Big Data-Driven Hierarchical Local Area Network Security Risk Event Prediction Algorithm

Table 4

Description of network node communication transmission volume.

Steps	Algorithm consumption	Description code
1	For the filtered security	Import numpy as np
2	The event merging function	For (int i = 101; i < 200; i+ = 2)
3	A large number of security events	Def nms (dets, thresh):
4	Accuracy of security events	Public static void main (String[] args) {
5	The accuracy of fusion is lower	Int f1 = 1, f2 = 1, f;
6	Compared with centralized fusion	Int M = 30;
7	Communication and energy consumption	System.out.println (f1);
8	Data-driven hierarchical local area	X1 = dets[:, 0]
9	The merging rules are under	Y1 = dets[:, 1]
10	Connect the database through vulnerability	X2 = dets[:, 2]
11	Environmental condition error	Y2 = dets[:, 3]
12	It reduces the amount of	Scores = dets[:,4]
13	A group of variables representing	For (int i = 3; i < M; i++) {
14	Many duplicate or similar incidents	F = f2;
15	The false alarm rate and false alarm rate	F2 = f1 + f2;
16	Other methods have fewer feature	Order = scores.argsort()[-1]
17	Vulnerability category labels	Keep = []
18	System command injection	While order.size > 0:
19	Access verification error	I = order[0]
20	It divides vulnerabilities into	Keep.append(i)