2,019 research outputs found
Coded Merkle Tree: Solving Data Availability Attacks in Blockchains
In this paper, we propose coded Merkle tree (CMT), a novel hash accumulator
that offers a constant-cost protection against data availability attacks in
blockchains, even if the majority of the network nodes are malicious. A CMT is
constructed using a family of sparse erasure codes on each layer, and is
recovered by iteratively applying a peeling-decoding technique that enables a
compact proof for data availability attack on any layer. Our algorithm enables
any node to verify the full availability of any data block generated by the
system by just downloading a byte block hash commitment and
randomly sampling bytes, where is the size of the data
block. With the help of only one connected honest node in the system, our
method also allows any node to verify any tampering of the coded Merkle tree by
just downloading bytes. We provide a modular library for CMT
in Rust and Python and demonstrate its efficacy inside the Parity Bitcoin
client.Comment: To appear in Financial Cryptography and Data Security (FC) 202
Tree-Based Parity Check for an Optimal Data Hiding Scheme
Abstract-Reducing distortion between the cover object and the stego object is an important issue for steganography. The tree-based parity check method is very efficient for hiding a message on image data due to its simplicity. Based on this approach, we propose a majority vote strategy that results in least distortion for finding a stego object. The lower embedding efficiency of our method is better than that of previous works when the hidden message length is relatively large
Energy Efficient Transmission over Space Shift Keying Modulated MIMO Channels
Energy-efficient communication using a class of spatial modulation (SM) that
encodes the source information entirely in the antenna indices is considered in
this paper. The energy-efficient modulation design is formulated as a convex
optimization problem, where minimum achievable average symbol power consumption
is derived with rate, performance, and hardware constraints. The theoretical
result bounds any modulation scheme of this class, and encompasses the existing
space shift keying (SSK), generalized SSK (GSSK), and Hamming code-aided SSK
(HSSK) schemes as special cases. The theoretical optimum is achieved by the
proposed practical energy-efficient HSSK (EE-HSSK) scheme that incorporates a
novel use of the Hamming code and Huffman code techniques in the alphabet and
bit-mapping designs. Experimental studies demonstrate that EE-HSSK
significantly outperforms existing schemes in achieving near-optimal energy
efficiency. An analytical exposition of key properties of the existing GSSK
(including SSK) modulation that motivates a fundamental consideration for the
proposed energy-efficient modulation design is also provided
Framework for reversible data hiding using cost-effective encoding system for video steganography
Importances of reversible data hiding practices are always higher in contrast to any conventional data hiding schemes owing to its capability to generate distortion free cover media. Review of existing approaches on reversible data hiding approaches shows variable scheme mainly focussing on the embedding mechanism; however, such schemes could be furthermore improved using encoding scheme for optimal embedding performance. Therefore, the proposed manuscript discusses about a cost-effective scheme where a novel encoding scheme has been used with larger block sizes which reduces the dependencies over larger number of blocks. Further a gradient-based image registration technique is applied to ensure higher quality of the reconstructed signal over the decoding end. The study outcome shows that proposed data hiding technique is proven better than existing data hiding scheme with good balance between security and restored signal quality upon extraction of data
Preserving privacy in edge computing
Edge computing or fog computing enables realtime services to smart application users by storing data and services at the edge of the networks. Edge devices in the edge computing handle data storage and service provisioning. Therefore, edge computing has become a  new norm for several delay-sensitive smart applications such as automated vehicles, ambient-assisted living, emergency response services, precision agriculture, and smart electricity grids. Despite having great potential, privacy threats are the main barriers to the success of edge computing. Attackers can leak private or sensitive information of data owners and modify service-related data for hampering service provisioning in edge computing-based smart applications. This research takes privacy issues of heterogeneous smart application data into account that are stored in edge data centers. From there, this study focuses on the development of privacy-preserving models for user-generated smart application data in edge computing and edge service-related data, such as Quality-of-Service (QoS) data, for ensuring unbiased service provisioning. We begin with developing privacy-preserving techniques for user data generated by smart applications using steganography that is one of the data hiding techniques. In steganography, user sensitive information is hidden within nonsensitive information of data before outsourcing smart application data, and stego data are produced for storing in the edge data center. A steganography approach must be reversible or lossless to be useful in privacy-preserving techniques. In this research, we focus on numerical (sensor data) and textual (DNA sequence and text) data steganography. Existing steganography approaches for numerical data are irreversible. Hence, we introduce a lossless or reversible numerical data steganography approach using Error Correcting Codes (ECC). Modern lossless steganography approaches for text data steganography are mainly application-specific and lacks imperceptibility, and DNA steganography requires reference DNA sequence for the reconstruction of the original DNA sequence. Therefore, we present the first blind and lossless DNA sequence steganography approach based on the nucleotide substitution method in this study. In addition, a text steganography method is proposed that using invisible character and compression based encoding for ensuring reversibility and higher imperceptibility.  Different experiments are conducted to demonstrate the justification of our proposed methods in these studies. The searching capability of the stored stego data is challenged in the edge data center without disclosing sensitive information. We present a privacy-preserving search framework for stego data on the edge data center that includes two methods. In the first method, we present a keyword-based privacy-preserving search method that allows a user to send a search query as a hash string. However, this method does not support the range query. Therefore, we develop a range search method on stego data using an order-preserving encryption (OPE) scheme. In both cases, the search service provider retrieves corresponding stego data without revealing any sensitive information. Several experiments are conducted for evaluating the performance of the framework. Finally, we present a privacy-preserving service computation framework using Fully Homomorphic Encryption (FHE) based cryptosystem for ensuring the service provider's privacy during service selection and composition. Our contributions are two folds. First, we introduce a privacy-preserving service selection model based on encrypted Quality-of-Service (QoS) values of edge services for ensuring privacy. QoS values are encrypted using FHE. A distributed computation model for service selection using MapReduce is designed for improving efficiency. Second, we develop a composition model for edge services based on the functional relationship among edge services for optimizing the service selection process. Various experiments are performed in both centralized and distributed computing environments to evaluate the performance of the proposed framework using a synthetic QoS dataset
Data Hiding and Its Applications
Data hiding techniques have been widely used to provide copyright protection, data integrity, covert communication, non-repudiation, and authentication, among other applications. In the context of the increased dissemination and distribution of multimedia content over the internet, data hiding methods, such as digital watermarking and steganography, are becoming increasingly relevant in providing multimedia security. The goal of this book is to focus on the improvement of data hiding algorithms and their different applications (both traditional and emerging), bringing together researchers and practitioners from different research fields, including data hiding, signal processing, cryptography, and information theory, among others
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