Researchers have studied Internet censorship for nearly as long as attempts to censor contents have taken place. Most studies have however been limited to a short period of time and/or a few countries; the few exceptions have traded off detail for breadth of coverage. Collecting enough data for a comprehensive, global, longitudinal perspective remains challenging. In this work, we present ICLab, an Internet measurement platform specialized for censorship research. It achieves a new balance between breadth of coverage and detail of measurements, by using commercial VPNs as vantage points distributed around the world. ICLab has been operated continuously since late 2016. It can currently detect DNS manipulation and TCP packet injection, and overt "block pages" however they are delivered. ICLab records and archives raw observations in detail, making retrospective analysis with new techniques possible. At every stage of processing, ICLab seeks to minimize false positives and manual validation. Within 53,906,532 measurements of individual web pages, collected by ICLab in 2017 and 2018, we observe blocking of 3,602 unique URLs in 60 countries. Using this data, we compare how different blocking techniques are deployed in different regions and/or against different types of content. Our longitudinal monitoring pinpoints changes in censorship in India and Turkey concurrent with political shifts, and our clustering techniques discover 48 previously unknown block pages. ICLab's broad and detailed measurements also expose other forms of network interference, such as surveillance and malware injection.
Vehicle-to-grid (V2G) is one of the future key technologies for the smart grid. Electric vehicles (EV) are potential power consumers that can play a crucial role by delivering the power back to the grid in order to meet the power demand. However, the V2G network has some crucial security and privacy challenges. Also the existing solutions generate a huge overhead cost and do not provide resistance against well known security attacks. In order to address the identified security and privacy challenges in the V2G smart grid network. We propose a scheme based on bilinear pairing technique with an accumulator that provides mutual authentication, and privacy preservation of EV's information such as identity, battery status, location, and charging/discharging selection and time duration. The proposed scheme defeats various security attacks, including man-in-the-middle attack, replay attack, impersonation attack, redirection attack, and repudiation attack while generating lower communication and computation overhead than existing privacypreserving V 2G mutual authentication schemes.
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