An Approach to Guide Users Towards Less Revealing Internet Browsers

When browsing the Internet, HTTP headers enable both clients and servers send extra data in their requests or responses such as the User-Agent string. This string contains information related to the sender’s device, browser, and operating system. Previous research has shown that there are numerous privacy and security risks result from exposing sensitive information in the User-Agent string. For example, it enables device and browser fingerprinting and user tracking and identification. Our large analysis of thousands of User-Agent strings shows that browsers differ tremendously in the amount of information they include in their User-Agent strings. As such, our work aims at guiding users towards using less exposing browsers. In doing so, we propose to assign an exposure score to browsers based on the information they expose and vulnerability records. Thus, our contribution in this work is as follows: first, provide a full implementation that is ready to be deployed and used by users. Second, conduct a user study to identify the effectiveness and limitations of our proposed approach. Our implementation is based on using more than 52 thousand unique browsers. Our performance and validation analysis show that our solution is accurate and efficient. The source code and data set are publicly available and the solution has been deployed

Extending the Exposure Score of Web Browsers by Incorporating CVSS

When browsing the Internet, HTTP headers enable both clients and servers send extra data in their requests or responses such as the User-Agent string. This string contains information related to the sender’s device, browser, and operating system. Yet its content differs from one browser to another. Despite the privacy and security risks of User-Agent strings, very few works have tackled this problem. Our previous work proposed giving Internet browsers exposure relative scores to aid users to choose less intrusive ones. Thus, the objective of this work is to extend our previous work through: first, conducting a user study to identify its limitations. Second, extending the exposure score via incorporating data from the NVD. Third, providing a full implementation, instead of a limited prototype. The proposed system: assigns scores to users’ browsers upon visiting our website. It also suggests alternative safe browsers, and finally it allows updating the back-end database with a click of a button. We applied our method to a data set of more than 52 thousand unique browsers. Our performance and validation analysis show that our solution is accurate and efficient. The source code and data set are publicly available here [4].</p

دراسة تحليلية لتحديد قيمة معامل تعديل القوى الزلزالية R لجمل إنشائية ثنائية بيتونية قائمة

تأتي أهمية اعتماد معامل تعديل القوى الزلزالية R في عملية التحليل والتصميم الزلزالي من تضمينه لمطاوعة الجملة الإنشائية الناتجة عن سلوك مرن - لدن لمادة الإنشاء، والمقاومة الزائدة المتأصلة لعناصرها والتي يتم التصميم على قيم مقاومة أقل منها، وبالتالي تخفيض قوة القص القاعدية المتولدة عن الحركة الزلزالية. عملت غالبية الأبحاث التي درست المعامل R على إيجاد قيمه وفقاً لتحليل استاتيكي لا خطي، وأظهرت النتائج وجود اختلافات بقيم المعامل R عن ما ورد في الكودات على اختلافها لأنواع مختلفة من الجمل الإنشائية، واستخدمت هذه الأبحاث نماذج مباني افتراضية للدراسة تخدم سهولة الوصول لهدف البحث وغالباً ما يكون الهدف دراسة قيمة المعامل R بتغير أحد العوامل الداخلة في حسابه. تم في هذه الدراسة تحديد قيم معامل السلوك اللامرن R  لمباني بيتونية قائمة مقاومة لزلازل بجمل إنشائية ثنائية بالعلاقة بين صلابة أعمدة الإطارات إلى صلابة جدران القص لهذه الجمل بالاتجاه المدروس، باستخدام التحليل الستاتيكي اللاخطي   Liner Static Analysis ) NLSA  (Non ، ومقارنة النتائج مع قيم المعامل R المعطاة في الجداول المبسطة للكود العربي السوري  وملحقه الثاني لعام 2013، وتوصلنا في دراستنا إلى وجود تبايناً كبيراً بين القيم الناتجة للمعامل R والقيم المعطاة في الكود العربي السوري إضافةً إلى زيادة قيمه بازدياد كل من الدور الأساسي ونسبة صلابة الأعمدة الإطارية إلى صلابة جدران القص لهذه الجمل

Preparation and characterization of carvedilol-loaded poly(d,l) lactide nanoparticles/microparticles as a sustained-release system

<p>Carvedilol poly(d,l)-lactide nanoparticles/microparticles were prepared. The size and morphology of the developed particles were optimized to study the carvedilol release profile by studying the effect of organic solvents and polymer amount through atomic force microscopy analysis. Spherical particles were obtained with a minimum size of 125 nm in the case of acetone and a maximum size of 970 nm in the case of dichloromethane affording microparticles formation. The interaction was confirmed by differential scanning calorimeter and Fourier transform infrared. The <i>in vitro</i> release profile of the multicompartment system (pure carvedilol, loaded nanoparticles and microparticles) has shown a sustained release with Korsmeyer–Peppas with T lag model.</p

Extending the Exposure Score of Web Browsers by Incorporating CVSS

When browsing the Internet, HTTP headers enable both clients and servers send extra data in their requests or responses such as the User-Agent string. This string contains information related to the sender’s device, browser, and operating system. Yet its content differs from one browser to another. Despite the privacy and security risks of User-Agent strings, very few works have tackled this problem. Our previous work proposed giving Internet browsers exposure relative scores to aid users to choose less intrusive ones. Thus, the objective of this work is to extend our previous work through: first, conducting a user study to identify its limitations. Second, extending the exposure score via incorporating data from the NVD. Third, providing a full implementation, instead of a limited prototype. The proposed system: assigns scores to users’ browsers upon visiting our website. It also suggests alternative safe browsers, and finally it allows updating the back-end database with a click of a button. We applied our method to a data set of more than 52 thousand unique browsers. Our performance and validation analysis show that our solution is accurate and efficient. The source code and data set are publicly available here [4]