scholarly journals An Optimized FPN Network Attack Model Based on Improved Ant Colony Algorithm

Author(s):  
Huilin Wu ◽  
Wenjuan Wu
2021 ◽  
Vol 7 (5) ◽  
pp. 5009-5017
Author(s):  
Lili Zhang

Objectives: The ant colony algorithm is an algorithm that the Italian scholar sums up by studying the living habits of the creatures, and algorithm model established by inspiration according to ants finding things in the shortest path. Methods: In this paper, through the establishment of algorithm model based on an ant colony algorithm, all kinds of problems in physical fitness test were solved, which makes the physical test more efficient and convenient. Results: Through the testing and use of the algorithm model, it is found that the ant colony algorithm established in this paper can meet the requirements, can plan the information of physical fitness test as a whole, Conclusion: and help to deal with the problems of physical tests, so it is a good performance algorithm.


2020 ◽  
Vol 57 (1) ◽  
pp. 010603
Author(s):  
聂清彬 Nie Qingbin ◽  
潘峰 Pan Feng ◽  
吴嘉诚 Wu Jiacheng ◽  
曹耀钦 Cao Yaoqin

2021 ◽  
Author(s):  
Xinpin Wang ◽  
Manxi Leng ◽  
Weiqiang Fu ◽  
Haoqi Wang ◽  
Yutong Xue ◽  
...  

2014 ◽  
Vol 989-994 ◽  
pp. 1989-1992 ◽  
Author(s):  
Chun Mei Hao

In the information management process, it is necessary to classify all information optimization to provide the support for quickly query the search target providing this, a classification optimization method based on improved ant colony algorithm is proposed in this paper. That is, extract the characteristics of information attribute, and then establish the optimization classification model based on the characteristics to achieve the classification of information. Experimental results show that using the improved algorithm for classification information, the classification accuracy can be improved to meet the actual demand data management.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yunpeng Li ◽  
Xi Li

With the rapid development of the Internet, network attacks often occur, and network security is widely concerned. Searching for practical security risk assessment methods is a research hotspot in the field of network security. Network attack graph model is an active detection technology for the attack path. From the perspective of the attacker, it simulated the whole network attack scenario and then presented the dependency among the vulnerabilities in the target network in the way of directed graph. It is an effective tool for analyzing network vulnerability. This paper describes in detail the common methods and tools of network security assessment and analyzes the construction of theoretical model of attack graph, the optimization technology of attack graph, and the research status of qualitative and quantitative analysis technology of attack graph in network security assessment. The attack graph generated in the face of large-scale network is too complex to find the key vulnerability nodes accurately and quickly. Optimizing the attack graph and solving the key attack set can help the security manager better understand the security state of the nodes in the network system, so as to strengthen the security defense ability and guarantee the security of the network system. For all kinds of loop phenomena of directed attribute attack graph, the general method of eliminating loop is given to get an acyclic attack graph. On the basis of acyclic attack graph, an optimization algorithm based on path complexity is proposed, which takes atomic attack distance and atomic weight into consideration, and on the basis of simplified attack graph, minimum-cost security reinforcement is carried out for the network environment. Based on the ant colony algorithm, the adaptive updating principle of changing pheromone and the local searching strategy of the adaptive genetic algorithm are proposed to improve the ant colony algorithm. The experimental results show that compared with the ant colony algorithm, the improved ant colony algorithm can speed up the process of solving the optimal solution. When the number of attack paths is large, the advantages of the improved ant colony algorithm in solving accuracy and late search speed are more obvious, and it is more suitable for large-scale networks.


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