Original Research
Developing a secured social networking site using information security awareness techniques
Submitted: 13 December 2013 | Published: 18 November 2014
About the author(s)
Julius O. Okesola, School of Computing, University of South Africa, South AfricaMarthie Grobler, School of Computing, University of South Africa, South Africa
Abstract
Background: Ever since social network sites (SNS) became a global phenomenon in almost every industry, security has become a major concern to many SNS stakeholders. Several security techniques have been invented towards addressing SNS security, but information security awareness (ISA) remains a critical point. Whilst very few users have used social circles and applications because of a lack of users’ awareness, the majority have found it difficult to determine the basis of categorising friends in a meaningful way for privacy and security policies settings. This has confirmed that technical control is just part of the security solutions and not necessarily a total solution. Changing human behaviour on SNSs is essential; hence the need for a privately enhanced ISA SNS.
Objective: This article presented sOcialistOnline – a newly developed SNS, duly secured and platform independent with various ISA techniques fully implemented.
Method: Following a detailed literature review of the related works, the SNS was developed on the basis of Object Oriented Programming (OOP) approach, using PhP as the coding language with the MySQL database engine at the back end.
Result: This study addressed the SNS requirements of privacy, security and services, and attributed them as the basis of architectural design for sOcialistOnline. SNS users are more aware of potential risk and the possible consequences of unsecured behaviours.
Conclusion: ISA is focussed on the users who are often the greatest security risk on SNSs, regardless of technical securities implemented. Therefore SNSs are required to incorporate effective ISA into their platform and ensure users are motivated to embrace it.
Keywords
Metrics
Total abstract views: 5034Total article views: 10796