Method and apparatus for data structure analyzing
First Claim
1. A method for detecting risky types of data structures of a computer program code with a neural network, said neural network comprising at least two neurons, and the neurons being related to each other by a topological arrangement involving a neighborhood definition, each of the neurons comprises a vector for representing elements of an input data space, at least one neuron having an associated label indicating the type of the neuron, and the data structures being detected comprising at least two data elements, characterized in that the method comprises, extracting information of at least two data elements from at least one data structure, forming at least two input vectors from said extracted information of the data elements, the vectors being compatible with the vectors of the neurons, comparing said input vectors with said vectors of the neurons, and detecting the type of said at least one data structure by using an associated label obtained on the basis of said comparison.
1 Assignment
0 Petitions
Accused Products
Abstract
A method and a device for detecting risky types of data structures of a computer program code with a neural network. The neural network comprises neurons being related to each other by a topological arrangement involving a neighborhood definition. The neurons each comprising a vector for representing values of an input data space, at least one neuron having an associated label indicating the type of the neuron, and the data structures being detected comprising at least two elements. Information is extracted from at least two data elements from said at least one data structure and at least two input vectors are formed from said extracted information, the vectors being compatible with the vectors of the neurons. Said input vectors are compared with said vectors of the neurons, and the type of said basic data element is detected by using an associated label on the basis of said comparison.
-
Citations
15 Claims
-
1. A method for detecting risky types of data structures of a computer program code with a neural network, said neural network comprising at least two neurons, and the neurons being related to each other by a topological arrangement involving a neighborhood definition, each of the neurons comprises a vector for representing elements of an input data space, at least one neuron having an associated label indicating the type of the neuron, and the data structures being detected comprising at least two data elements, characterized in that the method comprises,
extracting information of at least two data elements from at least one data structure, forming at least two input vectors from said extracted information of the data elements, the vectors being compatible with the vectors of the neurons, comparing said input vectors with said vectors of the neurons, and detecting the type of said at least one data structure by using an associated label obtained on the basis of said comparison.
-
8. An electronic device (400) for detecting risky types of data structures of a computer program code with a neural network, said neural network comprising at least two neurons, and the neurons being related to each other by a topological arrangement involving a neighborhood definition, each of the neurons each comprises a vector for representing elements of an input data space, at least one neuron having an associated label indicating the type of the neuron, and the data structures being detected comprising at least two data elements, characterized in that the device comprises,
extracting means (401, 402, 406) for extracting information of at least two data elements from at least one data structure, formation means (401, 402, 406) for forming at least two input vectors from said extracted information of the data elements, the vectors being compatible with the vectors of the neurons, comparison means (401, 402, 406) for comparing said input vectors with said vectors of the neurons, and detecting means (401, 402, 406) for detecting the type of said data structure by using an associated label obtained on the basis of said comparison.
-
15. A computer program product for an electronic device for detecting risky types of data structures of a computer program code with a neural network, said neural network comprising at least two neurons, and the neurons being related to each other by a topological arrangement involving a neighborhood definition, each of the neurons comprises a vector for representing elements of an input data space, at least one neuron having an associated label indicating the type of the neuron, and the data structures being detected comprising at least two data elements, characterized in that the computer program product comprises,
computer program code for causing the electronic device to extract information of at least two data elements from at least one data structure, computer program code for causing the electronic device to form at least two input vectors from said extracted information of the data elements, the vectors being compatible with the vectors of the neurons, computer program code for causing the electronic device to compare said input vectors with said vectors of the neurons, and computer program code for causing the electronic device to detect the type of said data structure by using an associated label obtained on the basis of said comparison.
Specification