# Biblio

A secure multi-party batch matrix multiplication problem (SMBMM) is considered, where the goal is to allow a master to efficiently compute the pairwise products of two batches of massive matrices, by distributing the computation across S servers. Any X colluding servers gain no information about the input, and the master gains no additional information about the input beyond the product. A solution called Generalized Cross Subspace Alignment codes with Noise Alignment (GCSA- NA) is proposed in this work, based on cross-subspace alignment codes. The state of art solution to SMBMM is a coding scheme called polynomial sharing (PS) that was proposed by Nodehi and Maddah-Ali. GCSA-NA outperforms PS codes in several key aspects - more efficient and secure inter-server communication, lower latency, flexible inter-server network topology, efficient batch processing, and tolerance to stragglers.

This paper studies the deletion propagation problem in terms of minimizing view side-effect. It is a problem funda-mental to data lineage and quality management which could be a key step in analyzing view propagation and repairing data. The investigated problem is a variant of the standard deletion propagation problem, where given a source database D, a set of key preserving conjunctive queries Q, and the set of views V obtained by the queries in Q, we try to identify a set T of tuples from D whose elimination prevents all the tuples in a given set of deletions on views △V while preserving any other results. The complexity of this problem has been well studied for the case with only a single query. Dichotomies, even trichotomies, for different settings are developed. However, no results on multiple queries are given which is a more realistic case. We study the complexity and approximations of optimizing the side-effect on the views, i.e., find T to minimize the additional damage on V after removing all the tuples of △V. We focus on the class of key-preserving conjunctive queries which is a dichotomy for the single query case. It is surprising to find that except the single query case, this problem is NP-hard to approximate within any constant even for a non-trivial set of multiple project-free conjunctive queries in terms of view side-effect. The proposed algorithm shows that it can be approximated within a bound depending on the number of tuples of both V and △V. We identify a class of polynomial tractable inputs, and provide a dynamic programming algorithm to solve the problem. Besides data lineage, study on this problem could also provide important foundations for the computational issues in data repairing. Furthermore, we introduce some related applications of this problem, especially for query feedback based data cleaning.

In this article the combination of secret sharing schemes and the requirement of discretionary security policy is considered. Secret sharing schemes of Shamir and Blakley are investigated. Conditions for parameters of schemes the providing forbidden information channels are received. Ways for concealment of the forbidden channels are suggested. Three modifications of the Shamir's scheme and two modifications of the Blakley's scheme are suggested. Transition from polynoms to exponential functions for formation the parts of a secret is carried out. The problem of masking the presence of the forbidden information channels is solved. Several approaches with the complete and partial concealment are suggested.

A permissioned blockchain platform comes with numerous assurances such as transaction confidentiality and system scalability to several organizations. Most permissioned blockchains rely on a Public-Key Infrastructure (PKI)as cryptographic tools to provide security services such as identity authentication and data confidentiality. Using PKI to validate transactions includes validating digital certificates of endorsement peers which creates an overhead in the system. Because public-key operations are computationally intensive, they limit the scalability of blockchain applications. Due to a large modulus size and expensive modular exponentiation operations, public-key operations such as RSA become slower than polynomial-based schemes, which involve a smaller modulus size and a less smaller number of modular multiplications. For instance, the 2048-bit RSA is approximately 15,728 times slower than a polynomial with a degree of 50 and 128-bit modulus size. In this paper, we propose a lightweight polynomial-based key management scheme in the context of a permissioned blockchain. Our scheme involves computationally less intensive polynomial evaluation operations such as additions and multiplications that result in a faster processing compared with public-key schemes. In addition, our proposed solution reduces the overhead of processing transactions and improves the system scalability. Security and performance analysis are provided in the paper.

Support vector machines (SVMs) have been widely used for classification in machine learning and data mining. However, SVM faces a huge challenge in large scale classification tasks. Recent progresses have enabled additive kernel version of SVM efficiently solves such large scale problems nearly as fast as a linear classifier. This paper proposes a new accelerated mini-batch stochastic gradient descent algorithm for SVM classification with additive kernel (AK-ASGD). On the one hand, the gradient is approximated by the sum of a scalar polynomial function for each feature dimension; on the other hand, Nesterov's acceleration strategy is used. The experimental results on benchmark large scale classification data sets show that our proposed algorithm can achieve higher testing accuracies and has faster convergence rate.

Homomorphic signatures can provide a credential of a result which is indeed computed with a given function on a data set by an untrusted third party like a cloud server, when the input data are stored with the signatures beforehand. Boneh and Freeman in EUROCRYPT2011 proposed a homomorphic signature scheme for polynomial functions of any degree, however the scheme is not based on the normal short integer solution (SIS) problems as its security assumption. In this paper, we show a homomorphic signature scheme for quadratic polynomial functions those security assumption is based on the normal SIS problems. Our scheme constructs the signatures of multiplication as tensor products of the original signature vectors of input data so that homomorphism holds. Moreover, security of our scheme is reduced to the hardness of the SIS problems respect to the moduli such that one modulus is the power of the other modulus. We show the reduction by constructing solvers of the SIS problems respect to either of the moduli from any forger of our scheme.

Multi-state logic presents a promising avenue for more-than-Moore scaling, since efficient implementation of multi-valued logic (MVL) can significantly reduce switching and interconnection requirements and result in significant benefits compared to binary CMOS. So far, traditional approaches lag behind binary CMOS due to: (a) reliance on logic decomposition approaches [4][5][6] that result in many multi-valued minterms [4], complex polynomials [5], and decision diagrams [6], which are difficult to implement, and (b) emulation of multi-valued computation and communication through binary switches and medium that require data conversion, and large circuits. In this paper, we propose a fundamentally different approach for MVL decomposition, merging concepts from data science and nanoelectronics to tackle the problems, (a) First, we do linear regression on all inputs and outputs of a multivalued function, and find an expression that fits most input and output combinations. For unmatched combinations, we do successive regressions to find linear expressions. Next, using our novel visual pattern matching technique, we find conditions based on input and output conditions to select each expression. These expressions along with associated selection criteria ensure that for all possible inputs of a specific function, correct output can be reached. Our selection of regression model to find linear expressions, coefficients and conditions allow efficient hardware implementation. We discuss an approach for solving problem (b) and show an example of quaternary sum circuit. Our estimates show 65.6% saving of switching components compared with a 4-bit CMOS adder.

EPC Gen2 tags are working as international RFID standards for the use in the supply chain worldwide, such tags are computationally weak devices and unable to perform even basic symmetric-key cryptographic operations. For this reason, to implement robust and secure pseudo-random number generators (PRNG) is a challenging issue for low-cost Radio-frequency identification (RFID) tags. In this paper, we study the security of LFSR-based PRNG implemented on EPC Gen2 tags and exploit LFSR-based PRNG to provide a better constructions. We provide a cryptanalysis against the J3Gen which is LFSR-based PRNG and proposed by Sugei et al. [1], [2] for EPC Gen2 tags using distinguish attack and make observations on its input using NIST randomness test. We also test the PRNG in EPC Gen2 RFID Tags by using the NIST SP800-22. As a counter-measure, we propose two modified models based on the security analysis results. We show that our results perform better than J3Gen in terms of computational and statistical property.

Todays' era of internet-of-things, cloud computing and big data centers calls for more fresh graduates with expertise in digital data processing techniques such as compression, encryption and error correcting codes. This paper describes a project-based elective that covers these three main digital data processing techniques and can be offered to three different undergraduate majors electrical and computer engineering and computer science. The course has been offered successfully for three years. Registration statistics show equal interest from the three different majors. Assessment data show that students have successfully completed the different course outcomes. Students' feedback show that students appreciate the knowledge they attain from this elective and suggest that the workload for this course in relation to other courses of equal credit is as expected.

This paper proposes a modified empirical-mode decomposition (EMD) filtering-based adaptive dynamic phasor estimation algorithm for the removal of exponentially decaying dc offset. Discrete Fourier transform does not have the ability to attain the accurate phasor of the fundamental frequency component in digital protective relays under dynamic system fault conditions because the characteristic of exponentially decaying dc offset is not consistent. EMD is a fully data-driven, not model-based, adaptive filtering procedure for extracting signal components. But the original EMD technique has high computational complexity and requires a large data series. In this paper, a short data series-based EMD filtering procedure is proposed and an optimum hermite polynomial fitting (OHPF) method is used in this modified procedure. The proposed filtering technique has high accuracy and convergent speed, and is greatly appropriate for relay applications. This paper illustrates the characteristics of the proposed technique and evaluates its performance by computer-simulated signals, PSCAD/EMTDC-generated signals, and real power system fault signals.

As the ubiquity of smartphones increases we see an increase in the popularity of location based services. Specifically, online social networks provide services such as alerting the user of friend co-location, and finding a user's k nearest neighbors. Location information is sensitive, which makes privacy a strong concern for location based systems like these. We have built one such service that allows two parties to share location information privately and securely. Our system allows every user to maintain and enforce their own policy. When one party, (Alice), queries the location of another party, (Bob), our system uses homomorphic encryption to test if Alice is within Bob's policy. If she is, Bob's location is shared with Alice only. If she is not, no user location information is shared with anyone. Due to the importance and sensitivity of location information, and the easily deployable design of our system, we offer a useful, practical, and important system to users. Our main contribution is a flexible, practical protocol for private proximity testing, a useful and efficient technique for representing location values, and a working implementation of the system we design in this paper. It is implemented as an Android application with the Facebook online social network used for communication between users.

The trusted network connection is a hot spot in trusted computing field and the trust measurement and access control technology are used to deal with network security threats in trusted network. But the trusted network connection lacks fine-grained states and real-time measurement support for the client and the authentication mechanism is difficult to apply in the trusted network connection, it is easy to cause the loss of identity privacy. In order to solve the above-described problems, this paper presents a trust measurement scheme suitable for clients in the trusted network, the scheme integrates the following attributes such as authentication mechanism, state measurement, and real-time state measurement and so on, and based on the authentication mechanism and the initial state measurement, the scheme uses the real-time state measurement as the core method to complete the trust measurement for the client. This scheme presented in this paper supports both static and dynamic measurements. Overall, the characteristics of this scheme such as fine granularity, dynamic, real-time state measurement make it possible to make more fine-grained security policy and therefore it overcomes inadequacies existing in the current trusted network connection.

Explicit formulae and complexities of bit-parallel GF(2n) squarers for a new class of irreducible pentanomials xn + xn-1 + xk + x + 1, where n is odd and 1 <; k <; (n - 1)/2 are presented. The squarer is based on the generalised polynomial basis of GF(2n). Its gate delay matches the best results, whereas its XOR gate complexity is n + 1, which is only about two thirds of the current best results.