Modeling and Optimal Design of Linear Network Coding for Secure Unicast with Multiple Streams

2013 ◽  
Vol 24 (10) ◽  
pp. 2025-2035 ◽  
Author(s):  
Jin Wang ◽  
Jianping Wang ◽  
Kejie Lu ◽  
Bin Xiao ◽  
Naijie Gu
Keyword(s):  
Optimal Design ◽  
Network Coding ◽  
Multiple Streams ◽  
Linear Network ◽  
Linear Network Coding

scholarly journals Secure Data Delivery with Linear Network Coding for Multiple Multicasts with Multiple Streams in Internet of Things

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Lianmin Shi ◽  
Yihuai Wang ◽  
Zhengqing Wen ◽  
Tao Peng
Keyword(s):  
Linear Programming ◽  
Internet Of Things ◽  
Network Coding ◽  
Base Station ◽  
Data Delivery ◽  
Multiple Streams ◽  
Linear Network ◽  
Linear Network Coding ◽  
First Case ◽  
Network Device

With the rapid developments of Internet of Things (IoT), tremendous number of sensors are deployed in the environment to monitor and collect different types of information. When a group of sensors located with the same location (or area) should deliver their data to a set of users and they have connected with the same network device, e.g., base station or access point, the data delivery between them and their users can be treated as a single source multicast in the core network from the network device connected with them to the network devices connected with their users. Generally, in such a case, multiple multicast sessions exist in the network simultaneously. In this paper, we study two major considerations, i.e., transmission throughput and information security, for multiple multicasts with multiple streams in IoT by using linear network coding (LNC). Specifically, we jointly consider the transmission rate allocation, transmission topology selection, and secure LNC design for multiple multicasts to maximize the total secure weighted throughput (SWT), which is referred to as the secure delivery for multiple multicasts with multiple streams (SMMS) problem. To this end, we firstly consider the SMMS problem in the case that each sensor is connected with a fixed network device. We then study the SMMS problem when the source of each multicast can be selected from a set of nodes. For the first case, we formulate it to be a linear programming (LP), based on which we give the MORT algorithm to optimally solve it. On the other hand, for the second case, we first formulate it to be an integer linear programming (ILP) and then propose an efficient MBLP algorithm based on linear programming relaxation to obtain a suboptimal solution. Finally, we conduct extensive simulations to show the effectiveness and efficiency of the proposed algorithms.

On the Optimal Linear Network Coding Design for Information Theoretically Secure Unicast Streaming

2016 ◽  
Vol 18 (6) ◽  
pp. 1149-1162 ◽  
Author(s):  
Jin Wang ◽  
Jianping Wang ◽  
Kejie Lu ◽  
Yi Qian ◽  
Naijie Gu
Keyword(s):  
Network Coding ◽  
Linear Network ◽  
Linear Network Coding ◽  
Optimal Linear

scholarly journals Semantically Secure Symmetric Encryption with Error Correction for Distributed Storage

2017 ◽  
Vol 2017 ◽  
pp. 1-10
Author(s):  
Juha Partala
Keyword(s):  
Error Correction ◽  
Network Coding ◽  
Linear Combination ◽  
Distributed Storage ◽  
Homomorphic Encryption ◽  
Error Correcting Codes ◽  
Symmetric Encryption ◽  
Goppa Codes ◽  
Linear Network ◽  
Linear Network Coding

A distributed storage system (DSS) is a fundamental building block in many distributed applications. It applies linear network coding to achieve an optimal tradeoff between storage and repair bandwidth when node failures occur. Additively homomorphic encryption is compatible with linear network coding. The homomorphic property ensures that a linear combination of ciphertext messages decrypts to the same linear combination of the corresponding plaintext messages. In this paper, we construct a linearly homomorphic symmetric encryption scheme that is designed for a DSS. Our proposal provides simultaneous encryption and error correction by applying linear error correcting codes. We show its IND-CPA security for a limited number of messages based on binary Goppa codes and the following assumption: when dividing a scrambled generator matrix G^ into two parts G1^ and G2^, it is infeasible to distinguish G2^ from random and to find a statistical connection between G1^ and G2^. Our infeasibility assumptions are closely related to those underlying the McEliece public key cryptosystem but are considerably weaker. We believe that the proposed problem has independent cryptographic interest.

scholarly journals Exact Decoding Probability Under Random Linear Network Coding

2011 ◽  
Vol 15 (1) ◽  
pp. 67-69 ◽  
Author(s):  
Oscar Trullols-Cruces ◽  
Jose M. Barcelo-Ordinas ◽  
Marco Fiore
Keyword(s):  
Network Coding ◽  
Linear Network ◽  
Linear Network Coding ◽  
Random Linear Network Coding
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