Internet Predictions

More than a dozen leading experts give their opinions on where the Internet is headed and where it will be in the next decade in terms of technology, policy, and applications. They cover topics ranging from the Internet of Things to climate change to the digital storage of the future. A summary of the articles is available in the Web extras section

After the Bubble: The Survival and Ownership of Internet Marketplaces for Farmers and Agribusiness

This paper presents a theory of how industry structure and beliefs about Internet marketplace use have driven choice and ownership of marketplaces. The theory's predictions suggest that surviving Internet marketplaces will be those with strong historical linkages in an industry and those owned by or affiliated with major commodity buyers. Comparisons of these predictions with actual outcomes provide validation of the theory. Where predictions differ from results, observations are made as to the nature of the deviations.agricultural markets, electronic commerce, Internet markets, network externalities, technology adoption, Agribusiness,

2010 may not have marked the first ‘internet election’, but digital platforms are of ever increasing importance in political campaigning

Predictions that an upcoming national election will be ‘the’ internet election have been circulating in the UK and other advanced democracies since the late 1990s. Rachel Gibson and Marta Cantijoch study the UK’s general election in 2010 and find that while ecampaigning still lagged behind traditional media and mobilisation tools, there is reason to believe the internet will play a much larger role in the 2015 election and politics more generally

Google Econometrics and Unemployment Forecasting

The current economic crisis requires fast information to predict economic behavior early, which is difficult at times of structural changes. This paper suggests an innovative new method of using data on internet activity for that purpose. It demonstrates strong correlations between keyword searches and unemployment rates using monthly German data and exhibits a strong potential for the method used.time-series analysis, internet, Google, keyword search, search engine, unemployment, predictions

Google Econometrics and Unemployment Forecasting

The current economic crisis requires fast information to predict economic behavior early, which is difficult at times of structural changes. This paper suggests an innovative new method of using data on internet activity for that purpose. It demonstrates strong correlations between keyword searches and unemployment rates using monthly German data and exhibits a strong potential for the method used.Google, internet, keyword search, search engine, unemployment, predictions, time-series analysis

Passport: enabling accurate country-level router geolocation using inaccurate sources

When does Internet traffic cross international borders? This question has major geopolitical, legal and social implications and is surprisingly difficult to answer. A critical stumbling block is a dearth of tools that accurately map routers traversed by Internet traffic to the countries in which they are located. This paper presents Passport: a new approach for efficient, accurate country-level router geolocation and a system that implements it. Passport provides location predictions with limited active measurements, using machine learning to combine information from IP geolocation databases, router hostnames, whois records, and ping measurements. We show that Passport substantially outperforms existing techniques, and identify cases where paths traverse countries with implications for security, privacy, and performance.First author draf

Passport: Enabling Accurate Country-Level Router Geolocation using Inaccurate Sources

When does Internet traffic cross international borders? This question has major geopolitical, legal and social implications and is surprisingly difficult to answer. A critical stumbling block is a dearth of tools that accurately map routers traversed by Internet traffic to the countries in which they are located. This paper presents Passport: a new approach for efficient, accurate country-level router geolocation and a system that implements it. Passport provides location predictions with limited active measurements, using machine learning to combine information from IP geolocation databases, router hostnames, whois records, and ping measurements. We show that Passport substantially outperforms existing techniques, and identify cases where paths traverse countries with implications for security, privacy, and performance

Defending Tor from Network Adversaries: A Case Study of Network Path Prediction

The Tor anonymity network has been shown vulnerable to traffic analysis attacks by autonomous systems and Internet exchanges, which can observe different overlay hops belonging to the same circuit. We aim to determine whether network path prediction techniques provide an accurate picture of the threat from such adversaries, and whether they can be used to avoid this threat. We perform a measurement study by running traceroutes from Tor relays to destinations around the Internet. We use the data to evaluate the accuracy of the autonomous systems and Internet exchanges that are predicted to appear on the path using state-of-the-art path inference techniques; we also consider the impact that prediction errors have on Tor security, and whether it is possible to produce a useful overestimate that does not miss important threats. Finally, we evaluate the possibility of using these predictions to actively avoid AS and IX adversaries and the challenges this creates for the design of Tor