Estimating computer network security scenarios with association rules

Singha, Anjani Kumar; Singh, Harsh Pratap; Kundu, Shakti; Tiwari, Pradeep Kumar; Rajput, Ajeet Singh

doi:10.47974/JDMSC-1876

Open Access Research Article

Estimating computer network security scenarios with association rules

Anjani Kumar Singhaanjani348@gmail.comDepartment of Computer ApplicationsDelhi-NCR CampusSRM Institute of Science and Technology (Deemed to be University)Ghaziabad, Uttar Pradesh, 201204, IndiaView full profile → , Harsh Pratap Singhdrharshprataps@gmail.comDepartment of Computer Science and EngineeringSri Vaishnav Vidhyapeeth VishwavidyalayaIndore, Madhya Pradesh, 453331, IndiaView full profile → , Shakti Kundushaktikundu@gmail.comSchool of Engineering and TechnologyComputer Science EngineeringBML Munjal UniversityGurugram, Haryana, 122413, IndiaView full profile → , ^*Pradeep Kumar TiwariCorresponding authorPradeeptiwari.mca@gmail.comDepartment of Computer Science and ApplicationsDr. Vishwanath Karad MIT World Peace University, PunePune, Maharashtra, 411005, IndiaView full profile → , Ajeet Singh Rajputajeetsinghrajput@gmail.comDepartment of Computer Science & EngineeringMedicaps UniversityIndore, Madhya Pradesh, IndiaView full profile →

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pp. 223–236Vol. 27Issue 2-AMarch 2024DOI: 10.47974/JDMSC-1876 Crossmark XML

Published Online:: 06 Apr 2024
Article type:: Research Article
Language:: EN
Article no.:: JDMSC-1876
Pages:: 223–236

Abstract

Traditional NSSA (network security situational awareness) systems are problems familiarize to enormous for complicated network circumstances due to instrument limitations, inadequate and data fusion capabilities. This paper proposes the investigation of Association Rules (AR) based NSS (network security situation) prediction technology. Mining for regulations for associations to remedy this issue re- confidence support framework is enhanced by incorporating an interest. The assessment standard is revised, and the worth of AR is reassessed established on a discussion of associated standard ideas and algorithms AR mining. This research proposes an MFP-interest algorithm that combines an alert AR pattern with a degree of interest. The MFP-interest algorithm was evaluated. The researcher found that the MFP-interest algorithm is capable of accurately predicting NSS. The majority of time points have relative error ranges of less than 0.035.

Keywords

Computer network security Association rules Data mining Security scenarios and Risk assessment

Subject Classifications

Primary 93A30Secondary 49K15

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