Evaluation of information security risks using hybrid assessment model

This paper developed a method to assess information security risks in e-healthcare. Specifically, it first developed a static E-Healthcare Information Security Risk (EHISR) model to present thirty-three security risk factors by identifying information security threats and their sources in e-healthcare. Second, a dynamic E-Healthcare Information Flow (EHIF) model was developed to logically link these information risk factors in the EHISR model. Pattern analysis showed that information security risks could be classified into two levels, and versatility analysis showed that the overall security risks for eight information flows were close with a range from 55% to 86%. Third, one quantifiable approach based on a relative-weighted assessment model was developed to demonstrate how to assess the information security risks in e-healthcare. This quantitative security risk measurement establishes a reference point for assessing e-healthcare security risks and assists managers in selecting a reliable information flow infrastructure with a lower security risk level.

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INFORMATION SECURITY ASSESSMENT BASED ON MACHINE LEARNING TECHNOLOGY-FUZZY-GRA-AHP

International Journal of Research -GRANTHAALAYAH ◽

10.29121/granthaalayah.v7.i6.2019.800 ◽

2019 ◽

Vol 7 (6) ◽

pp. 230-240

Author(s):

Mei-Er Zhuang ◽

Wen-Tsao Pan

Keyword(s):

Machine Learning ◽

Information Security ◽

Assessment Model ◽

Security Level ◽

Learning Technology ◽

Security Assessment ◽

Security Risks ◽

Gray Relation Analysis ◽

Fuzzy Gra ◽

Fuzzy Computing

With the advent of the information age, information security has become an urgent problem to be solved. Various application and platforms have not only brought convenience to people, but also brought hidden dangers - information security risks. This paper uses some of the machine learning technology - fuzzy computing and gray relation analysis (GRA), to analyze data of the three major video platforms of China, and takes the information security level as a new criterion to conduct the evaluation of their performance. An assessment model is constructed based on machine learning technology, namely the combination of fuzzy computing and GRA and analytic hierarchy process (AHP). Conclusions can be drawn as follows. First, consumers’ perception of video platform information security level is constantly being strengthened. Second, information security risks are affecting consumers' choice decisions about video platforms, and the weights will continue to increase. Third, video platforms are paying more attention to information security construction.

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A Web based Information Security Risks Assessment Model

Journal of Internet Technology and Secured Transaction ◽

10.20533/jitst.2046.3723.2015.0050 ◽

2015 ◽

Vol 4 (3) ◽

pp. 396-404

Author(s):

B. K. Alese ◽

O. Oyebade ◽

O. Iyare ◽

Osuolale A. Festus ◽

A. F. Thompson

Keyword(s):

Information Security ◽

Assessment Model ◽

Security Risks ◽

Web Based ◽

Risks Assessment

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Information security risks assessment in telecommunication network of the university

2016 Dynamics of Systems, Mechanisms and Machines (Dynamics) ◽

10.1109/dynamics.2016.7818967 ◽

2016 ◽

Cited By ~ 1

Author(s):

Igor V. Anikin

Keyword(s):

Information Security ◽

Telecommunication Network ◽

Security Risks ◽

Risks Assessment ◽

The University

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Research on Network and Information Security Risks of County-level Fusion Media in Zhejiang Province

10.1145/3482632.3487472 ◽

2021 ◽

Author(s):

Minyan Ma

Keyword(s):

Information Security ◽

Zhejiang Province ◽

County Level ◽

Security Risks ◽

Level Fusion

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Knowledge Transfer in Information Security Capacity Building for Community-Based Organizations

International Journal of Knowledge Management ◽

10.4018/ijkm.2015100104 ◽

2015 ◽

Vol 11 (4) ◽

pp. 52-69 ◽

Cited By ~ 1

Author(s):

Janine L. Spears ◽

Tonia San Nicolas-Rocca

Keyword(s):

Service Learning ◽

Information Security ◽

Knowledge Transfer ◽

Initial Study ◽

Security Risk ◽

Security Risks ◽

Community Based ◽

Services Sector ◽

Community Based Organizations ◽

Study Results

Community-based organizations (CBOs) in the health and human services sector handle very sensitive client information, such as psychiatric, HIV testing, criminal justice, and financial records. With annual revenue often in the range of $1 to $10 million, these organizations typically lack the financial, labor, and technical resources to identify and manage information security risks within their environment. Therefore, information security risk assessments were conducted at CBOs as part of a university service learning course intended to ultimately improve security within participating CBOs. Knowledge transfer between trainees and trainers is essential in order for security improvements to be realized. Therefore, this paper constructs a theoretical model of knowledge transfer that is used as a lens through which to examine initial study results of the CBO interventions as part of an exploratory study.

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