CPU/battery drain perspective, or in front of programming tricks to escape the analysis) are open questions. Tainting techniques applied to Mobile OSes (e.g., Taint-Droid) can be used as a basic bloc to build a behavioral analysis tool, but they have limited accuracy are unable to analyze native code and have poor performances.Il n'est pas surprenant , compte tenu de smartphones commodité et l'utilité, pour voir leur adoption à grande échelle dans le monde entier . Les smartphones sont naturellement rassemblent un grand nombre de renseignements personnels que l'utilisateur communique , navigue sur le Web et fonctionne diverses applications . Ils sont équipés de GPS , NFC et les installations d'appareils photo numériques et les smartphones génèrent donc de nouvelles informations personnelles telles qu'elles sont utilisées . Comme ils sont presque toujours connectés à Internet , et sont à peine éteints, ils peuvent potentiellement révéler beaucoup d'informations sur les activités de leurs propriétaires. L'arrivée à proximité de la puce - montres et intelligents - lunettes va juste augmenter la quantité de renseignements personnels disponibles et les risques de fuite de confidentialité . Ce sujet est étroitement lié au projet Mobilitics qui est actuellement menée par l'Inria / Privatics et CNIL , l'autorité française de protection des données [ 1] [2 ] [3] . Par conséquent , le candidat bénéficiera des enquêtes qui sont en cours dans ce contexte, afin de comprendre la situation et les tendances. Le candidat devra également bénéficier de tous les outils de diagraphie et l'analyse que nous avons développées pour l'iOS et Android OS mobiles , ainsi que l' expérience acquise sur le sujet. Une autre question est l'arrivée de HTML5 base de systèmes d'exploitation mobiles , comme Firefox OS: il ouvre clairement de nouvelles directives qu'elle " utilise des normes ouvertes complètement et il n'y a pas de logiciel propriétaire ou technologie impliquée " ( Andreas Gal, Mozilla) . Mais quelles sont les implications d'un point de vie privée OS mobile de vue? C'est un sujet important à analyser. Au-delà de la compréhension de la situation , le candidat devra aussi explorer plusieurs directions afin d' améliorer le contrôle des appareils mobiles de la vie privée . Tout d'abord, une vie privée - par - approche de conception , lorsque cela est possible , est une excellente façon d'aborder le problème . Par exemple, la tendance actuelle est de plus en plus compter sur un nuage - Services basés , soit directement (par exemple , via Dropbox, Instagram , les réseaux sociaux ou services similaires ) , ou indirectement (par exemple , lorsqu'une sauvegarde du contact , calendrier, bases de données des comptes sont nécessaires ) . Mais en poussant des données sur les nuages - systèmes basés , quelque part sur Internet , est en totale contradiction avec nos considérations de confidentialité. Par conséquent, l'idée est d'analyser et d'expérimenter avec les services de cloud personnel (par exemple , owncloud , diaspora ) qui sont entièrement gérés par l'utilisateur. Ici, le but est de comprendre les possibilités, les opportunités et la facilité d'utilisation de ces systèmes , que ce soit en remplacement ou en association avec les services de cloud commerciales. Une autre direction est d' effectuer des analyses comportementales . En effet, afin de contrôler précisément les aspects de la vie privée , à un extrême , l'utilisateur peut avoir à interagir fortement avec l'appareil (par exemple , par le biais des pop-ups chaque fois une fuite potentielle de la vie privée est identifié ) , qui a un impact négatif sur la facilité d'utilisation de l'appareil . À l'autre extrême , le contrôle de la vie privée peut être simplifiée à l'extrême , dans l'espoir de ne pas trop interférer avec l'utilisateur, comme c'est le cas avec les autorisations statiques Android ou celui - Temps pop - up de iOS6 . Ce n'est pas non plus approprié , puisque l'utilisation de renseignements personnels une fois n'est pas comparable à l'utiliser chaque minute
- …