Verifiable computation using multiple provers

The increasing ubiquity of the cloud computing paradigm has renewed focus on the classical problem of allowing weak clients to check the results of computation delegated to powerful servers. Recent advances in proof-based verifiable computation have led to several near-practical protocols. Protocols based on interactive proofs (IPs) work with highly restrictive models of computation and are thus efficient only for a limited class of computations. In contrast, protocols based on argument systems apply to a much larger class of computations, but efficiency requires amortization of very expensive setup costs. This paper initiates the study of the practical efficiency of multiprover interactive proofs (MIPs). We present a new MIP for delegating computation that extends insights from a powerful IP protocol (Goldwasser et al., STOC, 2008). Without reductions or amplification, our protocol uses only two provers (departing from prior work on MIPs), and achieves both the efficiency of interactive proof-based protocols and the generality of argument system-based protocols. Also, this result, together with recently developed machinery, creates a potential avenue toward concretely efficient arguments without setup costs. We describe Clover, a built system for verifiable computation, based on our protocol. Although Clover does not implement the full theory (it has setup costs), it applies to problems that existing IPs cannot efficiently handle, and achieves performance comparable to, or better than, the best argument systems

Verifying Computations with State (Extended Version)

When a client outsources a job to a third party (e.g., the cloud), how can the client check the result, without reexecuting the computation? Recent work in _proof-based verifiable computation_ has made significant progress on this problem by incorporating deep results from complexity theory and cryptography into built systems. However, these systems work within a stateless model: they exclude computations that interact with RAM or a disk, or for which the client does not have the full input. This paper describes Pantry, a built system that overcomes these limitations. Pantry composes proof-based verifiable computation with untrusted storage: the client expresses its computation in terms of digests that attest to state, and verifiably outsources _that_ computation. Using Pantry, we extend verifiability to MapReduce jobs, simple database queries, and interactions with private state. Thus, Pantry takes another step toward practical proof-based verifiable computation for realistic applications

Full accounting for verifiable outsourcing

Systems for verifiable outsourcing incur costs for a prover, a verifier, and precomputation; outsourcing makes sense when the combination of these costs is cheaper than not outsourcing. Yet, when prior works impose quantitative thresholds to analyze whether outsourcing is justified, they generally ignore prover costs. Verifiable ASICs (VA)---in which the prover is a custom chip---is the other way around: its cost calculations ignore precomputation. This paper describes a new VA system, called Giraffe; charges Giraffe for all three costs; and identifies regimes where outsourcing is worthwhile. Giraffe’s base is an interactive proof geared to data-parallel computation. Giraffe makes this protocol asymptotically optimal for the prover and improves the verifier\u27s main bottleneck by almost 3x, both of which are of independent interest. Giraffe also develops a design template that produces hardware designs automatically for a wide range of parameters, introduces hardware primitives molded to the protocol’s data flows, and incorporates program analyses that expand applicability. Giraffe wins even when outsourcing several tens of sub-computations, scales to 500x larger computations than prior work, and can profitably outsource parts of programs that are not worthwhile to outsource in full

Obesity and treatment meanings in bariatric surgery candidates: a qualitative study

Background This study used a qualitative approach to comprehend how the morbid obese conceptualize and deal with obesity and obesity treatment, with the particular aim of exploring the expectations and beliefs about the exigencies and the impact of bariatric surgery. Methods The study population included 30 morbid obese patients (20 women and 10 men) with a mean age of 39.17 years (SD = 8.81) and a mean body mass index of 47.5 (SD = 8.2) interviewed individually before surgery using open-ended questions. The interviews were audiotaped, transcribed, and then coded according to grounded analysis methodology. Results Three main thematic areas emerged from the data: obesity, eating behavior, and treatment. Obesity is described as a stable and hereditary trait. Although participants recognize that personal eating behavior exacerbates this condition, patients see their eating behavior as difficult to change and control. Food seems to be an ever-present dimension and a coping strategy, and to follow an adequate diet plan is described as a huge sacrifice. Bariatric surgery emerges as the only treatment for obesity, and participants highlight this moment as the beginning of a new life where health professionals have the main role. Bariatric surgery candidates see their eating behavior as out of their control, and to commit to its demands is seen as a big sacrifice. For these patients, surgery is understood as a miracle moment that will change their lives without requiring an active role or their participation. Conclusion According to these results, it is necessary to validate them with qualitative and quantitative studies; it is necessary to promote a new awareness of the weight loss process and to empower patients before and after bariatric surgery.Bolsa de doutoramento SFRH/BD/37069/2007 da Fundação para a Ciência e a Tecnologia (FCT

A Brief Overview of the NEBULA Future Internet Architecture

NEBULA is a proposal for a Future Internet Architecture. It is based on the assumptions that: (1) cloud computing will comprise an increasing fraction of the application workload offered to an Internet, and (2) that access to cloud computing resources will demand new architectural features from a network. Features that we have identified include dependability, security, flexibility and extensibility, the entirety of which constitute resilience.NEBULA provides resilient networking services using ultrareliable routers, an extensible control plane and use of multiple paths upon which arbitrary policies may be enforced. We report on a prototype system, Zodiac, that incorporates these latter two features

Efficient Verifiable Computation of XOR for Biometric Authentication

This work addresses the security and privacy issues in remotebiometric authentication by proposing an efficient mechanism to verifythe correctness of the outsourced computation in such protocols.In particular, we propose an efficient verifiable computation of XORingencrypted messages using an XOR linear message authenticationcode (MAC) and we employ the proposed scheme to build a biometricauthentication protocol. The proposed authentication protocol is bothsecure and privacy-preserving against malicious (as opposed to honest-but-curious) adversaries. Specifically, the use of the verifiable computation scheme together with an homomorphic encryption protects the privacy of biometric templates against malicious adversaries. Furthermore, in order to achieve unlinkability of authentication attempts, while keeping a low communication overhead, we show how to apply Oblivious RAM and biohashing to our protocol. We also provide a proof of security for the proposed solution. Our simulation results show that the proposed authentication protocol is efficient

Factors related to psychotherapists' self-assessment when treating anxiety and other disorders.

The aim of the study was to replicate and extend recent findings regarding therapists' self-assessment biases. This study examined clinicians' estimates of their abilities when working with general clinical groups and with anxious patients, and of the recovery/improvement rates of their clients. It also considered what clinician personality traits and clinical practice elements were associated with such estimates. A total of 195 out 801 clinicians completed a survey regarding self-ratings, team ratings, therapy outcomes for their clients, and their own personality traits. The great majority of clinicians rated themselves and their teams as being better clinicians than their peers, though not to as extreme a level as in the previous study. They also reported exceptionally positive therapy outcomes. Due to the large proportion of non-responders, it is possible that these findings do not reflect actual self-assessment bias, but a greater willingness to participate among clinicians who are more skilled and with particular personality styles. However, the data suggest that perceptions of skill and therapy outcome might be associated with clinician personality characteristics, though not with other clinical practice variables. These interpretations should be treated with caution due to the limited response rate. Different possible explanations for these patterns of self-assessment are outlined, including conscious and unconscious processes. Methods for enhancing accurate skill perception are discussed, including self-monitoring and supervision