Information Retrieval Scheme Research Articles

Optimal intelligent information retrieval and reliable storage scheme for cloud environment and E-learning big data analytics

Optimal intelligent information retrieval and reliable storage scheme for cloud environment and E-learning big data analytics

ALMEGA-VIR: face video retrieval system

ABSTRACT The limitations of Content Based Video Retrieval (CBVR), such as large pools of video data, selection of features, limited processing capacity, and content-related issues, can be overcome by Deep Belief Neural Networks (DBNs). The search engine does the processing, and the results are effectively returned to the users. The deep learning model also has some comparable challenges to be solved at various levels. Typically, the selection of frames is one of the most essential tasks for a face retrieval system which is efficiently accomplished by using deep learning models. Also, the performance of recognition models highly depends on the selection of frames that include both low-level and high-level features from the given video sequence. This paper proposes ALPHA-TO-OMEGA (ALMEGA-VIR) Visual Information Retrieval scheme that analyzes the contents of the video file for a particular face and retrieves the user's relevant videos. VIR aims to solve the challenge of locating relevant pictures and videos based on a query. VIR can be based on text-based search, content-based search, and Mixed based search. VIR here focuses on content-based search approach. The YouTube Celebrities (YTC) dataset, the Youtube Face (YTF) dataset, and Honda / UCSD dataset are used in this work. The used dataset addresses issues such as illumination changes, occlusion, rotation, and scale. We propose an ALMEGA-VIR framework for visual novelty face identification for specific investigation and evaluation. The classification accuracy of the proposed ALMEGA-VIR model shows that 4% is more effective than traditional classifier algorithms such as SVM, Naïve Bayesian classifier, MLP and Random Forest classifier. A comparative study is also implemented with other existing works to check the superiority of the proposed method.

Information-theoretic privacy in federated submodel learning

We consider information-theoretic privacy in federated submodel learning, where a global server has multiple submodels. Compared to the privacy considered in the conventional federated submodel learning where secure aggregation is adopted for ensuring privacy, information-theoretic privacy provides the stronger protection on submodel selection by the local machine. We propose an achievable scheme that partially adopts the conventional private information retrieval (PIR) scheme that achieves the minimum amount of download. With respect to computation and communication overhead, we compare the achievable scheme with a naïve approach for federated submodel learning with information-theoretic privacy.

Asymmetric Consortium Blockchain and Homomorphically Polynomial-Based PIR for Secured Smart Parking Systems

In crowded cities, searching for the availability of parking lots is a herculean task as it results in the wastage of drivers’ time, increases air pollution, and traffic congestion. Smart parking systems facilitate the drivers to determine the information about the parking lot in real time and book them depending on the requirement. But the existing smart parking systems necessitate the drivers to reveal their sensitive information that includes their mobile number, personal identity, and desired destination. This disclosure of sensitive information makes the existing centralized smart parking systems more vulnerable to service providers’ security breaches, single points of failure, and bottlenecks. In this paper, an Improved Asymmetric Consortium Blockchain and Homomorphically Computing Univariate Polynomial-based private information retrieval (IACB-HCUPPIR) scheme is proposed to ensure parking lots’ availability with transparency security in a privacy-preserving smart parking system. In specific, an improved Asymmetric Consortium Blockchain is used for achieving secure transactions between different parties interacting in the smart parking environment. It further adopted the method of Homomorphically Computing Univariate Polynomial-based private information retrieval (HCUPPIR) scheme for preserving the location privacy of drivers. The results of IACB-HCUPPIR confirmed better results in terms of minimized computation and communication overload with throughput, latency, and response time with maximized drivers’ privacy preservation. Moreover, the proposed fully homomorphic algorithm (FHE) was compared against partial-homomorphic encryption (PHE) and technique without encryption and found that the proposed model has quick communication in allocating the parking slots starting with 24.3 s, whereas PHE starts allocating from 24.7 s and the technique without encryption starts at 27.4 s. Thus, we ensure the proposed model performs well in allocating parking slots with less time and high security with privacy preservation.

FrodoPIR: Simple, Scalable, Single-Server Private Information Retrieval

We design FrodoPIR — a highly configurable, stateful, single-server Private Information Retrieval (PIR) scheme that involves an offline phase that is completely client-independent. Coupled with small online overheads, it leads to much smaller amortized financial costs on the server-side than previous approaches. In terms of performance for a database of 1 million 1KB elements, FrodoPIR requires < 1 second for responding to a client query, has a server response size blow-up factor of < 3.6x, and financial costs are ~$1 for answering 100,000 client queries. Our experimental analysis is built upon a simple, non-optimized Rust implementation, illustrating that FrodoPIR is particularly suitable for deployments that involve large numbers of clients.

Communication Systems With Amplitude Detection: An Asymptotic Approach

Amplitude detection (AD) is a low-complexity nonlinear scheme for information retrieval, as it only considers the envelope of the received signal. This makes it ideal in applications with low-cost low-power devices such as the Internet of Things (IoT). We consider a basic Point-to-Point (P2P) setup and develop a unified analytical framework for the asymptotic symbol error rate (SER) performance of the maximum-likelihood (ML) decoder with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> -ary amplitude-shift keying (ASK). The developed framework is general and can be applied for a large class of fading channels. The SER can be characterized by two parameters: the diversity order and the coding gain at a sufficiently high signal-to-noise regime. We derive closed-form expressions for the exact diversity order along with a lower and upper bound on the coding gain. We show that the diversity order is equal to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula> for Nakagami- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula> fading, whereas for the other considered models, it is equal to one. We also prove that among all possible binary modulations with equal power, the modulation with one symbol equal to zero [i.e., on–off keying (OOK)] achieves the minimum asymptotic SER. The mathematical framework developed for the P2P setup is extended for cooperative relay networks. Specifically, we consider a basic amplify-and-forward (AF) three-node relay topology that employs AD at both the relay and the destination. We analytically derive the ML decoder and study asymptotic bounds on the SER by showing that the proposed AF-AD relay setup can be transformed into an equivalent P2P-AD with respect to the ML decoder.

Intermittent Private Information Retrieval With Application to Location Privacy

We study the problem of intermittent private information retrieval with multiple servers, in which a user consecutively requests one of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> messages from <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> replicated databases such that part of requests need to be protected while others do not need privacy. Motivated by the location privacy application, the correlation between requests is modeled by a Markov chain. We propose an intermittent private information retrieval scheme that concatenates an obfuscation scheme and a private information retrieval scheme for the time period when privacy is not needed, to prevent leakage incurred by the correlation over time. In the end, we illustrate how the proposed scheme for the problem of intermittent private information retrieval with Markov structure correlation can be applied to design a location privacy protection mechanism in the location privacy problem.

How to Delegate Computations: The Power of No-Signaling Proofs

We construct a 1-round delegation scheme (i.e., argument-system) for every language computable in time t = t ( n ), where the running time of the prover is poly ( t ) and the running time of the verifier is n · polylog ( t ). In particular, for every language in P we obtain a delegation scheme with almost linear time verification. Our construction relies on the existence of a computational sub-exponentially secure private information retrieval ( PIR ) scheme. The proof exploits a curious connection between the problem of computation delegation and the model of multi-prover interactive proofs that are sound against no-signaling (cheating) strategies , a model that was studied in the context of multi-prover interactive proofs with provers that share quantum entanglement, and is motivated by the physical principle that information cannot travel faster than light. For any language computable in time t = t ( n ), we construct a multi-prover interactive proof ( MIP ), that is, sound against no-signaling strategies, where the running time of the provers is poly ( t ), the number of provers is polylog ( t ), and the running time of the verifier is n · polylog ( t ). In particular, this shows that the class of languages that have polynomial-time MIP s that are sound against no-signaling strategies, is exactly EXP . Previously, this class was only known to contain PSPACE . To convert our MIP into a 1-round delegation scheme, we use the method suggested by Aiello et al. (ICALP, 2000), which makes use of a PIR scheme. This method lacked a proof of security. We prove that this method is secure assuming the underlying MIP is secure against no-signaling provers.

Multi-scale Information Retrieval for BIM using Hierarchical Structure Modelling and Natural Language Processing

Building Information Modelling (BIM) captures numerous information the life cycle of buildings. Information retrieval is one of fundamental tasks for BIM decision support systems. Currently, most of the BIM retrieval systems focused on querying existing BIM models from a BIM database, seldom studies explore the multi-scale information retrieval from a BIM model. This study proposes a multi-scale information retrieval scheme for BIM jointly using the hierarchical structure of BIM and Natural Language Processing (NLP). Firstly, a BIM Hierarchy Tree (BIH-Tree) model is constructed to interpret the hierarchical structure relations among BIM data according to Industry Foundation Class (IFC) specification. Secondly, technologies of NLP and International Framework for Dictionaries (IFD) are employed to parse and unify the queries. Thirdly, a novel information retrieval scheme is developed to find the multi-scale information associated with the unified queries. Finally, the retrieval method proposed in this study is applied to an engineering case, and the practical results show that the proposed method is effective.

Ring signature and improved multi‐transaction mode consortium blockchain‐based private information retrieval for privacy‐preserving smart parking system

SummaryIn big cities, the drivers face a major problem in identifying an optimal vacant parking space for their vehicles as the number of vehicles has rapidly grown over the recent years. This objective of determining the available parking space results in wastage of time, air pollution, and traffic congestion. Smart parking systems facilitate the driver to book parking slots and attain real‐time parking information. However, the existing smart parking solutions necessitate the disclosure of sensitive information like desired destination from the vehicle drivers. Moreover, the current smart parking solutions are highly centralized, making them vulnerable for launching privacy breaches by service providers and resulting in the issues of single‐point failure. In this paper, ring signature and improved multi‐transaction mode consortium blockchain‐based private information retrieval (RS‐IMTMCB‐PIR) scheme is proposed for privacy preserving in smart parking system. This RS‐IMTMCB‐PIR scheme initially utilizes an improved multi‐transaction mode consortium blockchain constructed by different number of parking lot owners in order to achieve maximized parking offers based on the factor of availability, transparency, and security. It incorporates an improved private information retrieval approach for protecting the location privacy of drivers and secretly retrieving the offers of parking from the improved multi‐transaction mode consortium blockchain. It further utilizes the benefits of ring signature for permitting the drivers in a potential anonymous authentication process that aids in available parking slot reservation. The simulation results of this proposed RS‐IMTMCB‐PIR scheme portrayed a predominant performance in ensuring maximized degree of drivers' privacy with reduced computation and communication overheads.

A survey on single server private information retrieval in a coding theory perspective

In this paper, we present a new perspective of single server private information retrieval (PIR) schemes by using the notion of linear error-correcting codes. Many of the known single server schemes are based on taking linear combinations between database elements and the query elements. Using the theory of linear codes, we develop a generic framework that formalizes all such PIR schemes. This generic framework provides an appropriate setup to analyze the security of such PIR schemes. In fact, we describe some known PIR schemes with respect to this code-based framework, and present the weaknesses of the broken PIR schemes in a unified point of view.

The Capacity of Single-Server Weakly-Private Information Retrieval

A private information retrieval (PIR) protocol guarantees that a user can privately retrieve files stored in a database without revealing any information about the identity of the requested file. Existing information-theoretic PIR protocols ensure perfect privacy, i.e., zero information leakage to the servers storing the database, but at the cost of high download. In this work, we present weakly-private information retrieval (WPIR) schemes that trade off perfect privacy to improve the download cost when the database is stored on a single server. We study the tradeoff between the download cost and information leakage in terms of mutual information (MI) and maximal leakage (MaxL) privacy metrics. By relating the WPIR problem to rate-distortion theory, the download-leakage function, which is defined as the minimum required download cost of all single-server WPIR schemes for a given level of information leakage and a fixed file size, is introduced. By characterizing the download-leakage function for the MI and MaxL metrics, the capacity of single-server WPIR is fully described.

Single-Server Private Information Retrieval Schemes are Equivalent to Locally Recoverable Coding Schemes

The Private Information Retrieval (PIR) problem has recently attracted a significant interest in the information-theory community. In this problem, a client wants to download one or more messages belonging to a database while protecting the identity of the downloaded message(s). In this article, we focus on the scenarios in which (i) the entire database is stored on a single server and (ii) the client has prior side information, namely a subset of messages unknown to the server. Such prior side information is necessary to enable efficient private information retrieval in the single server scenario. In the last decade, there has also been a significant interest in Locally Recoverable Codes (LRCs), a class of storage codes in which each symbol can be recovered from a limited number of other symbols. More recently, there is an interest in cooperative locally recoverable codes, i.e., codes in which multiple symbols can be recovered from a small set of other code symbols. The central problem in this context is given a set of code parameters to design an LRC scheme that includes a locally recoverable code along with encoding, decoding, and repair functions. The paper establishes an equivalence between the single-server PIR schemes and LRC schemes. In particular, we present explicit algorithms that transform a given PIR scheme into an LRC scheme and vice versa. We show that (i) PIR schemes for retrieving a single message are equivalent to classical LRC schemes; and (ii) PIR schemes for retrieving multiple messages are equivalent to cooperative LRC schemes. These equivalence results allow us to recover upper bounds on the download rate for PIR schemes, and to obtain a novel rate upper bound on cooperative LRC schemes. Our results cover schemes based on both linear and non-linear codes.

A novel index retrieval and query optimisation method for private information retrieval in location-based service application

Location-based service is a popular information and communications technology. Security, trust and privacy are the major concerns preventing the wide deployment of LBS. In this paper, we address privacy issues by employing computational private information retrieval schemes and highlight a few optimisation methods. We propose a novel index retrieval technique which helps the user to identify his grid ID and know the index value for the point-of-interest (POI) type of his interest, and an adaptive computation method (flip-optimisation) to reduce multiplication cost for PIR query used to retrieve the POI item at the specified index. The adaptive computation method proposed in this paper is generic and can be applied to any application which uses PIR protocol to access data privately. Our work empirically evaluated the proposed method by implementing the PIR prototype and found it suitable for a practical purpose.

Private Information Retrieval Schemes With Product-Matrix MBR Codes

A private information retrieval (PIR) scheme allows a user to retrieve a file from a database without revealing any information on the file being requested. As of now, PIR schemes have been proposed for several kinds of storage systems, including replicated and MDS-coded systems. However, the problem of constructing PIR schemes on regenerating codes has been sparsely considered. A regenerating code is a storage code whose codewords are distributed among nodes, enabling efficient storage of files, as well as low-bandwidth retrieval of files and repair of nodes. Minimum-bandwidth regenerating (MBR) codes define a family of regenerating codes allowing a node repair with optimal bandwidth. Rashmi, Shah, and Kumar obtained a large family of MBR codes using the product-matrix (PM) construction. In this work, a new PIR scheme over PM-MBR codes is designed. The inherent redundancy of the PM structure is used to reduce the download communication complexity of the scheme. A lower bound on the PIR capacity of MBR-coded PIR schemes is derived, showing an interesting storage space vs. PIR rate trade-off compared to existing PIR schemes with the same reconstruction capability. The present scheme also outperforms a recent PM-MBR PIR construction of Dorkson and Ng.

Capacity-achieving private information retrieval scheme with a smaller sub-packetization

<p style='text-indent:20px;'>Private information retrieval (PIR) allows a user to retrieve one out of <inline-formula><tex-math id="M1">\begin{document}$ M $\end{document}</tex-math></inline-formula> messages from <inline-formula><tex-math id="M2">\begin{document}$ N $\end{document}</tex-math></inline-formula> servers without revealing the identity of the desired message. Every message consists of <inline-formula><tex-math id="M3">\begin{document}$ L $\end{document}</tex-math></inline-formula> symbols (packets) from an additive group and the length <inline-formula><tex-math id="M4">\begin{document}$ L $\end{document}</tex-math></inline-formula> is called the sub-packetization. A PIR scheme with download cost (DC) <inline-formula><tex-math id="M5">\begin{document}$ D/L $\end{document}</tex-math></inline-formula> is implemented by querying <inline-formula><tex-math id="M6">\begin{document}$ D $\end{document}</tex-math></inline-formula> sums of the symbols to servers. We assume that each uncoded server can store up to <inline-formula><tex-math id="M7">\begin{document}$ tLM/N $\end{document}</tex-math></inline-formula> symbols, <inline-formula><tex-math id="M8">\begin{document}$ t\in\{1,2,\cdots,N\} $\end{document}</tex-math></inline-formula>. The minimum DC of storage constrained PIR was determined by Attia <i>et al.</i> in 2018 to be <inline-formula><tex-math id="M9">\begin{document}$ DC_{min} = 1+1/t+1/t^{2}+\cdots+1/t^{M-1} $\end{document}</tex-math></inline-formula>. The capacity of storage constrained PIR (equivalently, the reciprocal of minimum download cost) is the maximum number of bits of desired symbols that can be privately retrieved per bit of downloaded symbols. Tandon <i>et al.</i> designed a capacity-achieving PIR scheme with sub-packetization <inline-formula><tex-math id="M10">\begin{document}$ L' = {N\choose t}t^{M} $\end{document}</tex-math></inline-formula> of each message. In this paper, we design a PIR scheme with <inline-formula><tex-math id="M11">\begin{document}$ t $\end{document}</tex-math></inline-formula> times smaller sub-packetization <inline-formula><tex-math id="M12">\begin{document}$ L'/t $\end{document}</tex-math></inline-formula> and with the minimum DC for any parameters <inline-formula><tex-math id="M13">\begin{document}$ N, M, t $\end{document}</tex-math></inline-formula>. We also prove that <inline-formula><tex-math id="M14">\begin{document}$ t^{M-1} $\end{document}</tex-math></inline-formula> is a factor of sub-packetization <inline-formula><tex-math id="M15">\begin{document}$ L $\end{document}</tex-math></inline-formula> for any capacity-achieving PIR scheme from storage constrained servers.

Towards Efficient Information-Theoretic Function Secret Sharing

A $(t,r)$ -function secret sharing ( $(t,r)$ -FSS) scheme allows a dealer to secret-share a function $f$ among $r$ parties as $r$ secret keys $k_{1},\ldots,k_{r}$ such that for any input $x$ the parties can compute $r$ output shares that allow the reconstruction of $f(x)$ but any $\leq t$ of the parties cannot learn any information about $f$ . FSS schemes for point functions have been constructed under the name of distributed point functions (DPFs). The existing DPFs are computationally secure and based on the existence of PRGs or OWFs. As a result, the protocols where DPFs work as building blocks are computationally secure as well. In this paper, we study information-theoretically secure $(t,r)$ -FSS (called $(t,r)$ -itFSS) and propose a generic transformation from information-theoretic private information retrieval (PIR) schemes to itFSS schemes for point functions. We measure the efficiency of itFSS with its communication complexity, which can be defined as the total length of the secret keys and the output shares, maximized over the choices of $f$ and $x$ . By instantiating the generic transformation, we obtain $(t,r)$ -itFSS schemes for a variety of choices of $(t,r)$ , which have sublinear (in the functions’ domain size) communication complexity. How to make sure that the parties’ shares of $f(x)$ do not reveal more information than what needed to compute $f(x)$ is an interesting problem. An itFSS with this property is called function-private. In this paper, we also define a parameter called the mutual rate of itFSS in order to measure the amount of information that will be leaked by the parties’ output shares. We calculate the mutual rates for several specific itFSS schemes. We also define computational function privacy and propose a 2-party itFSS scheme with computational function privacy.

Private Coded Matrix Multiplication

In distributed computing system for the master-worker framework, an erasure code is able to mitigate the effects of slow workers, also called stragglers. The distributed computing system combined with coding is referred to as coded computation . For a matrix multiplication, we consider a variation of coded computation that ensures the master’s privacy from the workers, which is referred to as private coded matrix multiplication . In the private coded matrix multiplication, the master needs to compute a matrix multiplication on its own matrix and one of the matrices in a library exclusively shared by the external workers. After the master recovers the matrix multiplication through coded matrix multiplication, the workers should not know which matrix in the library was desired by the master, which implies that the master’s privacy is ensured. Our problem is a special case of linear private computation , where a linear combination of matrices in the library should be concealed. We propose a private coded matrix multiplication scheme, based on the conventional coded matrix multiplication scheme. In terms of computation time and communication load, we compare our proposed scheme with a conventional robust private information retrieval scheme and private computation schemes.

On Share Conversions for Private Information Retrieval

Beimel et al. in CCC 12’ put forward a paradigm for constructing Private Information Retrieval (PIR) schemes, capturing several previous constructions for servers. A key component in the paradigm, applicable to three-server PIR, is a share conversion scheme from corresponding linear three-party secret sharing schemes with respect to a certain type of “modified universal” relation. In a useful particular instantiation of the paradigm, they used a share conversion from -CNF over to three-additive sharing over for primes where and . The share conversion is with respect to the modified universal relation . They reduced the question of whether a suitable share conversion exists for a triple to the (in)solvability of a certain linear system over . Assuming a solution exists, they also provided a efficient (in ) construction of such a sharing scheme. They proved a suitable conversion exists for several triples of small numbers using a computer program; in particular, yielded the three-server PIR with the best communication complexity at the time. This approach quickly becomes infeasible as the resulting matrix is of size . In this work, we prove that the solvability condition holds for an infinite family of ’s, answering an open question of Beimel et al. Concretely, we prove that if and , then a conversion of the required form exists. We leave the full characterization of such triples, with potential applications to PIR complexity, to future work. Although larger (particularly with ) triples do not yield improved three-server PIR communication complexity via BIKO’s construction, a richer family of PIR protocols we obtain by plugging in our share conversions might have useful properties for other applications. Moreover, we hope that the analytic techniques for understanding the relevant matrices we developed would help to understand whether share conversion as above for , where m is a product of more than two (say three) distinct primes, exists. The general BIKO paradigm generalizes to work for such ’s. Furthermore, the linear condition in Beimel et al. generalizes to m’s, which are products of more than two primes, so our hope is somewhat justified. In case such a conversion does exist, plugging it into BIKO’s construction would lead to major improvement to the state of the art of three-server PIR communication complexity (reducing Communication Complexity (CC) in correspondence with certain matching vector families).

Private Information Retrieval Over Random Linear Networks

In this paper, the problem of providing privacy to users requesting data over a network from a distributed storage system (DSS) is considered. The DSS, which is considered as the multi-terminal destination of the network from the user's perspective, is encoded by a maximum rank distance (MRD) code to store the data on these multiple servers. A private information retrieval (PIR) scheme ensures that a user can request a file without revealing any information on which file is being requested to any of the servers. In this paper, a novel PIR scheme is proposed, allowing the user to recover a file from a storage system with low communication cost, while allowing some servers in the system to collude in the quest of revealing the identity of the requested file. The network is modeled as a random linear network, i.e., all nodes of the network forward random (unknown) linear combinations of incoming packets. Both error-free and erroneous random linear networks are considered.