Leveraging NLP and Social Network Analytic Techniques to Detect Censored Keywords: System Design and Experiments

Internet regulation in the form of online censorship and Internet shutdowns have been increasing over recent years. This paper presents a natural language processing (NLP) application for performing cross country probing that conceals the exact location of the originating request. A detailed discussion of the application aims to stimulate further investigation into new methods for measuring and quantifying Internet censorship practices around the world. In addition, results from two experiments involving search engine queries of banned keywords demonstrates censorship practices vary across different search engines. These results suggest opportunities for developing circumvention technologies that enable open and free access to information

cOOKie, a Tool for Developing RF Communication Systems for the Internet of Things

There is a need for high-efficiency short-range wireless communications to connect IoT devices that have low to medium security requirements. A hardware/software tool was developed to help IoT product developers quickly and easily develop radio frequency (RF) communication systems for IoT devices where previously this was a manual, one-off process. The tool uses Software Defined Radio (SDR) and focuses on On-Off-Keying (OOK) modulation. It can be used by persons with limited knowledge of RF to analyze existing devices and capture its characteristics, which can be used to create and transmit new messages, in effect spoofing it. New device definitions can be implemented in low-cost off-the-shelf hardware for production. OOK has been found to be very efficient at binary RF communications because the transmitter is only powered when a “1” is being transmitted. This efficiency translates into a battery life of up to one year. Implementations of this system could include arrays of sensors that periodically transmit data to a traditionally-powered Internet-connected receiver. Another possible use of this system could be low-cost small transmitters to track animal movements in a defined area. Receivers placed around the area could record the time and signal strength of the transmissions. Software would be used to analyze the data and plot the animal’s movements. Because the RF transmissions have a specific range, the opportunity to intercept, modify or spoof communications is highly variable. For sensitive data, rolling codes and/or public/private key encryption could be used for encoding before modulating with OOK

Linguistic Characteristics of Censorable Language on SinaWeibo

This paper investigates censorship from a linguistic perspective. We collect a corpus of censored and uncensored posts on a number of topics, build a classifier that predicts censorship decisions independent of discussion topics. Our investigation reveals that the strongest linguistic indicator of censored content of our corpus is its readability

Detecting Censorable Content on Sina Weibo: A Pilot Study

This study provides preliminary insights into the linguistic features that contribute to Internet censorship in mainland China. We collected a corpus of 344 censored and uncensored microblog posts that were published on Sina Weibo and built a Naive Bayes classifier based on the linguistic, topic-independent, features. The classifier achieves a 79.34% accuracy in predicting whether a blog post would be censored on Sina Weibo

Internet Censorship and Economic Impacts: A case study of Internet outages in India

The objective of this research paper is to provide a methodology for measuring the financial impacts of Internet outages. The financial impacts are measured against a Nation’s Gross Domestic Product (GDP) for several states in India to project the aftermath of Internet outage episodes. In addition historical trends are analyzed to help derive predictive logic for Internet outages in order to forecast Internet shutdown incidents based on antecedent events. Results demonstrate the proposed method for determining economic loss highlights several factors and may at times be influenced by the frequency of events compared to overall size of GDP. In addition, historical trend analysis of Internet outages suggests that a predictive model to forecast future outages can help reveal underlying policies toward Internet censorship

Fighting the COVID-19 Infodemic with a Holistic BERT Ensemble

This paper describes the TOKOFOU system, an ensemble model for misinformation detection tasks based on six different transformer-based pre-trained encoders, implemented in the context of the COVID-19 Infodemic Shared Task for English. We fine tune each model on each of the task's questions and aggregate their prediction scores using a majority voting approach. TOKOFOU obtains an overall F1 score of 89.7%, ranking first