Prediction of Computer Network Security Situation Based on Association Rules Mining

Xue, Rixin; Tang, Peng; Fang, Shudong

doi:10.1155/2022/2794889

Cited by 13 publications

(4 citation statements)

References 17 publications

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“…Therefore, how to effectively deal with these threats has become one of the urgent issues to be solved at present. In order to better understand the changing trends of network security posture, relevant data statistics and analysis are needed [8,9]. Through the collection and processing of historical data, some important conclusions can be obtained: first, the number of cyber attacks is on the rise year by year; second, different types of attacks are emerging and developing; finally, the complexity of attack methods is increasing.…”

Section: Computation Of Cybersecurity Posturementioning

confidence: 99%

Research and application of network security detection technology based on computer vision

2023

Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023)

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With the development of the Internet and the advent of the digital era, the Internet has become an indispensable part of people's daily lives. However, along with the development of the network, there are more and more cyber attacks, which not only pose a threat to personal privacy, but also have a huge impact on national security and social stability. Therefore, how to effectively protect our network security has become one of the urgent issues to be solved. In the traditional network security defense, a rule-based approach is usually used for monitoring and analysis, but this approach has certain limitations. Because the network environment is complex and ever-changing, and various types of attacks are emerging, it is difficult to detect and respond to new attacks in a timely manner in the traditional way. More advanced technical means need to be introduced to improve the level of network security assurance. Therefore, this paper proposes a computer vision-based network security detection system based on the summary of existing network security detection methods and the development status of the computer vision field. The main idea of this system is to use computer vision technology to realize the functions of automatic extraction, characterization and classification of network data, so as to improve the efficiency and accuracy of network security detection.

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Section: Computation Of Cybersecurity Posturementioning

confidence: 99%

Research and application of network security detection technology based on computer vision

2023

Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023)

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“…Consequently, the rising number of cyber security attacks, including ransomware, denial-of-service, password, and phishing attacks, led to massive data breaches and losses in several reputable financial and industrial businesses, including government and military networks. This advancement in computer networks makes people distrust enterprises, which, in turn, leads firms to mistrust traditional tools and safeguards ( Xue, Tang & Fang, 2022 ; Fedele & Roner, 2022 ; Kärkkäinen, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

A novel smart multilevel security approach for secure data outsourcing in crisis

Sarhan

2023

PeerJ Computer Science

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The Interconnected Network or the Internet has revolutionized digital communications. It has expanded worldwide over the past four decades due to numerous features such as connectivity, transparency, hierarchy, and openness. Several drawbacks, including mobility, scalability, controllability, security, etc., have been presented due to continuous developments. Although several network paradigms exist to address such drawbacks, many issues still persist. This research proposed a future network paradigm that addresses multilevel security shortcomings. It suggested the following: (i) a two-router network-based cyber security architecture for multilevel data sharing; (ii) using a scheduler to deal with the multilevel transmitted packets scheduling problem; (iii) five algorithms for the studied difficult problem; and (iv) providing an experimental result to show the optimal results obtained by the developed algorithms and comparing it with algorithms in the literature. The experimental result shows that the random-grouped classification with shortest scheduling algorithm (RGS) performed the best at 37.7% with a gap of 0.03. This result proves the practicality of our approach in terms of two-machine scheduling problems.

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“…The current emphasis of cybersecurity research is to extract correlations as well as potential attacks from cyber threat intelligence information. Technologies such as correlation analysis [10], causal inference [11], and semantic reasoning [12] technologies based on knowledge modeling have evolved into novel solutions in the context of big data.…”

Section: Introductionmentioning

confidence: 99%

Recent Progress of Using Knowledge Graph for Cybersecurity

et al. 2022

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In today’s dynamic complex cyber environments, Cyber Threat Intelligence (CTI) and the risk of cyberattacks are both increasing. This means that organizations need to have a strong understanding of both their internal CTI and their external CTI. The potential for cybersecurity knowledge graphs is evident in their ability to aggregate and represent knowledge about cyber threats, as well as their ability to manage and reason with that knowledge. While most existing research has focused on how to create a full knowledge graph, how to utilize the knowledge graph to tackle real-world industrial difficulties in cyberattack and defense situations is still unclear. In this article, we give a quick overview of the cybersecurity knowledge graph’s core concepts, schema, and building methodologies. We also give a relevant dataset review and open-source frameworks on the information extraction and knowledge creation job to aid future studies on cybersecurity knowledge graphs. We perform a comparative assessment of the many works that expound on the recent advances in the application scenarios of cybersecurity knowledge graph in the majority of this paper. In addition, a new comprehensive classification system is developed to define the linked works from 9 core categories and 18 subcategories. Finally, based on the analyses of existing research issues, we have a detailed overview of various possible research directions.

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Prediction of Computer Network Security Situation Based on Association Rules Mining

Cited by 13 publications

References 17 publications

Research and application of network security detection technology based on computer vision

Research and application of network security detection technology based on computer vision

A novel smart multilevel security approach for secure data outsourcing in crisis

Recent Progress of Using Knowledge Graph for Cybersecurity

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