Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning

Deep Learning has recently become hugely popular in machine learning, providing significant improvements in classification accuracy in the presence of highly-structured and large databases. Researchers have also considered privacy implications of deep learning. Models are typically trained in a centralized manner with all the data being processed by the same training algorithm. If the data is a collection of users' private data, including habits, personal pictures, geographical positions, interests, and more, the centralized server will have access to sensitive information that could potentially be mishandled. To tackle this problem, collaborative deep learning models have recently been proposed where parties locally train their deep learning structures and only share a subset of the parameters in the attempt to keep their respective training sets private. Parameters can also be obfuscated via differential privacy (DP) to make information extraction even more challenging, as proposed by Shokri and Shmatikov at CCS'15. Unfortunately, we show that any privacy-preserving collaborative deep learning is susceptible to a powerful attack that we devise in this paper. In particular, we show that a distributed, federated, or decentralized deep learning approach is fundamentally broken and does not protect the training sets of honest participants. The attack we developed exploits the real-time nature of the learning process that allows the adversary to train a Generative Adversarial Network (GAN) that generates prototypical samples of the targeted training set that was meant to be private (the samples generated by the GAN are intended to come from the same distribution as the training data). Interestingly, we show that record-level DP applied to the shared parameters of the model, as suggested in previous work, is ineffective (i.e., record-level DP is not designed to address our attack).Comment: ACM CCS'17, 16 pages, 18 figure

No Place to Hide that Bytes won't Reveal: Sniffing Location-Based Encrypted Traffic to Track a User's Position

News reports of the last few years indicated that several intelligence agencies are able to monitor large networks or entire portions of the Internet backbone. Such a powerful adversary has only recently been considered by the academic literature. In this paper, we propose a new adversary model for Location Based Services (LBSs). The model takes into account an unauthorized third party, different from the LBS provider itself, that wants to infer the location and monitor the movements of a LBS user. We show that such an adversary can extrapolate the position of a target user by just analyzing the size and the timing of the encrypted traffic exchanged between that user and the LBS provider. We performed a thorough analysis of a widely deployed location based app that comes pre-installed with many Android devices: GoogleNow. The results are encouraging and highlight the importance of devising more effective countermeasures against powerful adversaries to preserve the privacy of LBS users.Comment: 14 pages, 9th International Conference on Network and System Security (NSS 2015

The impact of a feed-in tariff on wind power development in Germany

We estimate the impact of a feed-in tariff for renewable power on wind power investment in Germany at the county level from 1996-2010 controlling for windiness and access to the electricity transmission grid. After the Renewable Energy Law (EEG) was passed in 2000, the feed-in tariff became linked to wind power potential, such that more windy locations received a lower incentive per unit of output. We find that a 1 e-cent/kWh increase in the feed-in tariff rate would increase additions to capacity at the national level by 764MWper year from 1996- 2010 or 1,528 MW per year from 2005-2010. We analyze counterfactual scenarios, in which a uniform incentive is offered instead of the wind-dependent EEG incentive. Significantly more wind power plants are installed along the northern coastal counties in the uniform incentive scenario. We find that while the uniform incentive results in greater total wind power output per installed capacity, the EEG is ultimately more efficient by achieving 1% greater wind power output per euro and 3.7% greater reductions in power sector emissions per euro. In addition, we find a significant response from investors to an EEG provision that shifted the cost of transmission system upgrades from wind power developers to grid operators in 2000. The lack of a signal on scarcity of transmission capacity has likely resulted in a distribution of wind power plants that makes suboptimal use of existing infrastructure, necessitating investment in new transmission corridors

THE RELATIONSHIP BETWEEN INCOME, WEALTH, AND LIFE SATISFACTION

This dissertation inquires into the relationship between income, aspirations, and life satisfaction in post-transition Russia. It first explores the channels through which adaptation and social comparison contribute to higher income aspirations. The results show that social comparison is a strong agent in shaping aspirations, while the effect of adaptation is relatively weak. Subsequently, the dissertation tests for the effect of aspirations on two separate satisfaction indices, satisfaction with life and satisfaction with economic conditions. This dissertation uses a Chamberlain random-effects ordered probit estimation to control for time-invariant unobservable individual traits. In contrast to previous studies, the results suggest that increases in aspirations have a positive effect on life satisfaction. This dissertation argues that this is caused by the expectations contained in income aspirations. Higher aspirations reflect an increase in needs commensurate to changes in own and others' income, but they also reflect improved income expectations based on the information provided by the present income of relevant others. The improved outlook embedded in the higher income aspirations causes the latter to have a positive effect on life satisfaction. This suggests that, ten years into the transition process, the reaction patterns of life satisfaction in Russia differ substantially from those in developed countries. While the relationship between life satisfaction and income or institutions has recently received a lot attention, the relationship between life satisfaction and accumulated wealth remains unexplored. This dissertation makes use of the 2008 Gallup World Poll and a novel wealth database compiled by the World Bank to evaluate the effect of wealth, produced capital, and natural resources on life satisfaction. The dissertation finds that both produced capital and natural capital have a positive effect on life satisfaction. The effect of good institutions and informal safety nets is also positive. However, in results that parallel findings from the resource curse literature, this dissertation shows that the positive effect of natural capital is due to diffuse natural resources like cropland, pastureland and forestry. Subsoil asset wealth has no significant effect on life satisfaction. Blood feuds represent a significant challenge to law enforcement, institutional consolidation and economic development due to the violence they generate and the other forms of crime they contribute to. This paper seeks to model and explain the decision making dynamics behind blood feuds. Rather than a simple retaliatory act, the violence associated with blood feuds is very much an integral aspect of an institutional framework that reflects a different set of ecological conditions and preferences. This paper incorporates different cultural and ecological aspects of various societies into a theoretical model that explains how blood feuds are sustained in a society. In addition, the model developed in this paper helps explain the longevity of blood feuds and reconcile different views from the anthropology literature

Wind Power Development in the United States: Effects of Policies and Electricity Transmission Congestion

In this dissertation, I analyze the drivers of wind power development in the United States as well as the relationship between renewable power plant location and transmission congestion and emissions levels. I first examine the role of government renewable energy incentives and access to the electricity grid on investment in wind power plants across counties from 1998-2007. The results indicate that the federal production tax credit, state-level sales tax credit and production incentives play an important role in promoting wind power. In addition, higher wind power penetration levels can be achieved by bringing more parts of the electricity transmission grid under independent system operator regulation. I conclude that state and federal government policies play a significant role in wind power development both by providing financial support and by improving physical and procedural access to the electricity grid. Second, I examine the effect of renewable power plant location on electricity transmission congestion levels and system-wide emissions levels in a theoretical model and a simulation study. A new renewable plant takes the effect of congestion on its own output into account, but ignores the effect of its marginal contribution to congestion on output from existing plants, which results in curtailment of renewable power. Though pricing congestion removes the externality and reduces curtailment, I find that in the absence of a price on emissions, pricing congestion may in some cases actually increase system-wide emissions. The final part of my dissertation deals with an econometric issue that emerged from the empirical analysis of the drivers of wind power. I study the effect of the degree of censoring on random-effects Tobit estimates in finite sample with a particular focus on severe censoring, when the percentage of uncensored observations reaches 1 to 5 percent. The results show that the Tobit model performs well even at 5 percent uncensored observations with the bias in the Tobit estimates remaining at or below 5 percent. Under severe censoring (1 percent uncensored observations), large biases appear in the estimated standard errors and marginal effects. These are generally reduced as the sample size increases in both N and T

ENVIRONMENT PROTECTION UNDER THE ALBANIAN DOMESTIC LEGISLATION

Environment protection is of higher importance in developing countries like Albania. This paper shows how the new Albanian governmental and social bodies have faced this emerging challenge in favor both of the wellbeing and higher standards of environment of proper citizens. The rapid urban development which characterized the Albanian transition from the ’90s till nowadays has increasingly marked environmental standards. In addition, educational campaigns in favor of environmental protection have almost been absent although non-governmental agencies in the field are numerous. The awareness of the Albanian citizens at the beginning of the democratic processes towards issues of environment and sustainable development has been at the lowest ever; only with the improvement of economic standards and better quality of life, this sensibility towards the environment modified the fundamental social interests in favor of sustainable development without renouncing anyway from economic targets. The efforts of the government and the civil society in favor of the creation of a environmental mentality within the Albanian society is one of the clearest effects of the integration process towards the European Union which pays due attention to the environmental issues. The Albanian legislation, in the wake of the European one, tries to set up a complex of rules for the protection of environment under all its aspects. There is still much to do but the master route remains the European one

ENVIRONMENT PROTECTION UNDER THE ALBANIAN DOMESTIC LEGISLATION

Environment protection is of higher importance in developing countries like Albania. This paper shows how the new Albanian governmental and social bodies have faced this emerging challenge in favor both of the wellbeing and higher standards of environment of proper citizens. The rapid urban development which characterized the Albanian transition from the ’90s till nowadays has increasingly marked environmental standards. In addition, educational campaigns in favor of environmental protection have almost been absent although non-governmental agencies in the field are numerous. The awareness of the Albanian citizens at the beginning of the democratic processes towards issues of environment and sustainable development has been at the lowest ever; only with the improvement of economic standards and better quality of life, this sensibility towards the environment modified the fundamental social interests in favor of sustainable development without renouncing anyway from economic targets. The efforts of the government and the civil society in favor of the creation of a environmental mentality within the Albanian society is one of the clearest effects of the integration process towards the European Union which pays due attention to the environmental issues. The Albanian legislation, in the wake of the European one, tries to set up a complex of rules for the protection of environment under all its aspects. There is still much to do but the master route remains the European one

Choosing among different discrete approximations of a continuous random variable

For many complex probabilistic problems involving continuous random variables, it is impossible to find a closed-form solution. Consequently, it is necessary to approximate a given continuous probability distribution with a discrete one. Several techniques are available for producing a discrete approximation to a continuous random variable, based on rather di↵erent criteria. In this work, we will examine and compare these main methods, by considering a well-known parametric distribution. Applications to real problems will finally be suggested