Structuring the Chaos: Enabling Small Business Cyber-Security Risks & Assets Modelling with a UML Class Model
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ID: 282189
2024
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Abstract
Small businesses are increasingly adopting IT, and consequently becoming more
vulnerable to cyber-incidents. Whilst small businesses are aware of the
cyber-security risks, many struggle with implementing mitigations. Some of
these can be traced to fundamental differences in the characteristics of small
business versus large enterprises where modern cyber-security solutions are
widely deployed.
Small business specific cyber-security tools are needed. Currently available
cyber-security tools and standards assume technical expertise and time
resources often not practical for small businesses. Cyber-security competes
with other roles that small business owners take on, e.g. cleaning, sales etc.
A small business model, salient and implementable at-scale, with simplified
non-specialist terminologies and presentation is needed to encourage sustained
participation of all stakeholders, not just technical ones.
We propose a new UML class (Small IT Data (SITD)) model to support the often
chaotic information-gathering phase of a small business' first foray into
cyber-security. The SITD model is designed in the UML format to help small
business implement technical solutions. The SITD model structure stays relevant
by using generic classes and structures that evolve with technology and
environmental changes. The SITD model keeps security decisions proportionate to
the business by highlighting relationships between business strategy tasks and
IT infrastructure.
We construct a set of design principles to address small business
cyber-security needs. Model components are designed in response to these needs.
The uses of the SITD model are then demonstrated and design principles
validated by examining a case study of a real small business operational and IT
information. The SITD model's ability to illustrate breach information is also
demonstrated using the NotPetya incident.
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| Authors | Tracy Tam; Asha Rao; Joanne Hall |
| Journal | arXiv |
| Year | 2024 |
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