With the development of sensor network, mobile computing, and web applications, data are now collected from many distributed sources to form big datasets. Such datasets can be hosted in the cloud to achieve economical processing. However, these data might be highly sensitive requiring secure storage and processing. We envision a cloud-based data storage and processing framework that enables users to economically and securely share and handle big datasets. Under this framework, we study the matrix-based data mining algorithms with a focus on the secure top-k eigenvector algorithm. Our approach uses an iterative processing model in which the authorized user interacts with the cloud to achieve the result. In this process, both the source matrix and the intermediate results keep confidential and the client-side incurs low costs. The security of this approach is guaranteed by using Paillier Encryption and a random perturbation technique. We carefully analyze its security under a cloud-specific threat model. Our experimental results show that the proposed method is scalable to big matrices while requiring low client-side costs.
A framework for securely outsourcing general computations is given in @cite_16 . However, this framework is based on Gentry's fully homomorphic encryption scheme @cite_9 rendering it impractical due to the high computational costs and ciphertext sizes. A simple test with the Scarab FHE library (hcrypt.com scarab-library) yielded ciphertext sizes more than ten times those generated using Paillier @cite_14 . Very recent work by @cite_12 propose a secure outsourcing solution for problems which only require the encryption scheme to be somewhat'' homomorphic (SHE). They use the SHE scheme of @cite_10 which provides reasonably efficient computational performance but still suffers from large ciphertexts.
@cite_14 @cite_9 @cite_16 @cite_10 @cite_12
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We present a novel approach to fully homomorphic encryption (FHE) that dramatically improves performance and bases security on weaker assumptions. A central conceptual contribution in our work is a new way of constructing leveled fully homomorphic encryption schemes (capable of evaluating arbitrary polynomial-size circuits), without Gentry's bootstrapping procedure. Specifically, we offer a choice of FHE schemes based on the learning with error (LWE) or ring-LWE (RLWE) problems that have 2λ security against known attacks. For RLWE, we have: • A leveled FHE scheme that can evaluate L-level arithmetic circuits with O(λ · L3) per-gate computation -- i.e., computation quasi-linear in the security parameter. Security is based on RLWE for an approximation factor exponential in L. This construction does not use the bootstrapping procedure. • A leveled FHE scheme that uses bootstrapping as an optimization, where the per-gate computation (which includes the bootstrapping procedure) is O(λ2), independent of L. Security is based on the hardness of RLWE for quasi-polynomial factors (as opposed to the sub-exponential factors needed in previous schemes). We obtain similar results to the above for LWE, but with worse performance. Based on the Ring LWE assumption, we introduce a number of further optimizations to our schemes. As an example, for circuits of large width -- e.g., where a constant fraction of levels have width at least λ -- we can reduce the per-gate computation of the bootstrapped version to O(λ), independent of L, by batching the bootstrapping operation. Previous FHE schemes all required Ω(λ3.5) computation per gate. At the core of our construction is a much more effective approach for managing the noise level of lattice-based ciphertexts as homomorphic operations are performed, using some new techniques recently introduced by Brakerski and Vaikuntanathan (FOCS 2011). Cloud computing has emerged as one of the most influential paradigms in the IT industry in recent years. Since this new computing technology requires users to entrust their valuable data to cloud providers, there have been increasing security and privacy concerns on outsourced data. Several schemes employing attribute-based encryption (ABE) have been proposed for access control of outsourced data in cloud computing; however, most of them suffer from inflexibility in implementing complex access control policies. In order to realize scalable, flexible, and fine-grained access control of outsourced data in cloud computing, in this paper, we propose hierarchical attribute-set-based encryption (HASBE) by extending ciphertext-policy attribute-set-based encryption (ASBE) with a hierarchical structure of users. The proposed scheme not only achieves scalability due to its hierarchical structure, but also inherits flexibility and fine-grained access control in supporting compound attributes of ASBE. In addition, HASBE employs multiple value assignments for access expiration time to deal with user revocation more efficiently than existing schemes. We formally prove the security of HASBE based on security of the ciphertext-policy attribute-based encryption (CP-ABE) scheme by Bethencourt and analyze its performance and computational complexity. We implement our scheme and show that it is both efficient and flexible in dealing with access control for outsourced data in cloud computing with comprehensive experiments. We propose the first fully homomorphic encryption scheme, solving an old open problem. Such a scheme allows one to compute arbitrary functions over encrypted data without the decryption key—i.e., given encryptions E(m1), ..., E( mt) of m1, ..., m t, one can efficiently compute a compact ciphertext that encrypts f(m1, ..., m t) for any efficiently computable function f. Fully homomorphic encryption has numerous applications. For example, it enables encrypted search engine queries—i.e., a search engine can give you a succinct encrypted answer to your (boolean) query without even knowing what your query was. It also enables searching on encrypted data; you can store your encrypted data on a remote server, and later have the server retrieve only files that (when decrypted) satisfy some boolean constraint, even though the server cannot decrypt the files on its own. More broadly, it improves the efficiency of secure multiparty computation. In our solution, we begin by designing a somewhat homomorphic "boostrappable" encryption scheme that works when the function f is the scheme's own decryption function. We then show how, through recursive self-embedding, bootstrappable encryption gives fully homomorphic encryption. Fully homomorphic encryption is an encryption method with the property that any computation on the plaintext can be performed by a party having access to the ciphertext only. Here, we formally define and give schemes for quantum homomorphic encryption, which is the encryption of quantum information such that quantum computations can be performed given the ciphertext only. Our schemes allow for arbitrary Clifford group gates, but become inefficient for circuits with large complexity, measured in terms of the non-Clifford portion of the circuit (we use the “ ( 8 )” non-Clifford group gate, also known as the ( T )-gate). Mix-nets are used in e-voting schemes and other applications that require anonymity. Shuffles of homomorphic encryptions are often used in the construction of mix-nets. A shuffle permutes and re-encrypts a set of ciphertexts, but as the plaintexts are encrypted it is not possible to verify directly whether the shuffle operation was done correctly or not. Therefore, to prove the correctness of a shuffle it is often necessary to use zero-knowledge arguments. We propose an honest verifier zero-knowledge argument for the correctness of a shuffle of homomorphic encryptions. The suggested argument has sublinear communication complexity that is much smaller than the size of the shuffle itself. In addition the suggested argument matches the lowest computation cost for the verifier compared to previous work and also has an efficient prover. As a result our scheme is significantly more efficient than previous zero-knowledge schemes in literature. We give performance measures from an implementation where the correctness of a shuffle of 100,000 ElGamal ciphertexts is proved and verified in around 2 minutes. HElib is a software library that implements homomorphic encryption (HE), specifically the Brakerski-Gentry-Vaikuntanathan (BGV) scheme, focusing on effective use of the Smart-Vercauteren ciphertext packing techniques and the Gentry-Halevi-Smart optimizations. The underlying cryptosystem serves as the equivalent of a “hardware platform” for HElib, in that it defines a set of operations that can be applied homomorphically, and specifies their cost. This “platform” is a SIMD environment (somewhat similar to Intel SSE and the like), but with unique cost metrics and parameters. In this report we describe some of the algorithms and optimization techniques that are used in HElib for data movement, linear algebra, and other operations over this “platform.” Attribute-based encryption (ABE) is a new vision for public key encryption that allows users to encrypt and decrypt messages based on user attributes. For example, a user can create a ciphertext that can be decrypted only by other users with attributes satisfying ("Faculty" OR ("PhD Student" AND "Quals Completed")). Given its expressiveness, ABE is currently being considered for many cloud storage and computing applications. However, one of the main efficiency drawbacks of ABE is that the size of the ciphertext and the time required to decrypt it grows with the complexity of the access formula. In this work, we propose a new paradigm for ABE that largely eliminates this overhead for users. Suppose that ABE ciphertexts are stored in the cloud. We show how a user can provide the cloud with a single transformation key that allows the cloud to translate any ABE ciphertext satisfied by that user's attributes into a (constant-size) El Gamal-style ciphertext, without the cloud being able to read any part of the user's messages. To precisely define and demonstrate the advantages of this approach, we provide new security definitions for both CPA and replayable CCA security with outsourcing, several new constructions, an implementation of our algorithms and detailed performance measurements. In a typical configuration, the user saves significantly on both bandwidth and decryption time, without increasing the number of transmissions. Let ψ be a 2-DNF formula on boolean variables x1,...,xn ∈ 0,1 . We present a homomorphic public key encryption scheme that allows the public evaluation of ψ given an encryption of the variables x1,...,xn. In other words, given the encryption of the bits x1,...,xn, anyone can create the encryption of ψ(x1,...,xn). More generally, we can evaluate quadratic multi-variate polynomials on ciphertexts provided the resulting value falls within a small set. We present a number of applications of the system: In a database of size n, the total communication in the basic step of the Kushilevitz-Ostrovsky PIR protocol is reduced from @math to @math . An efficient election system based on homomorphic encryption where voters do not need to include non-interactive zero knowledge proofs that their ballots are valid. The election system is proved secure without random oracles but still efficient. A protocol for universally verifiable computation. We study the problem of a public key encryption with conjunctive keyword search (PECK). The keyword searchable encryption enables a user to outsource his data to the storage of an untrusted server and to have the ability to selectively search his data without leaking information. The PECK scheme provides the document search containing each of several keywords over a public key setting. First, we construct an efficient PECK scheme whose security is proven over a decisional linear Diffie-Hellman assumption in the random oracle model. In comparison with previous schemes, our scheme has the shortest ciphertext size and private key size, and requires a comparable computation overhead. Second, we discuss problems related to the security proof of previous schemes and show they cannot guarantee complete security. Finally, we introduce a new concept called a multi-user PECK scheme, which can achieve an efficient computation and communication overhead and effectively manage the storage in a server for a number of users. In an order-preserving encryption scheme, the encryption algorithm produces ciphertexts that preserve the order of their plaintexts. Order-preserving encryption schemes have been studied intensely in the last decade, and yet not much is known about the security of these schemes. Very recently, Boneh eti¾?al. Eurocrypti¾?2015 introduced a generalization of order-preserving encryption, called order-revealing encryption, and presented a construction which achieves this notion with best-possible security. Because their construction relies on multilinear maps, it is too impractical for most applications and therefore remains a theoretical result. In this work, we build efficiently implementable order-revealing encryption from pseudorandom functions. We present the first efficient order-revealing encryption scheme which achieves a simulation-based security notion with respect to a leakage function that precisely quantifies what is leaked by the scheme. In fact, ciphertexts in our scheme are only about 1.6 times longer than their plaintexts. Moreover, we show how composing our construction with existing order-preserving encryption schemes results in order-revealing encryption that is strictly more secure than all preceding order-preserving encryption schemes. Private set intersection enables two parties -- a client and a server -- to compute the intersection of their respective sets without disclosing anything else. It is a fundamental operation -- equivalent to a secure, distributed database join -- and has many applications particularly in privacy-preserving law enforcement. In this paper we present a novel protocol that has linear complexity, is secure in the malicious model without random oracles, is client set size-independent and efficient. Furthermore, the computation of the intersection can be outsourced to an oblivious service provider, as in secure cloud computing. We leverage a completely novel construction for computing the intersection using Bloom filter and homomorphic encryption. For outsourcing we require and introduce a new homomorphic encryption scheme which may be of independent interest. To improve the accuracy of learning result, in practice multiple parties may collaborate through conducting joint Back-Propagation neural network learning on the union of their respective data sets. During this process no party wants to disclose her his private data to others. Existing schemes supporting this kind of collaborative learning are either limited in the way of data partition or just consider two parties. There lacks a solution that allows two or more parties, each with an arbitrarily partitioned data set, to collaboratively conduct the learning. This paper solves this open problem by utilizing the power of cloud computing. In our proposed scheme, each party encrypts his her private data locally and uploads the ciphertexts into the cloud. The cloud then executes most of the operations pertaining to the learning algorithms over ciphertexts without knowing the original private data. By securely offloading the expensive operations to the cloud, we keep the computation and communication costs on each party minimal and independent to the number of participants. To support flexible operations over ciphertexts, we adopt and tailor the BGN "doubly homomorphic" encryption algorithm for the multiparty setting. Numerical analysis and experiments on commodity cloud show that our scheme is secure, efficient, and accurate. Constrained shortest distance (CSD) querying is one of the fundamental graph query primitives, which finds the shortest distance from an origin to a destination in a graph with a constraint that the total cost does not exceed a given threshold. CSD querying has a wide range of applications, such as routing in telecommunications and transportation. With an increasing prevalence of cloud computing paradigm, graph owners desire to outsource their graphs to cloud servers. In order to protect sensitive information, these graphs are usually encrypted before being outsourced to the cloud. This, however, imposes a great challenge to CSD querying over encrypted graphs. Since performing constraint filtering is an intractable task, existing work mainly focuses on unconstrained shortest distance queries. CSD querying over encrypted graphs remains an open research problem. In this paper, we propose Connor , a novel graph encryption scheme that enables approximate CSD querying. Connor is built based on an efficient, tree-based ciphertext comparison protocol, and makes use of symmetric-key primitives and the somewhat homomorphic encryption, making it computationally efficient. Using Connor , a graph owner can first encrypt privacy-sensitive graphs and then outsource them to the cloud server, achieving the necessary privacy without losing the ability of querying. Extensive experiments with real-world data sets demonstrate the effectiveness and efficiency of the proposed graph encryption scheme. In this paper, we consider the problem of predicate encryption and focus on the predicate for testing whether the Hamming distance between the attribute X of a data item and a target V is equal to (or less than) a threshold t where X and V are of length m. Existing solutions either do not provide attribute protection or produce a big ciphertext of size O(2 m ). For the equality version of the problem, we provide a scheme which is match-concealing (MC) secure and the sizes of the ciphertext and token are both O(m). For the inequality version of the problem, we give a practical scheme, also achieving MC security, which produces a ciphertext with size (O(m^ t_ max ) ) if the maximum value of t, t max , is known in advance and is a constant. We also show how to update the ciphertext if the user wants to increase t max without constructing the ciphertext from scratch. Order-preserving encryption - an encryption scheme where the sort order of ciphertexts matches the sort order of the corresponding plaintexts - allows databases and other applications to process queries involving order over encrypted data efficiently. The ideal security guarantee for order-preserving encryption put forth in the literature is for the ciphertexts to reveal no information about the plaintexts besides order. Even though more than a dozen schemes were proposed, all these schemes leak more information than order. This paper presents the first order-preserving scheme that achieves ideal security. Our main technique is mutable ciphertexts, meaning that over time, the ciphertexts for a small number of plaintext values change, and we prove that mutable ciphertexts are needed for ideal security. Our resulting protocol is interactive, with a small number of interactions. We implemented our scheme and evaluated it on microbenchmarks and in the context of an encrypted MySQL database application. We show that in addition to providing ideal security, our scheme achieves 1 - 2 orders of magnitude higher performance than the state-of-the-art order-preserving encryption scheme, which is less secure than our scheme. We construct a simple fully homomorphic encryption scheme, using only elementary modular arithmetic. We use Gentry’s technique to construct a fully homomorphic scheme from a “bootstrappable” somewhat homomorphic scheme. However, instead of using ideal lattices over a polynomial ring, our bootstrappable encryption scheme merely uses addition and multiplication over the integers. The main appeal of our scheme is the conceptual simplicity. We reduce the security of our scheme to finding an approximate integer gcd – i.e., given a list of integers that are near-multiples of a hidden integer, output that hidden integer. We investigate the hardness of this task, building on earlier work of Howgrave-Graham. We present a new tensoring technique for LWE-based fully homomorphic encryption. While in all previous works, the ciphertext noise grows quadratically @math with every multiplication before "refreshing", our noise only grows linearly @math . We use this technique to construct a scale-invariant fully homomorphic encryption scheme, whose properties only depend on the ratio between the modulus q and the initial noise level B, and not on their absolute values. Our scheme has a number of advantages over previous candidates: It uses the same modulus throughout the evaluation process no need for "modulus switching", and this modulus can take arbitrary form. In addition, security can be classically reduced from the worst-case hardness of the GapSVP problem with quasi-polynomial approximation factor, whereas previous constructions could only exhibit a quantum reduction from GapSVP. This paper proposes a novel public-key cryptosystem, which is practical, provably secure and has some other interesting properties as follows: 1. Its trapdoor technique is essentially different from any other previous schemes including RSA-Rabin and Diffie-Hellman. 2. It is a probabilistic encryption scheme. 3. It can be proven to be as secure as the intractability of factoring n = p2q (in the sense of the security of the whole plaintext) against passive adversaries. 4. It is semantically secure under the p-subgroup assumption, which is comparable to the quadratic residue and higher degree residue assumptions. 5. Under the most practical environment, the encryption and decryption speeds of our scheme are comparable to (around twice slower than) those of elliptic curve cryptosystems. 6. It has a homomorphic property: E(m0, r0)E(m1, r1) mod n = E(@#@ m0 + m1, r2), where E(m, r) means a ciphertext of plaintext m as randomized by r and m0+ m1 < p. 7. Anyone can change a ciphertext, C = E(m, r), into another ciphertext, C′ = Chr' mod n, while preserving plaintext of C (i.e., C′ = E(m,r″)), and the relationship between C and C′ can be concealed. The rapid expansion and increased popularity of cloud computing comes with no shortage of privacy concerns about outsourcing computation to semi-trusted parties. Leveraging the power of encryption, in this paper, we introduce Cryptoleq: an abstract machine based on the concept of one instruction set computer, capable of performing general-purpose computation on encrypted programs. The program operands are protected using the Paillier partially homomorphic cryptosystem, which supports addition on the encrypted domain. Full homomorphism over addition and multiplication, which is necessary for enabling general-purpose computation, is achieved by inventing a heuristically obfuscated software re-encryption module written using Cryptoleq instructions and blended into the executing program. Cryptoleq is heterogeneous, allowing mixing encrypted and unencrypted instruction operands in the same program memory space. Programming with Cryptoleq is facilitated using an enhanced assembly language that allows the development of any advanced algorithm on encrypted data sets. In our evaluation, we compare Cryptoleq's performance against a popular fully homomorphic encryption library, and demonstrate correctness using a typical private information retrieval problem. We present a (probabilistic) public key encryption (PKE) scheme such that when being implemented in a bilinear group, anyone is able to check whether two ciphertexts are encryptions of the same message. Interestingly, bilinear map operations are not required in key generation, encryption or decryption procedures of the PKE scheme, but is only required when people want to do an equality test (on the encrypted messages) between two ciphertexts that may be generated using different public keys. We show that our PKE scheme can be used in different applications such as searchable encryption and partitioning encrypted data. Moreover, we show that when being implemented in a non-bilinear group, the security of our PKE scheme can be strengthened from One-Way CCA to a weak form of IND-CCA.