Threshold FlipThem:when the winner does not need to take all

We examine a FlipIt game in which there are multiple resources which a monolithic attacker is trying to compromise. This extension to FlipIt was considered in a paper in GameSec 2014, and was there called FlipThem. Our analysis of such a situation is focused on the situation where the attacker’s goal is to compromise a threshold of the resources. We use our game theoretic model to enable a defender to choose the correct configuration of resources (number of resources and the threshold) so as to ensure that it makes no sense for a rational adversary to try to attack the system. This selection is made on the basis of the relative costs of the attacker and the defender

DAG-Based Attack and Defense Modeling: Don't Miss the Forest for the Attack Trees

This paper presents the current state of the art on attack and defense modeling approaches that are based on directed acyclic graphs (DAGs). DAGs allow for a hierarchical decomposition of complex scenarios into simple, easily understandable and quantifiable actions. Methods based on threat trees and Bayesian networks are two well-known approaches to security modeling. However there exist more than 30 DAG-based methodologies, each having different features and goals. The objective of this survey is to present a complete overview of graphical attack and defense modeling techniques based on DAGs. This consists of summarizing the existing methodologies, comparing their features and proposing a taxonomy of the described formalisms. This article also supports the selection of an adequate modeling technique depending on user requirements

Collateral damage of Facebook third-party applications: a comprehensive study

Third-party applications on Facebook can collect personal data of the users who install them, but also of their friends. This raises serious privacy issues as these friends are not notified by the applications nor by Facebook and they have not given consent. This paper presents a detailed multi-faceted study on the collateral information collection of the applications on Facebook. To investigate the views of the users, we designed a questionnaire and collected the responses of 114 participants. The results show that participants are concerned about the collateral information collection and in particular about the lack of notification and of mechanisms to control the data collection. Based on real data, we compute the likelihood of collateral information collection affecting users: we show that the probability is significant and greater than 80% for popular applications such as TripAdvisor. We also demonstrate that a substantial amount of profile data can be collected by applications, which enables application providers to profile users. To investigate whether collateral information collection is an issue to users’ privacy we analysed the legal framework in light of the General Data Protection Regulation. We provide a detailed analysis of the entities involved and investigate which entity is accountable for the collateral information collection. To provide countermeasures, we propose a privacy dashboard extension that implements privacy scoring computations to enhance transparency toward collateral information collection. Furthermore, we discuss alternative solutions highlighting other countermeasures such as notification and access control mechanisms, cryptographic solutions and application auditing. To the best of our knowledge this is the first work that provides a detailed multi-faceted study of this problem and that analyses the threat of user profiling by application providers

Rational Sumchecks

Rational proofs, introduced by Azar and Micali (STOC 2012) are a variant of interactive proofs in which the prover is neither honest nor malicious, but rather rational. The advantage of rational proofs over their classical counterparts is that they allow for extremely low communication and verification time. In recent work, Guo et al. (ITCS 2014) demonstrated their relevance to delegation of computation by showing that, if the rational prover is additionally restricted to being computationally bounded, then every language in NC1 admits a single-round delegation scheme that can be verified in sublinear time. We extend the Guo et al. result by constructing a single-round delegation scheme with sublinear verification for all languages in P. Our main contribution is the introduction of {\em rational sumcheck protocols}, which are a relaxation of classical sumchecks, a crucial building block for interactive proofs. Unlike their classical counterparts, rational sumchecks retain their (rational) soundness properties, {\em even if the polynomial being verified is of high degree} (in particular, they do not rely on the Schwartz-Zippel lemma). This enables us to bypass the main efficiency bottleneck in classical delegation schemes, which is a result of sumcheck protocols being inapplicable to the verification of the computation\u27s input level. As an additional contribution we study the possibility of using rational proofs as efficient blocks within classical interactive proofs. Specifically, we show a composition theorem for substituting oracle calls in an interactive proof by a rational protocol

Analysis and Design of Privacy-Enhancing Information Sharing Systems

Recent technological advancements have enabled the collection of large amounts of personal data of individuals at an ever-increasing rate. Service providers, organisations and governments can collect or otherwise acquire rich information about individuals’ everyday lives and habits from big data-silos, enabling profiling and micro-targeting such as in political elections. Therefore, it is important to analyse systems that allow the collection and information sharing between users and to design secure and privacy enhancing solutions. This thesis contains two parts. The aim of the first part is to investigate in detail the effects of the collateral information collection of third-party applications on Facebook. The aim of the second part is to analyse in detail the security and privacy issues of car sharing systems and to design a secure and privacy-preserving solution. In the first part, we present a detailed multi-faceted study on the collateral information collection privacy issues of Facebook applications; providers of third-party applications on Facebook exploit the interdependency between users and their friends. The goal is to (i) study the existence of the problem, (ii) investigate whether Facebook users are concerned about the issue, quantify its (iii) likelihood and (iv) impact of collateral information collection affecting users, (v) identify whether collateral information collection is an issue for the protection of the personal data of Facebook users under the legal framework, and (vi) we propose solutions that aim to solve the problem of collateral information collection. In order to investigate the views of the users, we designed a questionnaire and collected the responses of participants. Employing real data from the Facebook third-party applications ecosystem, we compute the likelihood of collateral information collection affecting users and quantify its significance evaluating the amount of attributes collected by such applications. To investigate whether collateral information collection is an issue in terms of users’ privacy we analysed the legal framework in light of the General Data Protection Regulation. To provide countermeasures, we propose a privacy dashboard extension that implements privacy scoring computations to enhance transparency towards collateral information collection