In this paper we define the overflow problem of a network coding storage system in which the encoding parameter and the storage parameter are mismatched. Through analyses and experiments, we first show the impacts of the overflow problem in a network coding scheme, which not only waste storage spaces, but also degrade coding efficiency. To avoid the overflow problem, we then develop the network coding based secure storage (NCSS) scheme. Thanks to considering both security and storage requirements in encoding procedures and distributed architectures, the NCSS can improve the performance of a cloud storage system from both the aspects of storage cost and coding processing time. We analyze the maximum allowable stored encoded data under the perfect secrecy criterion, and provide the design guidelines for the secure cloud storage system to enhance coding efficiency and achieve the minimal storage cost.
The secrecy capacity for a network-coded cloud storage system was investigated in @cite_10 @cite_16 , where the secrecy capacity is defined as the maximum amount of data that can be securely stored under the perfect secrecy condition. The perfect secrecy condition ensure the eavesdropper cannot obtain any information of source data. The secrecy capacity for nodes with different storage capacities was derived in @cite_12 . The coding scheme that can achieve the storage upper bound of secrecy capacity was proposed in @cite_23 . The maximum data size being stored under the perfect secrecy condition for any number of eavesdropped nodes was determined in @cite_0 . The authors of @cite_21 considered how to achieve the information-theoretical secrecy when an eavesdropper can access some data in the storage nodes.
@cite_21 @cite_0 @cite_23 @cite_16 @cite_10 @cite_12
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We address the problem of securing distributed storage systems against passive eavesdroppers that can observe a limited number of storage nodes. An important aspect of these systems is node failures over time, which demand a repair mechanism aimed at maintaining a targeted high level of system reliability. If an eavesdropper observes a node that is added to the system to replace a failed node, it will have access to all the data downloaded during repair, which can potentially compromise the entire information in the system.We are interested in determining the secrecy capacity of distributed storage systems under repair dynamics, i.e., the maximum amount of data that can be securely stored and made available to a legitimate user without revealing any information to any eavesdropper. We derive a general upper bound on the secrecy capacity and show that this bound is tight for the bandwidth-limited regime which is of importance in scenarios such as peer-to-peer distributed storage systems. We also provide a simple explicit code construction that achieves the capacity for this regime. In this paper, we revisit the problem of characterizing the secrecy capacity of minimum storage regenerating (MSR) codes under the passive @math -eavesdropper model, where the eavesdropper has access to data stored on @math nodes and the repair data for an additional @math nodes. We study it from the information-theoretic perspective. First, some general properties of MSR codes as well as a simple and generally applicable upper bound on secrecy capacity are given. Second, a new concept of stable MSR codes is introduced, where the stable property is shown to be closely linked with secrecy capacity. Finally, a comprehensive and explicit result on secrecy capacity in the linear MSR scenario is present, which generalizes all related works in the literature and also predicts certain results for some unexplored linear MSR codes. This paper addresses the issue of securing information stored on a distributed storage system from a passive eavesdropping attack. The security notion is perfect secrecy, i.e., the system is said to be secure only if the mutual information between the stored information and the observations at the adversary is zero. The paper summarizes state of the art on securing repair-efficient distributed storage systems. Then, storage systems that employ locally repairable codes with minimum bandwidth regenerating codes as local codes (MBR-LRCs) are investigated. A secure file size upper bound and a construction of secure MBR-LRCs are provided. These two are shown to match under special cases, establishing the secrecy capacity of these systems. We derive single-letter characterizations of (strong) secrecy capacities for models with an arbitrary number of terminals, each of which observes a distinct component of a discrete memoryless multiple source, with unrestricted and interactive public communication permitted between the terminals. A subset of these terminals can serve as helpers for the remaining terminals in generating secrecy. According to the extent of an eavesdropper's knowledge, three kinds of secrecy capacity are considered: secret key (SK), private key (PK), and wiretap secret key (WSK) capacity. The characterizations of the SK and PK capacities highlight the innate connections between secrecy generation and multiterminal source coding without secrecy requirements. A general upper bound for WSK capacity is derived which is tight in the case when the eavesdropper can wiretap noisy versions of the components of the underlying multiple source, provided randomization is permitted at the terminals. These secrecy capacities are seen to be achievable with noninteractive communication between the terminals. The achievability results are also shown to be universal. The problem of securing data against eavesdropping in distributed storage systems is studied. The focus is on systems that use linear codes and implement exact repair to recover from node failures. The maximum file size that can be stored securely is determined for systems in which all the available nodes help in repair (i.e., repair degree d = n -1, where n is the total number of nodes) and for any number of compromised nodes. Similar results in the literature are restricted to the case of at most two compromised nodes. Moreover, new explicit upper bounds are given on the maximum secure file size for systems with d <; n - 1. The key ingredients for the contribution of this paper are new results on subspace intersection for the data downloaded during repair. The new bounds imply the interesting fact that the maximum amount of data that can be stored securely decreases exponentially with the number of compromised nodes. Whether this exponential decrease is fundamental or is a consequence of the exactness and linearity constraints remains an open question. Abstract Until today, high-capacity is still one of important research parts in information hiding. After the secret information embedded is extracted, the demand for the image reversibility for the total recovery of the original object without any distortion goes high. This paper proposes a high capacity steganography using multilayer embedding (CRS), which can enhance the performance of information hiding system. The experimental results show the proposed CRS scheme has better performance than others. Moreover, the proposed CRS method can display the advantages of good quality image and low complexity of computation. In this paper, we consider the security of exact-repair regenerating codes operating at the minimum-storage-regenerating (MSR) point. The security requirement (introduced in Shah et. al.) is that no information about the stored data file must be leaked in the presence of an eavesdropper who has access to the contents of l 1 nodes as well as all the repair traffic entering a second disjoint set of l 2 nodes. We derive an upper bound on the size of a data file that can be securely stored that holds whenever l 2 ≤ d - k + 1. This upper bound proves the optimality of the product-matrix-based construction of secure MSR regenerating codes by Shah et. al. A user wants to retrieve a file from a database without revealing the identity of the file retrieved at the database, which is known as the problem of private information retrieval (PIR). If it is further required that the user obtains no information about the database other than the desired file, the concept of symmetric private information retrieval (SPIR) is introduced to guarantee privacy for both parties. In this paper, the problem of SPIR is studied for a database stored among N nodes in a distributed way, by using an (N, M)-MDS storage code. The information-theoretic capacity of SPIR, defined as the maximum number of information bits of the desired file retrieved per downloaded bit, for the coded database is derived. It is shown that the SPIR capacity for coded database is 1-M N, when the amount of the shared common randomness of distributed nodes (unavailable at the user) is at least M N-M times the file size. Otherwise, the SPIR capacity for the coded database equals zero. We consider the secret key generation problem when sources are randomly excited by the sender and there is a noiseless public discussion channel. Our setting is thus similar to recent works on channels with action-dependent states where the channel state may be influenced by some of the parties involved. We derive single-letter expressions for the secret key capacity through a type of source emulation analysis. We also derive lower bounds on the achievable reliability and secrecy exponents, i.e., the exponential rates of decay of the probability of decoding error and of the information leakage. These exponents allow us to determine a set of strongly-achievable secret key rates. For degraded eavesdroppers the maximum strongly-achievable rate equals the secret key capacity; our exponents can also be specialized to previously known results. In deriving our strong achievability results we introduce a coding scheme that combines wiretap coding (to excite the channel) and key extraction (to distill keys from residual randomness). The secret key capacity is naturally seen to be a combination of both source- and channel-type randomness. Through examples we illustrate a fundamental interplay between the portion of the secret key rate due to each type of randomness. We also illustrate inherent tradeoffs between the achievable reliability and secrecy exponents. Our new scheme also naturally accommodates rate limits on the public discussion. We show that under rate constraints we are able to achieve larger rates than those that can be attained through a pure source emulation strategy. This paper studies the secrecy capacity of unicast communication in a wireless erasure network setting in the presence of a wire-tapper. From an information-theoretic setting of perfect secrecy, both upper bounds and achievable secrecy rates are presented. Secrecy capacity is determined in closed form for a class of broadcast constrained erasure networks. The secrecy capacity is developed for a class of relay channels with orthogonal components and a passive eavesdropper node. The relay and destination receive signals from the source on two orthogonal channels such that the destination also receives transmissions from the relay on its channel. The eavesdropper can overhear either one or both of the orthogonal channels. Inner and outer bounds on the secrecy capacity are developed for both the discrete memoryless and the Gaussian channel models. For the discrete memoryless case, the secrecy capacity is shown to be achieved by a partial decode-and-forward (PDF) scheme when the eavesdropper can overhear only one of the two orthogonal channels. Two new outer bounds are presented for the Gaussian model using recent capacity results for a Gaussian multi-antenna channel with a multi-antenna eavesdropper. The outer bounds are shown to be tight for two sub-classes of channels. The first sub-class is one in which the source and relay are clustered and the eavesdropper overhears on only one of the two channels for which the PDF strategy is optimal. The second is a sub-class in which the source does not transmit to the relay for which a noise-forwarding strategy is optimal. Abstract In this paper, we proposes high payload reversible data hiding scheme using weighted matrix. Generate cover image by enlarge the size of original image using interpolation. Partition the original image into (3 × 3) pixel blocks and cover image into (5 × 5) blocks. Perform modular sum of entry-wise multiplication of an (3 × 3) original pixel block with same size shared predefined weighted matrix W . At most twelve multiplication operations are performed to embed 48 bits secret data within an (5 × 5) overlapped pixel block. In each operation, the data embedding position are identified and stored the positional value by modifying three least significant bits of the interleaved pixel of cover image to hide large amount of secret data. For i -th block i = 1, 2, …, we update the weighted matrix W i +1 as W i +1 = ( W i × κ − 1) mod 9, where gcd ( κ , 9) = 1. The original pixels are not effected during data embedding in our scheme which assure reversibility. The proposed scheme provides average embedding payload 2.97 bits per pixel (bpp) with good visual quality measured by peak signal to noise ratio (PSNR) guaranteed to be higher than 37.97 dB. Finally, we compare our scheme with other state-of-the-art methods and obtain reasonably better performance in terms of data embedding capacity. We consider the problem of secure distributed data storage under the paradigm of , in which no is leaked to the eavesdropper. More specifically, the eavesdropper cannot get any information about any individual message file or a small group of files. The key benefit of the weak security paradigm is that it incurs no loss in the storage capacity, which makes it practically appealing. In this paper, we present a coding scheme, using a coset coding based outer code and a Product-Matrix Minimum Bandwidth Regenerating code (proposed by ) as an inner code, that achieves weak security when the eavesdropper can observe any single storage node. We show that the proposed construction has good security properties and requires small finite field size. As Cloud Computing becomes prevalent, sensitive information are being increasingly centralized into the cloud. For the protection of data privacy, sensitive data has to be encrypted before outsourcing, which makes effective data utilization a very challenging task. Although traditional searchable encryption schemes allow users to securely search over encrypted data through keywords, these techniques support only boolean search, without capturing any relevance of data files. This approach suffers from two main drawbacks when directly applied in the context of Cloud Computing. On the one hand, users, who do not necessarily have pre-knowledge of the encrypted cloud data, have to post process every retrieved file in order to find ones most matching their interest, On the other hand, invariably retrieving all files containing the queried keyword further incurs unnecessary network traffic, which is absolutely undesirable in today's pay-as-you-use cloud paradigm. In this paper, for the first time we define and solve the problem of effective yet secure ranked keyword search over encrypted cloud data. Ranked search greatly enhances system usability by returning the matching files in a ranked order regarding to certain relevance criteria (e.g., keyword frequency), thus making one step closer towards practical deployment of privacy-preserving data hosting services in Cloud Computing. We first give a straightforward yet ideal construction of ranked keyword search under the state-of-the-art searchable symmetric encryption (SSE) security definition, and demonstrate its inefficiency. To achieve more practical performance, we then propose a definition for ranked searchable symmetric encryption, and give an efficient design by properly utilizing the existing cryptographic primitive, order-preserving symmetric encryption (OPSE). Thorough analysis shows that our proposed solution enjoys as-strong-as-possible" security guarantee compared to previous SSE schemes, while correctly realizing the goal of ranked keyword search. Extensive experimental results demonstrate the efficiency of the proposed solution. Maximum distance separable (MDS) codes are widely used in storage systems to protect against disk (node) failures. A node is said to have capacity l over some field F, if it can store that amount of symbols of the field. An (n, k, l) MDS code uses n nodes of capacity l to store k information nodes. The MDS property guarantees the resiliency to any n-k node failures. An optimal bandwidth (respectively, optimal access) MDS code communicates (respectively, accesses) the minimum amount of data during the repair process of a single failed node. It was shown that this amount equals a fraction of 1 (n - k) of data stored in each node. In previous optimal bandwidth constructions, l scaled polynomially with k in codes when the asymptotic rate is less than 1. Moreover, in constructions with a constant number of parities, i.e., when the rate approaches 1, l is scaled exponentially with k. In this paper, we focus on the case of linear codes with linear repair operations and constant number of parities n - k = r, and ask the following question: given the capacity of a node l what is the largest number of information disks k in an optimal bandwidth (respectively, access) (k + r, k, l) MDS code? We give an upper bound for the general case, and two tight bounds in the special cases of two important families of codes. The first is a family of codes with optimal update property, and the second is a family with optimal access property. Moreover, the bounds show that in some cases optimal-bandwidth codes have larger k than optimal-access codes, and therefore these two measures are not equivalent. Cloud storage services enable users to remotely access data in a cloud anytime and anywhere, using any device, in a pay-as-you-go manner. Moving data into a cloud offers great convenience to users since they do not have to care about the large capital investment in both the deployment and management of the hardware infrastructures. However, allowing a cloud service provider (CSP), whose purpose is mainly for making a profit, to take the custody of sensitive data, raises underlying security and privacy issues. To keep user data confidential against an untrusted CSP, a natural way is to apply cryptographic approaches, by disclosing the data decryption key only to authorized users. However, when a user wants to retrieve files containing certain keywords using a thin client, the adopted encryption system should not only support keyword searching over encrypted data, but also provide high performance. In this paper, we investigate the characteristics of cloud storage services and propose a secure and privacy preserving keyword searching (SPKS) scheme, which allows the CSP to participate in the decipherment, and to return only files containing certain keywords specified by the users, so as to reduce both the computational and communication overhead in decryption for users, on the condition of preserving user data privacy and user querying privacy. Performance analysis shows that the SPKS scheme is applicable to a cloud environment. In wireless cloud storage systems, the recovery failure probability depends on not only wireless channel conditions but also storage size of each distributed storage node. For an efficient utilization of limited storage capacity and the performance characterization of allocation strategies, we asymptotically analyze the recovery failure probability of a wireless cloud storage system with a sum storage capacity constraint for both high signal-to-noise ratio (SNR) regime and low SNR regime. Then, we find the optimal storage allocation strategy across distributed storage nodes in terms of the asymptotic recovery failure probability. Our analysis reveals that the maximal symmetric allocation is optimal for high SNR regime and the minimal allocation (with @math complete storage nodes and an incomplete storage node) is optimal for low SNR regime, where @math is the sum storage capacity. Based on the numerical investigation, we also show that in intermediate SNR regime, a balance allocation between the minimal allocation and the maximal symmetric allocation would not be required if we select one between them according to SNR. We consider distributed storage over two untrusted networks, whereby coding is used as a means to achieve a prescribed level of confidentiality. The key idea is to exploit the algebraic structure of the Vandermonde matrix to mix the input blocks, before they are stored in different locations. The proposed scheme ensures that eavesdroppers with access to only one of the networks are unable to decode any symbol even if they are capable of guessing some of the missing blocks. Information-theoretic techniques allow us to quantify the achievable level of confidentiality. Moreover, the proposed approach is shown to offer low complexity and optimal rate. We investigate the secrecy capacity of an ergodic fading wiretap channel when the main and eavesdropper channels are correlated. Assuming that the transmitter knows the full channel state information (CSI) (i.e., the channel gains from the transmitter to the legitimate receiver and eavesdropper), we quantify the loss of the secrecy capacity due to the correlation and investigate the asymptotic behavior of the secrecy capacity in the high signal-to-noise ratio (SNR) regime. While the ergodic capacity of fading channels grows logarithmically with SNR in general, we have found that the secrecy capacity converges to an upper-bound (a closed-form expression is derived) that will be shown to be a function of two channel parameters; the correlation coefficient and the ratio of the main to eavesdropper channel gains. From this, we are able to see how the two channel parameters affect the secrecy capacity and conclude that the excessively large signal power does not help to improve the secrecy capacity and the loss due to the correlation could be significant especially when the ratio of the main to eavesdropper channel gains is low. Suppose that Alice wishes to send messages to Bob through a communication channel C1, but her transmissions also reach an eavesdropper Eve through another channel C2. This is the wiretap channel model introduced by Wyner in 1975. The goal is to design a coding scheme that makes it possible for Alice to communicate both reliably and securely. Reliability is measured in terms of Bob's probability of error in recovering the message, while security is measured in terms of the mutual information between the message and Eve's observations. Wyner showed that the situation is characterized by a single constant Cs, called the secrecy capacity, which has the following meaning: for all e >; 0, there exist coding schemes of rate R ≥ Cs-e that asymptotically achieve the reliability and security objectives. However, his proof of this result is based upon a random-coding argument. To date, despite consider able research effort, the only case where we know how to construct coding schemes that achieve secrecy capacity is when Eve's channel C2 is an erasure channel, or a combinatorial variation thereof. Polar codes were recently invented by Arikan; they approach the capacity of symmetric binary-input discrete memoryless channels with low encoding and decoding complexity. In this paper, we use polar codes to construct a coding scheme that achieves the secrecy capacity for a wide range of wiretap channels. Our construction works for any instantiation of the wiretap channel model, as long as both C1 and C2 are symmetric and binary-input, and C2 is degraded with respect to C1. Moreover, we show how to modify our construction in order to provide strong security, in the sense defined by Maurer, while still operating at a rate that approaches the secrecy capacity. In this case, we cannot guarantee that the reliability condition will also be satisfied unless the main channel C1 is noiseless, although we believe it can be always satisfied in practice.