We introduce Signatures of Correct Computation (SCC), a new model for verifying dynamic computations in cloud settings. In the SCC model, a trusted source outsources a function f to an untrusted server, along with a public key for that function (to be used during verification). The server can then produce a succinct signature σ vouching for the correctness of the computation of f, i.e., that some result v is indeed the correct outcome of the function f evaluated on some point a. There are two crucial performance properties that we want to guarantee in an SCC construction: (1) verifying the signature should take asymptotically less time than evaluating the function f; and (2) the public key should be efficiently updated whenever the function changes.

We construct SCC schemes (satisfying the above two properties) supporting expressive manipulations over multivariate polynomials, such as polynomial evaluation and differentiation. Our constructions are adaptively secure in the random oracle model and achieve optimal updates, i.e., the function's public key can be updated in time proportional to the number of updated coefficients, without performing a linear-time computation (in the size of the polynomial).

We also show that signatures of correct computation imply Publicly Verifiable Computation (PVC), a model recently introduced in several concurrent and independent works. Roughly speaking, in the SCC model, any client can verify the signature σ and be convinced of some computation result, whereas in the PVC model only the client that issued a query (or anyone who trusts this client) can verify that the server returned a valid signature (proof) for the answer to the query. Our techniques can be readily adapted to construct PVC schemes with adaptive security, efficient updates and without the random oracle model.

/pdf/signatures-of-correct-computation-2m2aaerpcz.pdf

Signatures of correct computation

We study the design of protocols for set-operation verification, namely the problem of cryptographically checking the correctness of outsourced set operations performed by an untrusted server over a dynamic collection of sets that are owned (and updated) by a trusted source. We present new authenticated data structures that allow any entity to publicly verify a proof attesting the correctness of primitive set operations such as intersection, union, subset and set difference. Based on a novel extension of the security properties of bilinear-map accumulators as well as on a primitive called accumulation tree, our protocols achieve optimal verification and proof complexity (i.e., only proportional to the size of the query parameters and the answer), as well as optimal update complexity (i.e., constant), while incurring no extra asymptotic space overhead. The proof construction is also efficient, adding a logarithmic overhead to the computation of the answer of a set-operation query. In contrast, existing schemes entail high communication and verification costs or high storage costs. Applications of interest include efficient verification of keyword search and database queries. The security of our protocols is based on the bilinear q-strong Diffie-Hellman assumption.

/pdf/optimal-verification-of-operations-on-dynamic-sets-1wdiszyp3p.pdf

Optimal verification of operations on dynamic sets

http://www4.comp.polyu.edu.hk/~csweilou/Publications/pmc2015a.pdf

On protecting end-to-end location privacy against local eavesdropper in Wireless Sensor Networks

Moving objects databases should be able to manage trips that pass through several real world environments, e.g., road network, indoor. However, the current data models only deal with the movement in one situation and cannot represent comprehensive trips for humans who can move inside a building, walk on the pavement, drive on the road, take the public vehicles (bus or train), etc. As a result, existing queries are solely limited to one environment. In this paper, we design a data model that is able to represent moving objects in multiple environments in order to support novel queries on trips in different surroundings and various transportation modes (e.g., Car, Walk, Bus). A generic and precise location representation is proposed that can apply in all environments. The idea is to let the space for moving objects be covered by a set of so-called infrastructures each of which corresponds to an environment and defines the available places for moving objects. Then, the location is represented by referencing to the infrastructure. We formulate the concept of space and infrastructure and propose the methodology to represent moving objects in different environments with the integration of precise transportation modes. Due to different infrastructure characteristics, a set of novel data types is defined to represent infrastructure components. To efficiently support new queries, we design a group of operators to access the data. We present how such a data model is implemented in a database system and report the experimental results. The new model is designed with attention to the data models of previous work for free space and road networks to have a consistent type system and framework of operators. In this way, a powerful set of generic query operations is available for querying, together with those dealing with infrastructures and transportation modes. We demonstrate these capabilities by formulating a set of sophisticated queries across all infrastructures.

A generic data model for moving objects

We study the problem of verifiable delegation of computation over outsourced data, whereby a powerful worker maintains a large data structure for a weak client in a verifiable way Compared to the well-studied problem of verifiable computation, this setting imposes additional difficulties since the verifier also needs to check the consistency of updates succinctly and without maintaining large state We present a scheme for verifiable evaluation of hierarchical set operations unions, intersections and set-differences applied to a collection of dynamically changing sets of elements from a given domain The verification cost incurred is proportional only to the size of the final outcome set and to the size of the query, and is independent of the cardinalities of the involved sets The cost of updates is optimal involving O1 modular operations per update Our construction extends that of [Papamanthou et al, CRYPTO 2011] and relies on a modified version of the extractable collision-resistant hash function ECRH construction, introduced in [Bitansky et al, ITCS 2012] that can be used to succinctly hash univariate polynomials

/pdf/verifiable-set-operations-over-outsourced-databases-3w5040d7dw.pdf

Verifiable Set Operations over Outsourced Databases

Shortest path search in transportation networks is unarguably one of the most important online search services nowadays (e.g., Google Maps, MapQuest, etc), with applications spanning logistics, spatial optimization, or everyday driving decisions. Often times, the owner of the road network data (e.g., a transport authority) provides its database to third-party query services, which are responsible for answering shortest path queries posed by their clients. The issue arising here is that a query service might be returning sub-optimal paths either purposely (in order to serve its own purposes like computational savings or commercial reasons) or because it has been compromised by Internet attackers who falsify the results. Therefore, for the above applications to succeed, it is essential that each reported path is accompanied by a proof, which allows clients to verify the path's correctness. This is the first study on shortest path verification in outsourced network databases. We propose the concept of authenticated hints, which is used to reduce the size of the proofs. We develop several authentication techniques and quantify their tradeoffs with respect to offline construction cost and proof size. Experiments on real road networks demonstrate that our solutions are indeed efficient and lead to compact query proofs.

/pdf/efficient-verification-of-shortest-path-search-via-38mqote540.pdf

Efficient verification of shortest path search via authenticated hints

Location-based services (LBS) are receiving increasing popularity as they provide convenience to mobile users with on-demand information. The use of these services, however, poses privacy issues as the user locations and queries are exposed to untrusted LBSs. Spatial cloaking techniques provide privacy in the form of k -anonymity; i.e., they guarantee that the (location of the) querying user u is indistinguishable from at least k -1 others, where k is a parameter specified by u at query time. To achieve this, they form a group of k users, including u , and forward their minimum bounding rectangle (termed anonymizing spatial region , ASR) to the LBS. The rationale behind sending an ASR instead of the distinct k locations is that exact user positions (querying or not) should not be disclosed to the LBS. This results in large ASRs with considerable dead-space, and leads to unnecessary performance degradation. Additionally, there is no guarantee regarding the amount of location information that is actually revealed to the LBS. In this paper, we introduce the concept of information leakage in spatial cloaking. We provide measures of this leakage, and show how we can trade it for better performance in a tunable manner. The proposed methodology directly applies to centralized and decentralized cloaking models, and is readily deployable on existing systems.

/pdf/spatial-cloaking-revisited-distinguishing-information-2hw32sfl23.pdf

Spatial Cloaking Revisited: Distinguishing Information Leakage from Anonymity

In this paper, we study Resource Constrained Best Upgrade Plan (BUP) computation in road network databases. Consider a transportation network (weighted graph) G where a subset of the edges are upgradable, i.e., for each such edge there is a cost, which if spent, the weight of the edge can be reduced to a specific new value. In the single-pair version of BUP, the input includes a source and a destination in G, and a budget B (resource constraint). The goal is to identify which upgradable edges should be upgraded so that the shortest path distance between source and destination (in the updated network) is minimized, without exceeding the available budget for the upgrade. In the multiple-pair version of BUP, a set Q of source-destination pairs is given, and the problem is to choose for upgrade those edges that lead to the smallest sum of shortest path distances across all pairs in Q, subject to budget constraint B. In addition to transportation networks, the BUP query arises in other domains too, such as telecommunications. We propose a framework for BUP processing and evaluate it with experiments on large, real road networks.

/pdf/best-upgrade-plans-for-single-and-multiple-source-3td4ouitll.pdf

Best upgrade plans for single and multiple source-destination pairs

Research Summary Does growth training help entrepreneurs scale-up new ventures? Our field experiment answers this question using data from 181 Singapore-based, early-growth entrepreneurs drawn from a broad range of industry sectors. Treatment content focused on three growth-catalyst tools relevant for formulating and executing innovation-led growth: business-model design, leveraging external networks, and building internal teams. Treatment format comprised interactive lecture sessions and workshops on these tools supplemented by personalized coaching in applying the tools to entrepreneurs' specific challenges. We find that ventures led by entrepreneurs that received training experienced sales growth of 72.5% compared to 30.3% for those in the control condition. Furthermore, ventures led by entrepreneurs with more ambitious growth expectations experienced sales growth of about 100% compared to 10% for those in the control condition. Managerial Summary We study how training in growth-catalyst tools help entrepreneurs scale-up new ventures. We focused on three tools relevant for formulating and executing innovation-led growth: business-model design, leveraging external networks, and building internal teams. The training format comprised lecture workshops and personalized coaching in applying the tools. Our quantitative findings confirm that entrepreneurs who attended the training increased their venture's sales revenue, and the more ambitious entrepreneurs increased their venture's sales revenue to a much greater degree. Illustrative interviews suggest these tools help entrepreneurs to reimagine their business, successfully access influential resource-holders such as potential investors or customers, and persuade them by representing their business in a credible and succinct fashion. Our findings inform policymakers designing entrepreneurial training interventions on how participants' ambitions shapes intervention success. 

Do Ambitious Entrepreneurs Benefit More from Training?

In this paper, we consider a new problem in the context of road network databases, named Resource Constrained Best Upgrade Plan computation (BUP, for short). Consider a transportation network (weighted graph) G where a subset of the edges are upgradable, i.e., for each such edge there is a cost, which if spent, the weight of the edge can be reduced to a specific new value. Given a source and a destination in G, and a budget (resource constraint) B, the BUP problem is to identify which upgradable edges should be upgraded so that the shortest path distance between source and destination (in the updated network) is minimized, without exceeding the available budget for the upgrade. In addition to transportation networks, the BUP query arises in other domains too, such as telecommunications. We propose a framework for BUP processing and evaluate it with experiments on large, real road networks.

/pdf/best-upgrade-plans-for-large-road-networks-2wvp9ob1xu.pdf

Best Upgrade Plans for Large Road Networks

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