US 12,750,407 B2 · Method and apparatus for security management of internet of things traffic, and power internet of things system

Abstract

Provided are a method and apparatus for security management of Internet of Things traffic, and an power Internet of Things system, the method uses a fuzzy calculation method for the degree of trust of Internet of Things traffic, and the basic principle thereof is considering that when the Internet of Things performs data access, gain of data access and data sharing, and further considering influences of errors in a data acquisition process, a data transmission rate and a data sharing scale on the gain, quantifying the income, and calculating the credibility of the power Internet of Things for visiting users by means of the income value and the loss value, in addition, the influence of the degree of trust on user access is evaluated, and the user access behaviour is limited according to the degree of trust.

A method for security management of Internet of Things traffic, comprising:

using a statistical analysis method to determine accessible data volume of weather forecast data, power generation data, electricity consumption data, grid power flow data, market pricing data and accessible resources of user side energy shared data corresponding to each of a plurality of pre-set time intervals, according to the accessible data volume, using a statistical analysis method to calculate a three-dimensional trapezoidal fuzzy set of traffic demand amounts of the weather forecast data, the power generation data, the electricity consumption data, the grid power flow data, the market pricing data and the accessible resource of the user-side energy shared data corresponding to each of the pre-set time intervals, and calculating a three-dimensional trapezoidal fuzzy set of a total flow demand using a statistical analysis method according to the three-dimensional trapezoidal fuzzy set of each of the flow demand, using a statistical analysis method to calculate a three-dimensional trapezoidal fuzzy set of collection errors of the weather forecast data, the power generation data, the electricity consumption data, power grid tidal flow data, the market pricing data and an accessible resource of the energy sharing data of the user side corresponding to each of the plurality of pre-set time intervals;
according to a data transmission rate of an Internet of Things monitoring data centre, using a statistical analysis method to calculate a plurality of three-dimensional trapezoidal fuzzy sets of different levels of the data transmission rate, and according to a data storage sharing scale of the Internet of Things monitoring data centre, using a statistical analysis method to calculate a plurality of three-dimensional gradient fuzzy sets of different levels of the data storage sharing scale;
calculating a three-dimensional trapezoidal fuzzy set of total collection errors of accessible data in an electric power Internet of Things (IoT) according to the three-dimensional trapezoidal fuzzy set of collection errors of the weather forecast data, the power generation data, the electricity consumption data, the grid power flow data, market quotation data and the accessible resource of the user-side energy shared data;
calculating a first flow deviation amount based on an accessible amount of data and a three-dimensional trapezoidal fuzzy set of total collection errors of access resources, calculating a second flow deviation amount based on an accessible data amount and the plurality of three-dimensional trapezoidal fuzzy sets of different levels of the data transmission rate, the first flow deviation amount is a traffic reduction amount caused by a collecting error, and the second flow deviation amount is a traffic reduction amount caused by the data transmission rate;
calculating a first duration deviation amount according to the three-dimensional trapezoidal fuzzy set of the collection error of the access resources, calculating a second duration deviation amount based on amount of the accessible data and the plurality of three-dimensional trapezoidal fuzzy sets of different levels of the data transmission rate, the first duration deviation amount is an increment of a data transmission duration caused by the collection error, and the second duration deviation amount is an increment of a duration caused by the data transmission rate;
calculating a first information loss value according to the first flow deviation amount and the second flow deviation amount, calculating a second information loss value according to the first duration deviation amount and the second duration deviation amount, and calculating an information yield value according to a plurality of three-dimensional trapezoidal haze sets with different levels of the data transmission rate and the plurality of three-dimensional gradient fuzzy sets of different levels of the data storage sharing scale, and calculating a trust degree of the electric power Internet of Things to the user according to the first information loss value, the second information loss value and the information yield value, and controlling an access of the user according to the trust degree,
wherein, a first information loss value is calculated based on the first flow deviation value and the second flow deviation value, calculating a second information loss value according to the first duration deviation amount and the second duration deviation amount, and calculating an information yield value according to the plurality of three-dimensional trapezoidal haze sets with different levels of a data transmission rate and the plurality of three-dimensional gradient fuzzy sets with different levels of the data storage sharing scale, calculating the trust degree of the electric power Internet of Things to the user according to the first information loss value, the second information loss value and the information yield value, and controlling the access of the user according to the trust degree, comprises:
substituting the first flow deviation amount and the second flow deviation amount into a calculation formula of the first information loss value, and calculating the first information loss value LDF caused by the change of the access traffic of the power Internet of Things:
L
DF
=
∑
t
=
1
N
t
(
k
CDFe
′
⁢
k
LDFe
′
⁢
Δ
⁢
F
e
-
′
+
k
CDFv
′
⁢
k
LDFv
′
⁢
Δ
⁢
F
v
-
′
)
;
wherein LDF is an information loss value caused by a traffic change of the accessible resource,
k
CDFe
t
is a weight coefficient for obtaining the traffic change caused by the collection error of the accessible resource,
k
LDFe
t
is a unit loss value resulting from the collection error of the accessible resource yielding a change in traffic,
k
CDFv
t
is a weight coefficient of a traffic change due to the data transmission rate,
k
LDFv
t
is a unit loss value of the traffic change due to the data transmission rate;
substituting the first time span deviation amount and the second time span deviation amount into a calculation formula of the second information loss value, and calculating the second information loss value LDT or caused by the data transmission rate change of the power Internet of Things;
L
DT
=
∑
t
=
1
N
t
(
k
CDTe
′
⁢
k
LDTe
′
⁢
Δ
⁢
T
e
+
′
+
k
CDTv
′
⁢
k
LDTv
′
⁢
Δ
⁢
T
v
+
′
)
;
wherein LDT is an information loss value caused by a duration change of the accessible resource,
k
CDFe
t
is a weight coefficient for obtaining the duration change caused by the collection error of the accessible resource,
k
LDFe
t
is a unit loss value resulting in a time variation from the collection error of the accessible resource,
k
CDFv
t
is a weight coefficient of a time change caused by the data transmission rate,
k
LDFv
t
is a unit ross value of the time change caused by the data transmission rate;
substituting a plurality of three-dimensional trapezoidal fuzzy sets of different data transmission rates and the plurality of three-dimensional gradient fuzzy sets of different levels of the data storage sharing scale into a calculation formula of the information gain value, and calculating the information gain value RRP corresponding to the plurality of three-dimensional trapezoidal fuzzy sets of different data transmission rates and the plurality of three-dimensional gradient fuzzy sets of different levels of the data storage sharing scale;
R
RP
=
n
G
n
LT
·
E
[
⋁
i
=
1
9
k
Dvi
⁢
v
Dvi
⊗
⋁
i
=
1
9
k
DSi
⁢
S
Di
⊗
k
Mi
⁢
M
G
]
;
wherein, RRP providing the power Internet of Things to users with information gain values for accessible data collection, data transmission, data storage and data sharing services,
⋁
i
=
1
9
k
Dvi
⁢
v
Dvi
is the three-dimensional trapezoidal fuzzy set of the data transmission rate when said power Internet of Things provides services for a user being information gain values in the cases of extremely low, very low, low, low, medium, high, high, very high and extremely high, kDvi provides a unit benefit value in the case of a fuzzy uncertainable three-dimensional trapezoidal fuzzy set of the data transmission rate at level i for the power Internet of Things,
⋁
i
=
1
9
k
DSi
⁢
S
Di
when the power Internet of Things provides services to users, the data storage sharing a fuzzy three-dimensional trapezoidal fuzzy set of a scale is an information gain value in the case of extremely low, very low, low, low, medium, high, high, very high, and extremely high, kDSi providing the power Internet of Things with a unit yield value in the case of an ith data storage sharing scale fuzzy three-dimensional trapezoidal fuzzy set, kMiMG is an information benefit value of said power Internet of Things providing a data acquisition service for an access user in a sensing layer, MG is a unit income value of the power Internet of Things providing a data acquisition service for an access user in a sensing layer, E[ ] is the expectation for [ ],
9
⋁
il
=
1
represents the union of 9 fuzzy sets;
substituting the first information loss value, the second information loss value and the information yield value into a trust degree calculation formula of the power Internet of Things for a user, and calculating the trust degree BI of the power Internet of Things for the user;
B
1
=
R
RP
R
RP
+
L
DF
+
L
DT
;
in the case where the degree of trust is greater than or equal to a first threshold value and less than a second threshold value, allowing a user to access traffic corresponding to a three-dimensional trapezoidal fuzzy set of a total traffic demand amount;
in the case where the degree of trust is less than the first threshold and greater than or equal to a third threshold, allowing a user to access the traffic corresponding to a product of the degree of trust and a three-dimensional trapezoidal fuzzy set of the total traffic demand;
in the case where the trust degree is less than the third threshold and greater than a fourth threshold, not allowing the user to access.

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Method and apparatus for security management of internet of things traffic, and power internet of things system

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Method and apparatus for security management of internet of things traffic, and power internet of things system

Life of this patent

Abstract

Claims8