Optimal non-perfect uniform secret sharing schemes

A secret sharing scheme is non-perfect if some subsets of participants that cannot recover the secret value have partial information about it. The information ratio of a secret sharing scheme is the ratio between the maximum length of the shares and the length of the secret. This work is dedicated to the search of bounds on the information ratio of non-perfect secret sharing schemes. To this end, we extend the known connections between polymatroids and perfect secret sharing schemes to the non-perfect case. In order to study non-perfect secret sharing schemes in all generality, we describe their structure through their access function, a real function that measures the amount of information that every subset of participants obtains about the secret value. We prove that there exists a secret sharing scheme for every access function. Uniform access functions, that is, the ones whose values depend only on the number of participants, generalize the threshold access structures. Our main result is to determine the optimal information ratio of the uniform access functions. Moreover, we present a construction of linear secret sharing schemes with optimal information ratio for the rational uniform access functions.Peer ReviewedPostprint (author's final draft

On the information ratio of non-perfect secret sharing schemes

The final publication is available at Springer via http://dx.doi.org/10.1007/s00453-016-0217-9A secret sharing scheme is non-perfect if some subsets of players that cannot recover the secret value have partial information about it. The information ratio of a secret sharing scheme is the ratio between the maximum length of the shares and the length of the secret. This work is dedicated to the search of bounds on the information ratio of non-perfect secret sharing schemes and the construction of efficient linear non-perfect secret sharing schemes. To this end, we extend the known connections between matroids, polymatroids and perfect secret sharing schemes to the non-perfect case. In order to study non-perfect secret sharing schemes in all generality, we describe their structure through their access function, a real function that measures the amount of information on the secret value that is obtained by each subset of players. We prove that there exists a secret sharing scheme for every access function. Uniform access functions, that is, access functions whose values depend only on the number of players, generalize the threshold access structures. The optimal information ratio of the uniform access functions with rational values has been determined by Yoshida, Fujiwara and Fossorier. By using the tools that are described in our work, we provide a much simpler proof of that result and we extend it to access functions with real values.Peer ReviewedPostprint (author's final draft

Local Bounds for the Optimal Information Ratio of Secret Sharing Schemes

The information ratio of a secret sharing scheme $\Sigma$ is the ratio between the length of the largest share and the length of the secret, and it is denoted by $\sigma(\Sigma)$. The optimal information ratio of an access structure $\Gamma$ is the infimum of $\sigma(\Sigma)$ among all schemes $\Sigma$ with access structure $\Gamma$, and it is denoted by $\sigma(\Gamma)$. The main result of this work is that for every two access structures $\Gamma$ and $\Gamma\u27$, $|\sigma(\Gamma)-\sigma(\Gamma\u27)|\leq |\Gamma\cup\Gamma\u27|-|\Gamma\cap\Gamma\u27|$. We prove it constructively. Given any secret sharing scheme $\Sigma$ for $\Gamma$, we present a method to construct a secret sharing scheme $\Sigma\u27$ for $\Gamma\u27$ that satisfies that $\sigma(\Sigma\u27)\leq \sigma(\Sigma)+|\Gamma\cup\Gamma\u27|-|\Gamma\cap\Gamma\u27|$. As a consequence of this result, we see that \emph{close} access structures admit secret sharing schemes with similar information ratio. We show that this property is also true for particular classes of secret sharing schemes and models of computation, like the family of linear secret sharing schemes, span programs, Boolean formulas and circuits. In order to understand this property, we also study the limitations of the techniques for finding lower bounds on the information ratio and other complexity measures. We analyze the behavior of these bounds when we add or delete subsets from an access structure

Improving the Linear Programming Technique in the Search for Lower Bounds in Secret Sharing

We present a new improvement in the linear programming technique to derive lower bounds on the information ratio of secret sharing schemes. We obtain non-Shannon-type bounds without using information inequalities explicitly. Our new technique makes it possible to determine the optimal information ratio of linear secret sharing schemes for all access structures on 5 participants and all graph-based access structures on 6 participants. In addition, new lower bounds are presented also for some small matroid ports and, in particular, the optimal information ratios of the linear secret sharing schemes for the ports of the Vamos matroid are determined

A Candidate Access Structure for Super-polynomial Lower Bound on Information Ratio

The contribution vector (convec) of a secret sharing scheme is the vector of all share sizes divided by the secret size. A measure on the convec (e.g., its maximum or average) is considered as a criterion of efficiency of secret sharing schemes, which is referred to as the information ratio. It is generally believed that there exists a family of access structures such that the information ratio of any secret sharing scheme realizing it is $2^{\mathrm{\Omega}(n)}$, where the parameter $n$ stands for the number of participants. The best known lower bound, due to Csirmaz (1994), is $\mathrm{\Omega}(n/\log n)$. Closing this gap is a long-standing open problem in cryptology. Using a technique called \emph{substitution}, we recursively construct a family of access structures by starting from that of Csirmaz, which might be a candidate for super-polynomial information ratio. We provide support for this possibility by showing that our family has information ratio ${n^{\mathrm{\Omega}(\frac{\log n}{\log \log n})}}$, assuming the truth of a well-stated information-theoretic conjecture, called the \emph{substitution conjecture}. The substitution method is a technique for composition of access structures, similar to the so called block composition of Boolean functions, and the substitution conjecture is reminiscent of the Karchmer-Raz-Wigderson conjecture on depth complexity of Boolean functions. It emerges after introducing the notion of convec set for an access structure, a subset of $n$-dimensional real space, which includes all achievable convecs. We prove some topological properties about convec sets and raise several open problems

Cryptographic Techniques for Securing Data in the Cloud

El paradigma de la computació al núvol proporciona accés remot a potents infraestructures a cost reduït. Tot i que l’adopció del núvol ofereix nombrosos beneficis, la migració de dades sol requerir un alt nivell de confiança en el proveïdor de serveis i introdueix problemes de privacitat. En aquesta tesi es dissenyen tècniques per a permetre a usuaris del núvol protegir un conjunt de dades externalitzades. Les solucions proposades emanen del projecte H2020 de la Comissió Europea “CLARUS: User-Centered Privacy and Security in the Cloud”. Els problemes explorats són la cerca sobre dades xifrades, la delegació de càlculs d’interpolació, els esquemes de compartició de secrets i la partició de dades. Primerament, s’estudia el problema de la cerca sobre dades xifrades mitjançant els esquemes de xifrat cercable simètric (SSE), i es desenvolupen tècniques que permeten consultes per rangs dos-dimensionals a SSE. També es tracta el mateix problema utilitzant esquemes de xifrat cercable de clau pública (PEKS), i es presenten esquemes PEKS que permeten consultes conjuntives i de subconjunt. En aquesta tesi també s’aborda la delegació privada de computacions Kriging. Kriging és un algoritme d’interpolació espaial dissenyat per a aplicacions geo-estadístiques. Es descriu un mètode per a delegar interpolacions Kriging de forma privada utilitzant xifrat homomòrfic. Els esquemes de compartició de secrets són una primitiva fonamental en criptografia, utilitzada a diverses solucions orientades al núvol. Una de les mesures d’eficiència relacionades més importants és la taxa d’informació òptima. Atès que calcular aquesta taxa és generalment difícil, s’obtenen propietats que faciliten la seva descripció. Finalment, es tracta el camp de la partició de dades per a la protecció de la privacitat. Aquesta tècnica protegeix la privacitat de les dades emmagatzemant diversos fragments a diferents ubicacions. Aquí s’analitza aquest problema des d’un punt de vista combinatori, fitant el nombre de fragments i proposant diversos algoritmes.El paradigma de la computación en la nube proporciona acceso remoto a potentes infraestructuras a coste reducido. Aunque la adopción de la nube ofrece numerosos beneficios, la migración de datos suele requerir un alto nivel de confianza en el proveedor de servicios e introduce problemas de privacidad. En esta tesis se diseñan técnicas para permitir a usuarios de la nube proteger un conjunto de datos externalizados. Las soluciones propuestas emanan del proyecto H2020 de la Comisión Europea “CLARUS: User-Centered Privacy and Security in the Cloud”. Los problemas explorados son la búsqueda sobre datos cifrados, la delegación de cálculos de interpolación, los esquemas de compartición de secretos y la partición de datos. Primeramente, se estudia el problema de la búsqueda sobre datos cifrados mediante los esquemas de cifrado simétrico buscable (SSE), y se desarrollan técnicas para permitir consultas por rangos dos-dimensionales en SSE. También se trata el mismo problema utilizando esquemas de cifrado buscable de llave pública (PEKS), y se presentan esquemas que permiten consultas conyuntivas y de subconjunto. Adicionalmente, se aborda la delegación privada de computaciones Kriging. Kriging es un algoritmo de interpolación espacial diseñado para aplicaciones geo-estadísticas. Se describe un método para delegar interpolaciones Kriging privadamente utilizando técnicas de cifrado homomórfico. Los esquemas de compartición de secretos son una primitiva fundamental en criptografía, utilizada en varias soluciones orientadas a la nube. Una de las medidas de eficiencia más importantes es la tasa de información óptima. Dado que calcular esta tasa es generalmente difícil, se obtienen propiedades que facilitan su descripción. Por último, se trata el campo de la partición de datos para la protección de la privacidad. Esta técnica protege la privacidad de los datos almacenando varios fragmentos en distintas ubicaciones. Analizamos este problema desde un punto de vista combinatorio, acotando el número de fragmentos y proponiendo varios algoritmos.The cloud computing paradigm provides users with remote access to scalable and powerful infrastructures at a very low cost. While the adoption of cloud computing yields a wide array of benefits, the act of migrating to the cloud usually requires a high level of trust in the cloud service provider and introduces several security and privacy concerns. This thesis aims at designing user-centered techniques to secure an outsourced data set in cloud computing. The proposed solutions stem from the European Commission H2020 project “CLARUS: User-Centered Privacy and Security in the Cloud”. The explored problems are searching over encrypted data, outsourcing Kriging interpolation computations, secret sharing and data splitting. Firstly, the problem of searching over encrypted data is studied using symmetric searchable encryption (SSE) schemes, and techniques are developed to enable efficient two-dimensional range queries in SSE. This problem is also studied through public key encryption with keyword search (PEKS) schemes, efficient PEKS schemes achieving conjunctive and subset queries are proposed. This thesis also aims at securely outsourcing Kriging computations. Kriging is a spatial interpolation algorithm designed for geo-statistical applications. A method to privately outsource Kriging interpolation is presented, based in homomorphic encryption. Secret sharing is a fundamental primitive in cryptography, used in many cloud-oriented techniques. One of the most important efficiency measures in secret sharing is the optimal information ratio. Since computing the optimal information ratio of an access structure is generally hard, properties are obtained to facilitate its description. Finally, this thesis tackles the privacy-preserving data splitting technique, which aims at protecting data privacy by storing different fragments of data at different locations. Here, the data splitting problem is analyzed from a combinatorial point of view, bounding the number of fragments and proposing various algorithms to split the data

On Group-Characterizability of Homomorphic Secret Sharing Schemes

A group-characterizable (GC) random variable is induced by a finite group, called main group, and a collection of its subgroups [Chan and Yeung 2002]. The notion extends directly to secret sharing schemes (SSS). It is known that multi-linear SSSs can be equivalently described in terms of GC ones. The proof extends to abelian SSSs, a more powerful generalization of multi-linear schemes, in a straightforward way. Both proofs are fairly easy considering the notion of dual for vector spaces and Pontryagin dual for abelian groups. However, group-characterizability of homomorphic SSSs (HSSSs), which are generalizations of abelian schemes, is non-trivial, and thus the main focus of this paper. We present a necessary and sufficient condition for a SSS to be equivalent to a GC one. Then, we use this result to show that HSSSs satisfy the sufficient condition, and consequently they are GC. Then, we strengthen this result by showing that a group-characterization can be found in which the subgroups are all normal in the main group. On the other hand, GC SSSs whose subgroups are normal in the main group can easily be shown to be homomorphic. Therefore, we essentially provide an equivalent characterization of HSSSs in terms of GC schemes. We also present two applications of our equivalent definition for HSSSs. One concerns lower bounding the information ratio of access structures for the class of HSSSs, and the other is about the coincidence between statistical, almost-perfect and perfect security notions for the same class

On the Information Ratio of Non-Perfect Secret Sharing Schemes

A secret sharing scheme is non-perfect if some subsets of players that cannot recover the secret value have partial information about it. The information ratio of a secret sharing scheme is the ratio between the maximum length of the shares and the length of the secret. This work is dedicated to the search of bounds on the information ratio of non-perfect secret sharing schemes and the construction of efficient linear non-perfect secret sharing schemes. To this end, we extend the known connections between matroids, polymatroids and perfect secret sharing schemes to the non-perfect case. In order to study non-perfect secret sharing schemes in all generality, we describe their structure through their access function, a real function that measures the amount of information on the secret value that is obtained by each subset of players. We prove that there exists a secret sharing scheme for every access function. Uniform access functions, that is, access functions whose values depend only on the number of players, generalize the threshold access structures. The optimal information ratio of the uniform access functions with rational values has been determined by Yoshida, Fujiwara and Fossorier. By using the tools that are described in our work, we provide a much simpler proof of that result and we extend it to access functions with real values

On the Theory of Linear Rank Inequalities

Abstract. In this work, we study linear polymatroids and linear rank inequalities. We focus on the problem of determining if the Common Information Method can generate all the linear inequalities satisfied by all linear polymatroids. It is well known that there exist deep connections between the Theory of Linear Rank Inequalities and Linear Secret Sharing. We study those connections. First, we study the problem of estimating the information rates that can be achieved by Linear Secret Sharing. Then, we arrive to the novel notion of Abelian Secret Sharing. We prove that if Abelian Secret Sharing outperforms Linear Secret Sharing, then the Common Information Method is incomplete. Therefore, we focus on the problem of comparing the performances of abelian and linear schemes. We show that the last problem is related to the Representation Theory of Matroids.En este trabajo estudiamos los polimatroides lineales y las desigualdades rango lineales. Nos enfocamos en el problema de determinar si elMétodo de la Información Común puede generar todas las desigualdades rango lineales, que son las desigualdades satisfechas por todos los polimatroides lineales. Se sabe que existen conexiones profundas entre la Teoría de desigualdades rango lineales y el Problema de Repartición Lineal de Secretos. En este texto estudiamos estas conexiones. Primero, estudiamos el problema de estimar las ratas de información que pueden ser alcanzadas por soluciones lineales al Problema de Repartición de Secretos. Luego, llegamos a la nueva noción de Repartición Abeliana de Secretos. Probamos que si las soluciones abelianas al Problema de Repartición de Secretos superan a las soluciones lineales, entonces el Método de la Información Común es incompleto. Por lo tanto, nos enfocamos en el problema de comparar las representaciones de esquemas abelianos y lineales. Nosotros probamos que este último problema está relacionado con la Teoría de Representación de Matroides.Doctorad

Batched differentially private information retrieval

Private Information Retrieval (PIR) allows several clients to query a database held by one or more servers, such that the contents of their queries remain private. Prior PIR schemes have achieved sublinear communication and computation by leveraging computational assumptions, federating trust among many servers, relaxing security to permit differentially private leakage, refactoring effort into an offline stage to reduce online costs, or amortizing costs over a large batch of queries. In this work, we present an efficient PIR protocol that combines all of the above techniques to achieve constant amortized communication and computation complexity in the size of the database and constant client work. We leverage differentially private leakage in order to provide better trade-offs between privacy and efficiency. Our protocol achieves speed-ups up to and exceeding 10x in practical settings compared to state of the art PIR protocols, and can scale to batches with hundreds of millions of queries on cheap commodity AWS machines. Our protocol builds upon a new secret sharing scheme that is both incremental and non-malleable, which may be of interest to a wider audience. Our protocol provides security up to abort against malicious adversaries that can corrupt all but one party.1414119 - National Science Foundation; CNS-1718135 - National Science Foundation; CNS-1931714 - National Science Foundation; HR00112020021 - Department of Defense/DARPA; 000000000000000000000000000000000000000000000000000000037211 - SRI Internationalhttps://www.usenix.org/system/files/sec22-albab.pdfPublished versio