Biblio

With the explosive development of big data, it is necessary to sort the data according to their importance or priorities. The sources with different importance levels can be modeled by the multilevel diversity coding systems (MDCS). Another trend in future communication networks, say 5G wireless networks and Internet of Things, is that users may obtain their data from all available sources, even from devices belonging to other users. Then, the privacy of data becomes a crucial issue. In a recent work by Li et al., the secure asymmetric MDCS (S-AMDCS) with wiretap channels was investigated, where the wiretapped messages do not leak any information about the sources (i.e. perfect secrecy). It was shown that superposition (source-separate coding) is not optimal for the general S-AMDCS and the exact full secure rate region was proved for a class of S-AMDCS. In addition, a bound on the key size of the secure rate region was provided as well. As a further step on the SAMDCS problem, this paper mainly focuses on the key size characterization. Specifically, the constraints on the key size of superposition secure rate region are proved and a counterexample is found to show that the bound on the key size of the exact secure rate region provided by Li et al. is not tight. In contrast, tight necessary and sufficient constraints on the secrecy key size of the counterexample, which is the four-encoder S-AMDCS, are proved.

We determine the semantic security capacity for quantum wiretap channels. We extend methods for classical channels to quantum channels to demonstrate that a strongly secure code guarantees a semantically secure code with the same secrecy rate. Furthermore, we show how to transform a non-secure code into a semantically secure code by means of biregular irreducible functions (BRI functions). We analyze semantic security for classical-quantum channels and for quantum channels.

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.

{The secure exact-repair regenerating codes are studied, for distributed storage systems with parameters (n

An equivalence was shown between network coding and index coding. The equivalence allows for a network code for any given network-coding instance to be translated to an index code for a suitably constructed index-coding instance, and vice versa. The equivalence also holds for the opposite direction. A secure version of the equivalence in the presence of eavesdroppers was proven for the case where there is no decoding error and no information leakage to the eavesdroppers. For the case of non-zero decoding error and non-zero leakage, three out of the four directions required for an equivalence were proven. This paper proves the last direction, thereby completing the equivalence between secure network coding and secure index coding.

Ze the quality of channels into either completely noisy or noieseless channels. This paper presents extrinsic information transfer (EXIT) analysis for iterative decoding of Polar codes to reveal the mechanism of channel transformation. The purpose of understanding the transformation process are to comprehend the placement process of information bit and frozen bit and to comprehend the security standard of Polar codes. Mutual information derived based on the concept of EXIT chart for check nodes and variable nodes of low density parity check (LDPC) codes and applied to Polar codes. This paper explores the quality of the polarized channels in finite blocklength. The finite block-length is of our interest since in the fifth telecommunications generation (5G) the block length is limited. This paper reveals the EXIT curve changes of Polar codes and explores the polarization characteristics, thus, high value of mutual informations for frozen bit are needed to be detectable. If it is the other way, the error correction capability of Polar codes would be drastically decreases. These results are expected to be a reference for developments of Polar codes for 5G technologies and beyond.

In the paradigm of network coding, information-theoretic security is considered in the presence of wiretappers, who can access one arbitrary edge subset up to a certain size, referred to as the security level. Secure network coding is applied to prevent the leakage of the source information to the wiretappers. In this paper, we consider the problem of secure network coding for flexible pairs of information rate and security level with any fixed dimension (equal to the sum of rate and security level). We present a novel approach for designing a secure linear network code (SLNC) such that the same SLNC can be applied for all the rate and security-level pairs with the fixed dimension. We further develop a polynomial-time algorithm for efficient implementation and prove that there is no penalty on the required field size for the existence of SLNCs in terms of the best known lower bound by Guang and Yeung. Finally, by applying our approach as a crucial building block, we can construct a family of SLNCs that not only can be applied to all possible pairs of rate and security level but also share a common local encoding kernel at each intermediate node in the network.

Software security is a major concern of the developers who intend to deliver a reliable software. Although there is research that focuses on vulnerability prediction and discovery, there is still a need for building security-specific metrics to measure software security and vulnerability-proneness quantitatively. The existing methods are either based on software metrics (defined on the physical characteristics of code; e.g. complexity or lines of code) which are not security-specific or some generic patterns known as nano-patterns (Java method-level traceable patterns that characterize a Java method or function). Other methods predict vulnerabilities using text mining approaches or graph algorithms which perform poorly in cross-project validation and fail to be a generalized prediction model for any system. In this paper, we envision to construct an automated framework that will assist developers to assess the security level of their code and guide them towards developing secure code. To accomplish this goal, we aim to refine and redefine the existing nano-patterns and software metrics to make them more security-centric so that they can be used for measuring the software security level of a source code (either file or function) with higher accuracy. In this paper, we present our visionary approach through a series of three consecutive studies where we (1) will study the challenges of the current software metrics and nano-patterns in vulnerability prediction, (2) will redefine and characterize the nano-patterns and software metrics so that they can capture security-specific properties of code and measure the security level quantitatively, and finally (3) will implement an automated framework for the developers to automatically extract the values of all the patterns and metrics for the given code segment and then flag the estimated security level as a feedback based on our research results. We accomplished some preliminary experiments and presented the results which indicate that our vision can be practically implemented and will have valuable implications in the community of software security.

The presented method of encoding and steganographic embedding of a series of bits for the hidden message was first developed by modifying the digital platform (bases) of the elements of the image container. Unlike other methods, steganographic coding and embedding is accomplished by changing the elements of the image fragment, followed by the formation of code structures for the established structure of the digital representation of the structural elements of the image media image. The method of estimating quantitative indicators of embedded critical data is presented. The number of bits of the container for the developed method of steganographic coding and embedding of critical information is estimated. The efficiency of the presented method is evaluated and the comparative analysis of the value of the embedded digital data in relation to the method of weight coefficients of the discrete cosine transformation matrix, as well as the comparative analysis of the developed method of steganographic coding, compared with the Koch and Zhao methods to determine the embedded data resistance against attacks of various types. It is determined that for different values of the quantization coefficient, the most critical are the built-in containers of critical information, which are built by changing the part of the digital video data platform depending on the size of the digital platform and the number of bits of the built-in container.

In recent years, Edge Computing (EC) has attracted increasing attention for its advantages in handling latencysensitive and compute-intensive applications. It is becoming a widespread solution to solve the last mile problem of cloud computing. However, in actual EC deployments, data confidentiality becomes an unignorable issue because edge devices may be untrusted. In this paper, a secure and efficient edge computing scheme based on linear coding is proposed. Generally, linear coding can be utilized to achieve data confidentiality by encoding random blocks with original data blocks before they are distributed to unreliable edge nodes. However, the addition of a large amount of irrelevant random blocks also brings great communication overhead and high decoding complexities. In this paper, we focus on the design of secure coded edge computing using orthogonal vector to protect the information theoretic security of the data matrix stored on edge nodes and the input matrix uploaded by the user device, while to further reduce the communication overhead and decoding complexities. In recent years, Edge Computing (EC) has attracted increasing attention for its advantages in handling latencysensitive and compute-intensive applications. It is becoming a widespread solution to solve the last mile problem of cloud computing. However, in actual EC deployments, data confidentiality becomes an unignorable issue because edge devices may be untrusted. In this paper, a secure and efficient edge computing scheme based on linear coding is proposed. Generally, linear coding can be utilized to achieve data confidentiality by encoding random blocks with original data blocks before they are distributed to unreliable edge nodes. However, the addition of a large amount of irrelevant random blocks also brings great communication overhead and high decoding complexities. In this paper, we focus on the design of secure coded edge computing using orthogonal vector to protect the information theoretic security of the data matrix stored on edge nodes and the input matrix uploaded by the user device, while to further reduce the communication overhead and decoding complexities.

Matrices as mathematical models have been used in each branch of scientific fields for hundred years. We propose a new type of matrices, called topological coding matrices (Topcode-matrices). Topcode-matrices show us the following advantages: Topcode-matrices can be saved in computer easily and run quickly in computation; since a Topcode-matrix corresponds two or more Topsnut-gpws, so Topcode-matrices can be used to encrypt networks such that the encrypted networks have higher security; Topcode-matrices can be investigated and applied by people worked in more domains; Topcode-matrices can help us to form new operations, new parameters and new topics of graph theory, such as vertex/edge splitting operations and connectivities of graphs. Several properties and applications on Topcode-matrices, and particular Topcode-matrices, as well as unknown problems are introduced.

In a linear code, a code symbol with (r, δ)-locality can be repaired by accessing at most r other code symbols in case of at most δ - 1 erasures. A q-ary (n, k, r, δ) locally repairable codes (LRC) in which every code symbol has (r, δ)-locality is said to be optimal if it achieves the Singleton-like bound derived by Prakash et al.. In this paper, we study the classification of optimal ternary (n, k, r, δ)-LRCs (δ \textbackslashtextgreater 2). Firstly, we propose an upper bound on the minimum distance of optimal q-ary LRCs in terms of the field size. Then, we completely determine all the 6 classes of possible parameters with which optimal ternary (n, k, r, δ)-LRCs exist. Moreover, explicit constructions of all these 6 classes of optimal ternary LRCs are proposed in the paper.

It is investigated how to achieve semantic security for the wiretap channel. A new type of functions called biregular irreducible (BRI) functions, similar to universal hash functions, is introduced. BRI functions provide a universal method of establishing secrecy. It is proved that the known secrecy rates of any discrete and Gaussian wiretap channel are achievable with semantic security by modular wiretap codes constructed from a BRI function and an error-correcting code. A characterization of BRI functions in terms of edge-disjoint biregular graphs on a common vertex set is derived. This is used to study examples of BRI functions and to construct new ones.

{1 We present a construction for exact-repair regenerating codes with an information-theoretic secrecy guarantee against an eavesdropper with access to the content of (up to) ℓ nodes. The proposed construction works for the entire range of per-node storage and repair bandwidth for any distributed storage system with parameters (n

Wireless technology has seen a tremendous growth in the recent past. Orthogonal Frequency Division Multiplexing (OFDM) modulation scheme has been utilized in almost all the advanced wireless techniques because of the advantages it offers. Hence in this aspect, SystemVue based OFDM transceiver has been developed with AWGN as the channel noise. To mitigate the channel noise Convolutional code with Viterbi decoder has been depicted. Further to protect the information from the malicious users the data is scrambled with the aid of gold codes. The performance of the transceiver is analysed through various Bit Error Rate (BER) versus Signal to Noise Ratio (SNR) graphs.

With an increasing number of wireless devices, the risk of being eavesdropped increases as well. From information theory, it is well known that wiretap codes can asymptotically achieve vanishing decoding error probability at the legitimate receiver while also achieving vanishing leakage to eavesdroppers. However, under finite blocklength, there exists a tradeoff among different parameters of the transmission. In this work, we propose a flexible wiretap code design for Gaussian wiretap channels under finite blocklength by neural network autoencoders. We show that the proposed scheme has higher flexibility in terms of the error rate and leakage tradeoff, compared to the traditional codes.

We propose a serverless computing mechanism for distributed computation based on polar codes. Serverless computing is an emerging cloud based computation model that lets users run their functions on the cloud without provisioning or managing servers. Our proposed approach is a hybrid computing framework that carries out computationally expensive tasks such as linear algebraic operations involving large-scale data using serverless computing and does the rest of the processing locally. We address the limitations and reliability issues of serverless platforms such as straggling workers using coding theory, drawing ideas from recent literature on coded computation. The proposed mechanism uses polar codes to ensure straggler-resilience in a computationally effective manner. We provide extensive evidence showing polar codes outperform other coding methods. We have designed a sequential decoder specifically for polar codes in erasure channels with full-precision input and outputs. In addition, we have extended the proposed method to the matrix multiplication case where both matrices being multiplied are coded. The proposed coded computation scheme is implemented for AWS Lambda. Experiment results are presented where the performance of the proposed coded computation technique is tested in optimization via gradient descent. Finally, we introduce the idea of partial polarization which reduces the computational burden of encoding and decoding at the expense of straggler-resilience.

Nowadays public-key cryptography is based on number theory problems, such as computing the discrete logarithm on an elliptic curve or factoring big integers. Even though these problems are considered difficult to solve with the help of a classical computer, they can be solved in polynomial time on a quantum computer. Which is why the research community proposed alternative solutions that are quantum-resistant. The process of finding adequate post-quantum cryptographic schemes has moved to the next level, right after NIST's announcement for post-quantum standardization. One of the oldest quantum-resistant proposition goes back to McEliece in 1978, who proposed a public-key cryptosystem based on coding theory. It benefits of really efficient algorithms as well as a strong mathematical background. Nonetheless, its security has been challenged many times and several variants were cryptanalyzed. However, some versions remain unbroken. In this paper, we propose to give some background on coding theory in order to present some of the main flawless in the protocols. We analyze the existing side-channel attacks and give some recommendations on how to securely implement the most suitable variants. We also detail some structural attacks and potential drawbacks for new variants.

Since the security and fault tolerance is the two important metrics of the data storage, it brings both opportunities and challenges for distributed data storage and transaction. The traditional transaction system of storage resources, which generally runs in a centralized mode, results in high cost, vendor lock-in, single point failure risk, DDoS attack and information security. Therefore, this paper proposes a distributed transaction method for cloud storage based on smart contract. First, to guarantee the fault tolerance and decrease the storing cost for erasure coding, a VCG-based auction mechanism is proposed for storage transaction, and we deploy and implement the proposed mechanism by designing a corresponding smart contract. Especially, we address the problem - how to implement a VCG-like mechanism in a blockchain environment. Based on private chain of Ethereum, we make the simulations for proposed storage transaction method. The results showed that proposed transaction model can realize competitive trading of storage resources, and ensure the safe and economic operation of resource trading.

Program analysis on binary code is considered as difficult because one has to resolve destinations of indirect jumps. However, there is another difficulty of context-dependency that matters when one processes binary programs that are not compiler generated. In this paper, we propose a novel approach for tackling these difficulties and describe a way to reconstruct a control flow from a binary program with no extra assumptions than the operational meaning of machine instructions.

In modern societies, critical services such as transportation, power supply, water treatment and distribution are strongly dependent on Industrial Control Systems (ICS). As technology moves along, new features improve services provided by such ICS. On the other hand, this progress also introduces new risks of cyber attacks due to the multiple direct and indirect dependencies between cyber and physical components of such systems. Performing rigorous security tests and risk analysis in these critical systems is thus a challenging task, because of the non-trivial interactions between digital and physical assets and the domain-specific knowledge necessary to analyse a particular system. In this work, we propose a methodology to model and analyse a System Under Test (SUT) as a data flow graph that highlights interactions among internal entities throughout the SUT. This model is automatically extracted from production code available in Programmable Logic Controllers (PLCs). We also propose a reachability algorithm and an attack diagram that will emphasize the dependencies between cyber and physical domains, thus enabling a human analyst to gauge various attack vectors that arise from subtle dependencies in data and information propagation. We test our methodology in a functional water treatment testbed and demonstrate how an analyst could make use of our designed attack diagrams to reason on possible threats to various targets of the SUT.

The Advanced Encryption Standard (AES) enables secure transmission of confidential messages. Since its invention, there have been many proposed attacks against the scheme. For example, one can inject errors or faults to acquire the encryption keys. It has been shown that the AES algorithm itself does not provide a protection against these types of attacks. Therefore, additional techniques like error control codes (ECCs) have been proposed to detect active attacks. However, not all the proposed solutions show the adequate efficacy. For instance, linear ECCs have some critical limitations, especially when the injected errors are beyond their fault detection or tolerance capabilities. In this paper, we propose a new method based on a non-linear code to protect all four internal stages of the AES hardware implementation. With this method, the protected AES system is able to (a) detect all multiplicity of errors with a high probability and (b) correct them if the errors follow certain patterns or frequencies. Results shows that the proposed method provides much higher security and reliability to the AES hardware implementation with minimal overhead.

Network coding has become a promising approach to improve the communication capability for WSN, which is vulnerable to malicious attacks. There are some solutions, including cryptographic and information-theory schemes, just can thwart data pollution attacks but are not able to detect replay attacks. In the paper, we present a lightweight timestamp-based message authentication code method, called as TMAC. Based on TMAC and the time synchronization technique, the proposed detection scheme can not only resist pollution attacks but also defend replay attacks simultaneously. Finally

The most promising way to improve the performance of dynamic information-flow tracking (DIFT) for machine code is to only track instructions when they process tainted data. Unfortunately, prior approaches to on-demand DIFT are a poor match for modern mobile platforms that rely heavily on parallelism to provide good interactivity in the face of computationally intensive tasks like image processing. The main shortcoming of these prior efforts is that they cannot support an arbitrary mix of parallel threads due to the limitations of page protections. In this paper, we identify parallel permissions as a key requirement for multithreaded, on-demand native DIFT, and we describe the design and implementation of a system called SandTrap that embodies this approach. Using our prototype implementation, we demonstrate that SandTrap's native DIFT overhead is proportional to the amount of tainted data that native code processes. For example, in the photo-sharing app Instagram, SandTrap's performance is close to baseline (1x) when the app does not access tainted data. When it does, SandTrap imposes a slowdown comparable to prior DIFT systems (\textasciitilde8x).

Secure network coding realizes the secrecy of the message when the message is transmitted via noiseless network and a part of edges or a part of intermediate nodes are eavesdropped. In this framework, if the channels of the network has noise, we apply the error correction to noisy channel before applying the secure network coding. In contrast, secure physical layer network coding is a method to securely transmit a message by a combination of coding operation on nodes when the network is given as a set of noisy channels. In this paper, we give several examples of network, in which, secure physical layer network coding realizes a performance that cannot be realized by secure network coding.