CN110213279B - Privacy protection-based dynamic network average consensus method - Google Patents

Privacy protection-based dynamic network average consensus method Download PDF

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CN110213279B
CN110213279B CN201910496659.3A CN201910496659A CN110213279B CN 110213279 B CN110213279 B CN 110213279B CN 201910496659 A CN201910496659 A CN 201910496659A CN 110213279 B CN110213279 B CN 110213279B
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state
individual
dynamic network
explicit
implicit
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CN110213279A (en
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汪伟
李德权
姜颖
申修宇
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Anhui University of Science and Technology
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/04—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/04—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks
    • H04L63/0428—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the data content is protected, e.g. by encrypting or encapsulating the payload

Abstract

The invention relates to a privacy protection-based dynamic network average consensus algorithm, which is suitable for communication security and data privacy protection of a dynamic network. The algorithm involves the decomposition of the state at individual initial moments and the interaction of explicit and implicit states. Through the decomposition scheme, the real state of the individual is guaranteed to be always subjected to strict privacy protection in the interaction process. And the individual decomposes the real state of the initial moment of the individual to obtain an explicit state and an implicit state. In this algorithm, explicit state generated by an individual interacts with neighboring individuals in the network, while implicit state is stored only in the individual itself and interacts only with the explicit state of itself. The privacy protection algorithm for the average consensus of the dynamic network provided by the invention can achieve accurate average consensus under the condition that the real state of an individual is not leaked in the dynamic network, effectively solves the problem that the privacy leakage is easy to occur in the communication process of the dynamic network in the individual state, and ensures the communication safety.

Description

Privacy protection-based dynamic network average consensus method
Technical Field
The invention belongs to the technical field of electronic information communication, and particularly relates to a method for providing privacy protection for sensitive information of communication individuals in a dynamic network.
Background
With the rapid development of technologies such as big data, internet of things, cloud computing and the like, distributed optimization receives more and more attention, and the distributed optimization is widely applied to the fields of wireless sensor networks, machine learning, smart power grids and the like. Compared with a centralized system, the distributed system has good fault tolerance and robustness, and can still maintain normal operation for downtime and local network communication faults of a single individual. In a distributed network, how to make all individuals in the network reach an average consensus is a very important research direction.
In the conventional average consensus algorithm, in order to ensure that all individuals in the distributed network can eventually agree on an average, state information needs to be exchanged among the individuals. Information exchange among individuals is often explicit, and when the individuals are attacked maliciously, privacy information of nodes is easy to leak, which is a great hidden danger for system security. For example, in banking, health care and smart grid systems, it is desirable to ensure that such information communication is privacy protected. Most of the existing privacy protection average consensus algorithm is established on a fixed network topology, and in practical application, the network topology is often not fixed due to communication faults and individual movement.
Disclosure of Invention
The invention aims to provide a dynamic network average consensus algorithm based on privacy protection, which achieves accurate average consensus on the basis of protecting individual privacy information.
In order to solve the technical problems, the invention adopts the following technical scheme:
a dynamic network average consensus algorithm based on privacy protection comprises decomposition of a real state at an initial moment and interaction of an explicit state and an implicit state; the method is characterized in that: decomposing the real initial state of the individual to generate an explicit state and an implicit state; the explicit state carries out normal communication among individuals, and the implicit state is hidden as privacy information; the algorithm is implemented in a dynamic network, and the accurate average consensus can be achieved without considering the network topology for the parameter selection of the relevant implicit state. And establishing a relation between the decomposed explicit state and the implicit state, so that the explicit state and the implicit state can be communicated and interacted in an individual at any time, and can not only receive information but also transmit information.
Further, the present invention provides a decomposition of the real state at the initial time, the real state at the initial time needs to be decomposed into an explicit state and an implicit state, and satisfies the following conditions: 2, initial time real state is explicit state + implicit state; any of the different random combinations of explicit and implicit states, for which the generated implicit state is stored only in the individual himself, are not accessible to other individuals except for the fact that the explicit state of the individual can interact with it.
Furthermore, the invention provides an interactive method of the explicit state and the implicit state, the explicit state can be linked with the implicit state, the relevant coefficient meeting the set condition is selected, the updating of the implicit state does not need to consider the structure of the network topology, and the explicit state and the implicit state of all individuals can be converged to the accurate average consensus along with the increase of the iteration times
Further, the present invention provides an algorithm implemented in a dynamic network, wherein the network topology is randomly changed, and in the dynamic network, the join of all the topological graphs is connected in an undirected manner only in a non-empty, continuous and bounded time interval as to the precondition of achieving average consensus.
Compared with the prior art, the invention has the beneficial effects that:
the state decomposition can ensure that the real state of an individual is strictly protected by privacy in a dynamic network, and the communication interaction of the explicit state and the implicit state can ensure that the individual can achieve accurate average consensus in the dynamic network, so the state decomposition and the communication interaction of the explicit state and the implicit state are combined to obtain the dynamic network average consensus algorithm with privacy protection.
Drawings
FIG. 1 is a schematic diagram of an individual state decomposition of the present invention.
FIG. 2 is a diagram of the evolution of the explicit state of the present invention to achieve accurate average consensus.
FIG. 3 is a progression diagram of the privacy states of the present invention to achieve accurate average consensus.
Detailed Description
In the dynamic network, the invention carries out privacy protection on the information exchange of a plurality of individuals and ensures that the real state of the individual is not leaked.
Dynamic network average consensus algorithm with privacy protection:
Figure BDA0002088830770000021
we associate the true state x of each individual i in the networki(t) decomposition into
Figure BDA0002088830770000022
And
Figure BDA0002088830770000023
and
Figure BDA0002088830770000024
in order to randomly select from the set of real numbers,satisfy the requirement of
Figure BDA0002088830770000025
Wherein
Figure BDA0002088830770000026
As an explicit state, is responsible for information interaction with neighboring individuals in the network,
Figure BDA0002088830770000027
as implicit state, only within the individual i and
Figure BDA0002088830770000028
and carrying out information interaction. h isi(t) is a random number generated by the individual i at time t, and satisfies 0 < hi< 1, and is stored only in individual i itself.
The invention is further described below with reference to the accompanying drawings.
Fig. 1 is a true state exploded schematic of the present invention. By the true state x of the individuali(t) decomposing to obtain an explicit state
Figure BDA0002088830770000031
And implicit status
Figure BDA0002088830770000032
Wherein the explicit status of the individual
Figure BDA0002088830770000033
Communication interaction between individuals, implicit status of individuals
Figure BDA0002088830770000034
With explicit state inside the individual i
Figure BDA0002088830770000035
And carrying out communication interaction.
FIG. 2 is an explicit state of the present invention
Figure BDA0002088830770000036
Evolution diagrams in dynamic networks, explicit states for communication interactions between individuals
Figure BDA0002088830770000037
True state xi(t) is not revealed to the neighbor individuals, and as can be seen from FIG. 2, the average consensus of all individual explicit states converges exactly to a value of 3.
FIG. 3 is an implicit state of the present invention
Figure BDA0002088830770000038
Evolution diagrams, implicit states in dynamic networks
Figure BDA0002088830770000039
With explicit state inside the individual i
Figure BDA00020888307700000310
Communication interaction, ensuring implicit state
Figure BDA00020888307700000311
Not visible to other individuals. As can be seen from fig. 3, the average consensus of all individual implicit states converges exactly to a value of 3.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Furthermore, it should be understood that although the present description refers to embodiments, not every embodiment may contain only a single embodiment, and such description is for clarity only, and those skilled in the art should integrate the description, and the embodiments may be combined as appropriate to form other embodiments understood by those skilled in the art.

Claims (4)

1. A privacy protection-based dynamic network average consensus method comprises decomposition of a real state at an initial moment and interaction of an explicit state and an implicit state, and is characterized in that: true state x of individual ii(t) decomposition into
Figure FDA0003315993480000011
And
Figure FDA0003315993480000012
and
Figure FDA0003315993480000013
is randomly selected from a real number set to satisfy
Figure FDA0003315993480000014
Wherein
Figure FDA0003315993480000015
As an explicit state, it is responsible for information interaction with neighboring individuals in the network, and the formula is:
Figure FDA0003315993480000016
true state x of individual ii(t) is not disclosed to the neighbor individual j, the privacy information of the individual i is protected,
Figure FDA0003315993480000017
as implicit state, only within the individual i and
Figure FDA0003315993480000018
carry out information interaction, hi(t) is a random number generated by the individual i at time t, and satisfies 0 < hi< 1, and is stored only in individual i itself.
2. The privacy protection-based dynamic network average consensus method according to claim 1, wherein the generated implicit state is stored only in the individual itself and is invisible to other individuals except the explicit state of the individual itself can interact with the implicit state.
3. The privacy protection based dynamic network average consensus method of claim 1, wherein: the explicit state can be linked with the implicit state, so that the explicit state and the implicit state of all individuals can realize accurate average consensus along with time iteration, precision loss is avoided, and the requirement of a high-precision distributed system can be met.
4. The privacy protection based dynamic network average consensus method of claim 1, wherein: the network topology is dynamically changed, in a dynamic network, as for the precondition of achieving average consensus, the network does not need to be connected in an undirected mode at any moment, and only on a non-empty, continuous and bounded time interval, the union graph of all the topological graphs is connected in an undirected mode.
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