Apparatus, Device, Method, and Non-Transitory Machine-Readable Storage Medium for a Node of a Blockchain Network

Patent metadata

Field	Value
Publication number	US-2023344864-A1
Application number	US-202318344882-A
Country	US
Kind code	A1
Filing date	Jun 30, 2023
Priority date	Jun 30, 2023
Publication date	Oct 26, 2023
Grant date	—

Abstract

Various examples relate to an apparatus, device, method, and a non-transitory machine-readable storage medium for a node of a blockchain network. The apparatus comprises interface circuitry, machine-readable instructions and processor circuitry to execute the machine-readable instructions to compare a traffic pattern of requests associated with one or more smart contracts hosted by the node of the blockchain network with a reference traffic pattern, determine an estimated denial of service of at least one of the one or more smart contracts based on the comparison between the traffic pattern and the reference traffic pattern, determine one or more potential mitigations for the estimated denial of service, and apply at least one of the one or more potential mitigations.

First claim

What is claimed is:

1 . An apparatus for a node of a blockchain network, the apparatus comprising interface circuitry, machine-readable instructions and processor circuitry to execute the machine-readable instructions to:
compare a traffic pattern of requests associated with one or more smart contracts hosted by the node of the blockchain network with a reference traffic pattern; determine an estimated denial of service of at least one of the one or more smart contracts based on the comparison between the traffic pattern and the reference traffic pattern; determine one or more potential mitigations for the estimated denial of service; and apply at least one of the one or more potential mitigations.

2 . The apparatus according to claim 1 , wherein the processor circuitry is to execute the machine-readable instructions to determine the one or more potential mitigations based on a collection of mitigations collectively maintained by the nodes of the blockchain network.

3 . The apparatus according to claim 1 , wherein the traffic pattern relates to at least one of incoming requests and outgoing requests.

4 . The apparatus according to claim 1 , wherein the reference traffic pattern is a reference traffic pattern that is determined locally at the node.

5 . The apparatus according to claim 4 , wherein the processor circuitry is to execute the machine-readable instructions to monitor requests associated with the one or more smart contracts, and to determine the reference traffic pattern based on the monitored requests.

6 . The apparatus according to claim 1 , wherein the reference traffic pattern is a reference traffic pattern that is collectively maintained by the nodes of the blockchain network.

7 . The apparatus according to claim 1 , wherein the comparison between the traffic pattern and the reference traffic pattern is performed using a traffic pattern evaluation mechanism.

8 . The apparatus according to claim 7 , wherein the traffic pattern evaluation mechanism is collectively maintained by the nodes of the blockchain network.

9 . The apparatus according to claim 7 , wherein the processor circuitry is to execute the machine-readable instructions to adjust the traffic pattern evaluation mechanism over time based on a plurality comparisons between the traffic pattern and the reference traffic pattern at a plurality of points of time.

10 . The apparatus according to claim 9 , wherein the processor circuitry is to execute the machine-readable instructions to adjust the traffic pattern evaluation mechanism by training a machine-learning model used by the traffic pattern evaluation mechanism, and to propagate the training of the machine-learning model to one or more further nodes of the blockchain network using federated learning.

11 . The apparatus according to claim 1 , wherein a selection of the one or more potential mitigations is performed using a mitigation selection mechanism.

12 . The apparatus according to claim 11 , wherein the mitigation selection mechanism is collectively maintained by the nodes of the blockchain network.

13 . The apparatus according to claim 11 , wherein the processor circuitry is to execute the machine-readable instructions to determine an efficacy of the at least one applied mitigation, and to adjust the mitigation selection mechanism over time based on the determined efficacy.

14 . The apparatus according to claim 13 , wherein the processor circuitry is to execute the machine-readable instructions to adjust the mitigation selection mechanism by training a machine-learning model used by the mitigation selection mechanism, and to propagate the training of the machine-learning model to one or more further nodes of the blockchain network using federated learning.

15 . The apparatus according to claim 1 , wherein at least one of a collective maintenance of a collection of mitigations, a collective maintenance of a traffic pattern evaluation mechanism and a collective maintenance of a mitigation selection mechanism is based on a reputation-based mechanism that is based on a reputation of the nodes of the blockchain network.

16 . The apparatus according to claim 1 , wherein the processor circuitry is to execute the machine-readable instructions to determine an efficacy of the at least one applied mitigation, and to provide information on the efficacy of the at least one potential mitigation to at least one other node of the blockchain network.

17 . The apparatus according to claim 1 , wherein the processor circuitry is to execute the machine-readable instructions to identify a potential vulnerability associated with the estimated denial of service, and to provide information on the potential vulnerability to at least one other node of the blockchain network.

18 . The apparatus according to claim 1 , wherein the processor circuitry is to execute the machine-readable instructions to provide information on the estimated denial of service to at least one other node of the blockchain network.

19 . A method for a node of a blockchain network, the method comprising:
comparing a traffic pattern of requests associated with one or more smart contracts hosted by the node of the blockchain network with a reference traffic pattern; determining an estimated denial of service of at least one of the one or more smart contracts based on the comparison between the traffic pattern and the reference traffic pattern; determining one or more potential mitigations for the estimated denial of service; and applying at least one of the one or more potential mitigations.

20 . A non-transitory machine-readable storage medium including program code, when executed, to cause a machine to perform the method of claim 19 .

Assignees

• Divan Koller Mario Jose
• Carranza Marcos
• Poornachandran Rajesh
• Guim Bernat Francesc
• Martinez Spessot Cesar

Inventors

• Divan Koller Mario Jose
• Carranza Marcos
• Poornachandran Rajesh
• Guim Bernat Francesc
• Martinez-Spessot Cesar

Classifications

• H04L41/16

  using machine learning or artificial intelligence · CPC title

• H04L63/1425

  Traffic logging, e.g. anomaly detection · CPC title

• H04L9/50

  using hash chains, e.g. blockchains or hash trees · CPC title

• H04L63/1458 Primary

  Denial of Service · CPC title

• H04L63/1433

  Vulnerability analysis · CPC title