Anonymous Single-Round Server-Aided Verification

Server-Aided Verification (SAV) is a method that can be employed to speed up the process of verifying signatures by letting the verifier outsource part of its computation load to a third party. Achieving fast and reliable verification under the presence of an untrusted server is an attractive goal in cloud computing and internet of things scenarios. In this paper, we describe a simple framework for SAV where the interaction between a verifier and an untrusted server happens via a single-round protocol. We propose a security model for SAV that refines existing ones and includes the new notions of SAV-anonymity and extended unforgeability. In addition, we apply our definitional framework to provide the first generic transformation from any signature scheme to a single-round SAV scheme that incorporates verifiable computation. Our compiler identifies two independent ways to achieve SAV-anonymity: computationally, through the privacy of the verifiable computation scheme, or unconditionally, through the adaptibility of the signature scheme. Finally, we define three novel instantiations of SAV schemes obtained through our compiler. Compared to previous works, our proposals are the only ones which simultaneously achieve existential unforgeability and soundness against collusion

Denial-of-Service Resistance in Key Establishment

Denial of Service (DoS) attacks are an increasing problem for network connected systems. Key establishment protocols are applications that are particularly vulnerable to DoS attack as they are typically required to perform computationally expensive cryptographic operations in order to authenticate the protocol initiator and to generate the cryptographic keying material that will subsequently be used to secure the communications between initiator and responder. The goal of DoS resistance in key establishment protocols is to ensure that attackers cannot prevent a legitimate initiator and responder deriving cryptographic keys without expending resources beyond a responder-determined threshold. In this work we review the strategies and techniques used to improve resistance to DoS attacks. Three key establishment protocols implementing DoS resistance techniques are critically reviewed and the impact of misapplication of the techniques on DoS resistance is discussed. Recommendations on effectively applying resistance techniques to key establishment protocols are made

Shortest Path Computation with No Information Leakage

Shortest path computation is one of the most common queries in location-based services (LBSs). Although particularly useful, such queries raise serious privacy concerns. Exposing to a (potentially untrusted) LBS the client's position and her destination may reveal personal information, such as social habits, health condition, shopping preferences, lifestyle choices, etc. The only existing method for privacy-preserving shortest path computation follows the obfuscation paradigm; it prevents the LBS from inferring the source and destination of the query with a probability higher than a threshold. This implies, however, that the LBS still deduces some information (albeit not exact) about the client's location and her destination. In this paper we aim at strong privacy, where the adversary learns nothing about the shortest path query. We achieve this via established private information retrieval techniques, which we treat as black-box building blocks. Experiments on real, large-scale road networks assess the practicality of our schemes.Comment: VLDB201

Authentication under Constraints

Authentication has become a critical step to gain access to services such as on-line banking, e-commerce, transport systems and cars (contact-less keys). In several cases, however, the authentication process has to be performed under challenging conditions. This thesis is essentially a compendium of five papers which are the result of a two-year study on authentication in constrained settings. The two major constraints considered in this work are: (1) the noise and (2) the computational power. For what concerns authentication under noisy conditions, Paper A and Paper B ad- dress the case in which the noise is in the authentication credentials. More precisely, the aforementioned papers present attacks against biometric authentication systems, that exploit the inherent variant nature of biometric traits to gain information that should not be leaked by the system. Paper C and Paper D study proximity- based authentication, i.e., distance-bounding protocols. In this case, both of the constraints are present: the possible presence of noise in the channel (which affects communication and thus the authentication process), as well as resource constraints on the computational power and the storage space of the authenticating party (called the prover, e.g., an RFID tag). Finally, Paper E investigates how to achieve reliable verification of the authenticity of a digital signature, when the verifying party has limited computational power, and thus offloads part of the computations to an untrusted server. Throughout the presented research work, a special emphasis is given to privacy concerns risen by the constrained conditions

Formal Analysis and Redesign of a Neural Network-Based Aircraft Taxiing System with VerifAI

We demonstrate a unified approach to rigorous design of safety-critical autonomous systems using the VerifAI toolkit for formal analysis of AI-based systems. VerifAI provides an integrated toolchain for tasks spanning the design process, including modeling, falsification, debugging, and ML component retraining. We evaluate all of these applications in an industrial case study on an experimental autonomous aircraft taxiing system developed by Boeing, which uses a neural network to track the centerline of a runway. We define runway scenarios using the Scenic probabilistic programming language, and use them to drive tests in the X-Plane flight simulator. We first perform falsification, automatically finding environment conditions causing the system to violate its specification by deviating significantly from the centerline (or even leaving the runway entirely). Next, we use counterexample analysis to identify distinct failure cases, and confirm their root causes with specialized testing. Finally, we use the results of falsification and debugging to retrain the network, eliminating several failure cases and improving the overall performance of the closed-loop system.Comment: Full version of a CAV 2020 pape

Counterexample Generation in Probabilistic Model Checking

Providing evidence for the refutation of a property is an essential, if not the most important, feature of model checking. This paper considers algorithms for counterexample generation for probabilistic CTL formulae in discrete-time Markov chains. Finding the strongest evidence (i.e., the most probable path) violating a (bounded) until-formula is shown to be reducible to a single-source (hop-constrained) shortest path problem. Counterexamples of smallest size that deviate most from the required probability bound can be obtained by applying (small amendments to) k-shortest (hop-constrained) paths algorithms. These results can be extended to Markov chains with rewards, to LTL model checking, and are useful for Markov decision processes. Experimental results show that typically the size of a counterexample is excessive. To obtain much more compact representations, we present a simple algorithm to generate (minimal) regular expressions that can act as counterexamples. The feasibility of our approach is illustrated by means of two communication protocols: leader election in an anonymous ring network and the Crowds protocol

Insider threats for auctions: formalization, mechanized proof, and code generation

This paper applies machine assisted formal methods to explore insider threats for auctions. Auction systems, like eBay, are an important problem domain for formal analysis because they challenge modelling concepts as well as analysis methods. We use machine assisted formal modelling and proof in Isabelle to demonstrate how security and privacy goals of auction protocols can be formally verified. Applying the costly scrutiny of formal methods is justified for auctions since privacy and trust are prominent issues and auctions are sometimes designed for one-off occasions where high bids are at stake. For example, when radio wave frequencies are on sale, auctions are especially created for just one occasion where fair and consistent behaviour is required. Investigating the threats in auctions and insider collusions, we model and analyze auction protocols for insider threats using the interactive theorem prover Isabelle. We use the existing example of a fictitious cocaine auction protocol from the literature to develop and illustrate our approach. Combining the Isabelle Insider framework with the inductive approach to verifying security protocols in Isabelle, we formalize the cocaine auction protocol, prove that this formal definition excludes sweetheart deals, and also that collusion attacks cannot generally be excluded. The practical implication of the formalization is demonstrated by code generation. Isabelle allows generating code from constructive specifications into the programming language Scala. We provide constructive test functions for cocaine auction traces, prove within Isabelle that these functions conform to the protocol definition, and apply code generation to produce an implementation of the executable test predicate for cocaine auction traces in Scala