Using a process known as signature matching, NIDPSs must look for attack pattern
ID: 3909949 • Letter: U
Question
Using a process known as signature matching, NIDPSs must look for attackpatterns by comparing measured activity to known signatures in their
knowledge base to determine whether or not an attack has occurred or may be
under way. Describe the three methods used by a NIDPS to accomplish this. Using a process known as signature matching, NIDPSs must look for attack
patterns by comparing measured activity to known signatures in their
knowledge base to determine whether or not an attack has occurred or may be
under way. Describe the three methods used by a NIDPS to accomplish this. Using a process known as signature matching, NIDPSs must look for attack
patterns by comparing measured activity to known signatures in their
knowledge base to determine whether or not an attack has occurred or may be
under way. Describe the three methods used by a NIDPS to accomplish this.
Explanation / Answer
Hello Sir/Madam
Here are the three methods that was used ny NIDPS for Signature matching in intrusion detection
Graph Based:
This method involves obtaining boundary cubes approximations to the two objectsThis method is based upon matching of strong graphs defined by relational signatures computed between clusters of a fuzzy
partition. Such a representation combines color and spatial information between the regions and has nice geometric properties with respect to scale factor, rotation and translation
The input image is decomposed into regions through a quadtree algorithm. The decomposed image is represented by an attributed relational graph (ARG) named input graph. The objects
to be recognized are also stored in an ARG named model graph. Object segmentation and recognition are accomplished by matching the input graph to the model graph.
Signature Preprocessing:
Before a signature can be compared to any other signature, it undergoes some preprocessing operations. A
signature is captured as a binary image, S . Then, pepper noise is removed, if there is any, to allow more
accurate calculation of center of area. The angle, ?, of least second moment of S is found. The angle is
measured counterclockwise from the y-axis. The signature is rotated about the center of area of S ? degrees
clockwise. This rotation eliminates skew angle of a signature which is necessary for signatures of the same
subject. After rotation, the image is smoothed which is a necessary step before thinning. To reduce data, the
image is thinned using Zhang-Suen algorithm . The thinned image undergoes a normalization step
that preserves the aspect ratio of the signature. The set of pixels that constitute the final thinned-normalized
image of S , denoted as the set of vertices X , represents the signature S . These steps are summarized as
follows, where after every image processing operation S is replaced by the resultant image.
--> Remove pepper noise from S .
--> Find the angle of least second moment, ?, of S .
--> Rotate S ? degrees clockwise.
--> Smooth S .
--> Thin S .
--> Normalize S . The set of pixels that constitute the final normalized image, S ; denoted as the set of
vertices X , represents the signature S .
A grid of 5 rows by 3 columns was prepared and printed on an A4 paper to collect signatures of subjects. Each cell of the grid is 6.3 cm width and 4.5 cm height. This size is usually sufficient to handwrite a signature freely. Subjects were asked to provide 15 of their genuine signatures on an A4 page with the described grid. Subjects were also asked not to touch the borders of the grid cells to facilitate signature segmentation. Although we explained to subjects that their signatures will be solely used in a scientific research study and this was written clearly in Arabic on the top of the page, most of the subjects refused to provide any signature.
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