Large volumes of data are being generated daily from IoT networks, healthcare, and many other applications, which makes secure, reliable, and cost-effective data storage a critical infrastructure of the computing system. Existing data storage largely depends on centralized clouds, which is not only costly but also vulnerable to single points of failure and other types of security attacks. Moreover, cloud providers will have full access to user data and revision history beyond user control. To provide data security, data encryption has to be used, which requires extensive computing power and cumbersome key management. Distributed storage system (DSS) is being widely viewed as a natural solution to future online data storage due to improved access time and lower storage cost. However, the existing DSS also has the limitations of low storage efficiency and weak data security. In this article, we investigate multi-layer code-based distributed data storage systems that can achieve inherit content confidentiality and optimal storage efficiency. Our comprehensive performance analysis shows that the optimal code can improve the feasible region in reliable data storage by 50% under various adversarial attack scenarios.

Regenerating code is a class of distributed storage codes that can optimally trade the bandwidth with the amount of data stored per node to repair a failed node. There are two extreme points in the optimal regenerating trade-off curve, which correspond to minimum-storage regenerating (MSR) and minimum-bandwidth regenerating (MBR). Recently, Reed-Solomon (RS) code based regenerating codes (RS-RC) were constructed under the product-matrix framework. It can also achieve the maximum distance separable (MDS) property in code regeneration and reconstruction. However, in case that the network is hostile and the storage nodes could be compromised or packets be modified, the storage capacity and the bandwidth required to regenerate or reconstruct the original file can be significantly affected. In this paper, we propose Hermitian code based regenerating codes (H-RC) by developing constructions under the product-matrix framework for minimum storage regenerating (H-MSR) and the minimum bandwidth regenerating (H-MBR). We also propose data regeneration and reconstruction algorithms for both H-MSR and H-MBR codes under both error-free and hostile networks. We demonstrate that the proposed algorithms can also successfully determine the erroneous decodings in hostile networks. Theoretical evaluation shows that our proposed H-RC can detect and correct more errors in hostile networks well beyond the RS-RC with the same code rate. Our analysis shows that the proposed H-RC have lower computational complexity than the RS-RC for both code regeneration and code reconstruction.

In the upcoming 5G era, many new types of networks will greatly expand the connectivity of the world such as vehicular ad hoc networks (VANETs), Internet of Things (IoT), and device‐to‐device communications (D2D). Network coding is a promising technology that can significantly improve the throughput and robustness of these emerging 5G multihop networks. However, network coding is generally very fragile to malicious attacks such as message content corruption and node compromise attacks. To take advantage of network coding in performance gain while refraining malicious network attacks is an interesting and challenging research issue. In this paper, we propose a new error‐detection and error‐correction (EDEC) scheme that can jointly detect and remove the malicious attacks based on the underlying error‐control scheme for general multihop networks that can model the 5G multihop networks. The proposed scheme can increase the throughput for network with pollution attacks compared to existing error‐detection based schemes. Then we propose a low‐density parity check (LDPC) decoding based EDEC (LEDEC) scheme. Our theoretical analysis demonstrates that the LEDEC scheme can further increase the throughput for heavily polluted network environments. We also provide extensive performance evaluation and simulation results to validate the proposed schemes. This research ensures the expected performance gain for the application of network coding in the 5G network under malicious pollution attacks.

Regenerating code is a class of distributed storage codes that can optimally trade the bandwidth required to repair a failed node with the amount of data stored per node. There are two optimal points in the regeneration tradeoff curve: the minimum storage regeneration code and the minimum bandwidth regeneration code. However, in hostile networks where the storage nodes may be compromised, the storage capacity of the network can be significantly affected. In this paper, we propose two optimal regenerating code constructions through rate-matching to combat this kind of adversarial attacks in hostile networks. We first develop a two-layer rate-matched regenerating code construction. By matching the parameters of the full rate code and the partial rate code, we can optimize the overall storage efficiency while maintaining the corrupted node detection probability. Through comprehensive analysis, we show that the two-layer rate-matched regenerating code can achieve 70% higher storage efficiency than the universally resilient regenerating code. We then propose an optimal m-layer regenerating code construction. While the principle remains the same as the two-layer code, it is designed to optimize the total number of detectable corrupted nodes of m layers from which the errors can be corrected under the constraint of any given code efficiency. Compared with the universally resilient regenerating code with the same rate, our m-layer code can detect 50% more corrupted nodes.

Regenerating code is a class of code very suitable for distributed storage systems, which can maintain optimal bandwidth and storage space. Two types of important regenerating code have been constructed: the minimum storage regeneration (MSR) code and the minimum bandwidth regeneration (MBR) code. However, in hostile networks where adversaries can compromise storage nodes, the storage capacity of the network can be significantly affected. In this paper, we propose a rate-matched MSR code that can combat against this kind of adversaries in hostile networks. We optimize the code parameters for given system requirements. Our comprehensive analysis shows that our code can detect and correct malicious nodes with higher storage efficiency compared to the normal error correction MSR code.

Distributed storage plays a crucial role in the current cloud computing framework. After the theoretical bound for distributed storage was derived by the pioneer work of the regenerating code, Reed-Solomon code based regenerating codes, including the minimum storage regeneration (MSR) code and the minimum bandwidth regeneration (MBR) code, were developed. However, in the hostile network with passive eavesdroppers and active attackers, the data confidentiality and storage capacity of the network can be significantly affected. In this paper, we propose a secure MSR code that can combat against the passive eavesdroppers and active attackers in the network. We also provide theoretical analyses showing that our code can provide better security with less computational cost and bandwidth overhead.

Distributed storage plays a crucial role in the current cloud computing framework. After the theoretical bound for distributed storage was derived by the pioneer work of the regenerating code, Reed-Solomon code based regenerating codes were developed. The RS code based minimum storage regeneration code (RS-MSR) and the RS code based minimum bandwidth regeneration code (RS-MBR) can achieve the theoretical bounds on the MSR point and the MBR point respectively in code regeneration. They can also maintain the MDS property in code reconstruction. However, in the hostile network where the storage nodes can be compromised and the packets can be tampered with, the storage capacity of the network can be significantly affected. In this paper, we propose a Hermitian code based regenerating (H-MSR) code. We first prove that this code can achieve the theoretical MSR bound. We then propose data regeneration and reconstruction algorithms for the H-MSR code in both error-free network and hostile network. Theoretical evaluation shows that our proposed schemes can detect the erroneous decodings and correct more errors in the hostile network than the RS-MSR code with the same code rate. Our analysis also demonstrates that the proposed H-MSR code has a lower complexity than the RS-MSR code in both code regeneration and code reconstruction.

Message authentication is one of the most effective ways to thwart unauthorized and corrupted messages from being forwarded in wireless sensor networks (WSNs). For this reason, many message authentication schemes have been developed, based on either symmetric-key cryptosystems or public-key cryptosystems. Most of them, however, have the limitations of high computational and communication overhead in addition to lack of scalability and resilience to node compromise attacks. To address these issues, a polynomial-based scheme was recently introduced. However, this scheme and its extensions all have the weakness of a built-in threshold determined by the degree of the polynomial: when the number of messages transmitted is larger than this threshold, the adversary can fully recover the polynomial. In this paper, we propose a scalable authentication scheme based on elliptic curve cryptography (ECC). While enabling intermediate nodes authentication, our proposed scheme allows any node to transmit an unlimited number of messages without suffering the threshold problem. In addition, our scheme can also provide message source privacy. Both theoretical analysis and simulation results demonstrate that our proposed scheme is more efficient than the polynomial-based approach in terms of computational and communication overhead under comparable security levels while providing message source privacy.

Linear network coding provides a new communication diagram to significantly increase the network capacity by allowing the relay nodes to encode the incoming messages. However, this communication diagram is fragile to communication errors and node compromising attacks. How to combat errors while maintaining the network efficiency is a challenging research problem. In this paper, we characterize a linear network coding through a series of cascaded linear error-control codes. This representation enables us to determine the independent source of errors in the cascaded network level. It could lead to a successful decoding of the original message and locating of the malicious network nodes. We provide comprehensive theoretical analysis on network coding in both unicast and multicast scenarios. Our research provides a new approach to understand network coding schemes and also a novel methodology to develop network coding schemes that can combat node compromising attacks and locate the malicious nodes.

While linear network coding can improve the throughput significantly in network environment with little additional computational overhead, it is fragile to communication errors and node compromising attacks. To combat the errors in network coding, both error-detection and error-correction based schemes have been proposed. In this paper, we provide a novel methodology to characterize linear network coding through error-control coding. Our main idea is to represent each linear network coding with an error-control coding. We provide comprehensive theoretical analysis on the relationships between linear network coding and error-control coding in both unicast and multicast scenarios. We find that these two codes are essentially identical in algebraic aspects. Our research provides a new approach to understand network coding schemes and also a novel methodology to develop network coding schemes that can combat communication errors and also node compromising attacks.

Message authentication is one of the most effective ways to thwart unauthorized and corrupted traffic from being forwarded in wireless sensor networks (WSNs). To provide this service, a polynomial-based scheme was recently introduced. However, this scheme and its extensions all have the weakness of a built-in threshold determined by the degree of the polynomial: when the number of messages transmitted is larger than this threshold, the adversary can fully recover the polynomial. In this paper, we propose a scalable authentication scheme based on elliptic curve cryptography (ECC). While enabling intermediate node authentication, our proposed scheme allows any node to transmit an unlimited number of messages without suffering the threshold problem. In addition, our scheme can also provide message source privacy. Both theoretical analysis and simulation results demonstrate that our proposed scheme is more efficient than the polynomial-based approach in terms of communication and computational overhead under comparable security levels while providing message source privacy.

Network coding is being viewed to have the potential for significant throughput improvement in network environment. However, these expected benefits are very fragile to malicious attacks, including message block content corruption and node compromise attacks. To solve these problems, both pollution detection and pollution correction based schemes have been proposed. These schemes are only effective in some limited scenarios. In this paper, we propose a new scheme that combines the benefits of the existing error-detection and error-correction (EDEC) schemes. The proposed scheme is similar in structure to the existing error-control based schemes. However, by appropriately modifying the rate of the underlying error-control scheme, we can improve the network throughput and robustness significantly. Our scheme can detect the malicious attacks by computing whether the syndromes are all zeros. By collecting all the non-zero syndromes, the malicious attacks within the error-decoding capacity of the underlying linear network coding can be removed and the original message can be recovered. Our theoretical analysis and simulation results demonstrate that the proposed EDEC scheme can improve the overall network performance dramatically with only a very moderate increase of the computational overhead.