Enjoy the Benefit of Network Coding: Combat Pollution Attacks in 5G Multihop Networks

Li, Jian; Li, Tongtong; Ren, Jian; Chao, Han‐Chieh

doi:10.1155/2018/3473910

Cited by 6 publications

(4 citation statements)

References 30 publications

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“…Chen et al proposed a method of applying error detection and error correction techniques to encoded packets. This paper showed that the throughput can be improved by allowing the intermediate nodes to correct the packet [12]. Mamidwar et al analyzed studies to prevent the rapid spread of pollution attacks from network coding throughout the network.…”

Section: Related Workmentioning

confidence: 99%

Attack Detection Using Network Coding in IoT Environment

Yong¹,

Lee

2020

Sensors

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Network coding is a reasonable way to increase network efficiency in response to an increase of sensed data in the Internet of Things (IoT). In network coding, intermediate nodes combine packets received from neighboring nodes, transform, and transmit encoded packets that can be decoded at the destination. This scheme is based on trust among nodes. If any malicious node joins the network, it can act as an intermediate node that could fabricate encoded packets. It might be more difficult to identify the authenticity of such encoded packets since packets that are received at the destination might not originate from a single source, but be combined with several other packets originating from multiple sources. In this paper, we propose a scheme on how to detect attacked packets among the received packets at a destination and how to recover the original message from the packets including the attacked “look-like-valid” packets. This scheme shows that a destination could recover the valid message with just the received packets including some attacked packets and will result in a quite efficient performance in network coding.

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Section: Related Workmentioning

confidence: 99%

Attack Detection Using Network Coding in IoT Environment

Yong¹,

Lee

2020

Sensors

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“…In fact, in cryptography, homomorphic signature scheme is another technique to protect network coding against pollution attack [3]- [5], [11]. Contrast to homomorphic MAC scheme, it is a kind of public key authentication method.…”

Section: A Related Workmentioning

confidence: 99%

Security Analysis of an Efficient Null Space-Based Homomorphic MAC Scheme Against Tag Pollution Attacks in RLNC

et al. 2019

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Recently, Esfahani, Mantas, and Rodriguez proposed a homomorphic message authentication code (MAC) scheme for the random linear network coding (RLNC) to resist tag pollution attacks (TPAs), and also presented the security analysis. As Esfahani et al. said, their scheme is based on the null space properties of Kehdi and Li, and the main contribution lies in adding the process of swapping when generating the tags for data packets. However, in this paper, we first point out that Esfahani et al.'s swapping technique is not essential for the TPA security, because the underlying non-swapping homomorphic MAC scheme has been secure against TPA and the process of swapping only improves the TPA security with a non-negligible factor. More importantly, we find that the security proof of Esfahani et al. is incorrect and misguided. In particular, according to Esfahani et al. suggestion, one should enlarge the number of neighbor nodes to reduce the probability of the TPA. However, this paper gives contrary suggestions in Esfahani et al.'s work by presenting the precise proof for the proposed homomorphic MAC scheme.INDEX TERMS Homomorphic MAC, network coding, tag pollution attack (TPA).

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“…It is a new concept. Study on the performance of network coding shows that it can utilize the available limited bandwidth of the network to achieve improved throughput in multicast communication [16] [31] [32]. Network coding is applied on on-demand broadcasting network [14] [23] [28].…”

Section: Introductionmentioning

confidence: 99%

Performance Improvement of Network Coding for Heterogeneous Data Items with Scheduling Algorithms in Wireless Broadcast

Ema¹,

Hossain²,

Hossain³

et al. 2021

IJACSA

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This is the age of information. Now-a-days everyone communicates with each other by means of digital systems. Humans are always communicating with each other on the go. On-demand broadcasting is an efficient way to broadcast information according to user requests. In an on-demand broadcasting network, anyone can satisfy multiple clients in one broadcast which helps to fulfill the enormous demand of information by clients. The optimized flow of digital data in a network through the transmission of digital evidence about messages is called network coding. The "digital evidence" is composed of two or more messages. Network coding incorporated with data scheduling algorithms can further improve the performance of on-demand broadcasting networks. Using network coding, anyone can broadcast multiple data items using single broadcast strategy which can satisfy the needs of more clients. In this work, it is described that network coding cannot always maintain its superiority over non-network coding when the system handles different sized data items. However, the causes of performance reduction on network coding have been analyzed and THETA based dynamic threshold value integration strategy has been proposed through which the network coding can overcome its limitation for handling heterogeneous data items. In the proposed strategy, THETA based dynamic threshold will control which data item will be selected from the Client Relationship graph (CR-graph) so that large sized data items cannot be encoded with small sized data items. Simulation result shows some interesting performance comparison.

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Enjoy the Benefit of Network Coding: Combat Pollution Attacks in 5G Multihop Networks

Cited by 6 publications

References 30 publications

Attack Detection Using Network Coding in IoT Environment

Attack Detection Using Network Coding in IoT Environment

Security Analysis of an Efficient Null Space-Based Homomorphic MAC Scheme Against Tag Pollution Attacks in RLNC

Performance Improvement of Network Coding for Heterogeneous Data Items with Scheduling Algorithms in Wireless Broadcast

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