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All Journal JURNAL SAINS PERTANIAN EQUATOR Knowledge Engineering and Data Science Jurnal Lektur Keagamaan Bulletin of Social Informatics Theory and Application
Darusalam, Darusalam
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Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Engineering Environmental Science Social Sciences

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Journal : knowledge engineering and data science

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Profiling and Identifying Individual Usersby Their Command Line Usage and Writing Style Darusalam, Darusalam; Ashman, Helen
Knowledge Engineering and Data Science
Publisher : citeus

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Abstract

Profiling and identifying individual users is an approach for intrusion detection in a computer system. User profiles are important in many applications since they record highly user-specific information - profiles are basically built to record information about users or for users to share experiences with each other. This research extends previous research on re-authenticating users with their user profiles. This research focuses on the potential to add psychometric user characteristics into the user model so as to be able to detect unauthorized users who may be masquerading as a genuine user. There are five participants involved in the investigation for formal language user identification. Additionally, we analyze the natural language of two famous writers, Jane Austen & William Shakespeare, in their written works to determine if the same principles can be applied to natural language use. This research used the n-gram analysis method for characterizing user’s style, and can potentially provide accurate user identification. As a result, n-gram analysis of a user's typed inputs offers another method for intrusion detection as it may be able to both positively and negatively identify users. The contribution of this research is to assess the use of a user’s writing styles in both formal language and natural language as a user profile characteristic that could enable intrusion detection where intruders masquerade as real users.
The Diffusion of ICT for Corruption Detectionin Open Government Data Darusalam, Darusalam; Said, Jamaliah; Omar, Normah; Janssen, Marijn; Sohag, Kazi
Knowledge Engineering and Data Science
Publisher : citeus

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Corruption occurs in many places within the government. To tackle the issue, open data can be used as one of the tools in creating more insight into the government. The premise of this paper is to support the notion that data opening can bring up new ways of fighting corruption. The current paper aimed at investigating how open data can be employed to detect corruption. This open data is trivial due to challenges like information asymmetry among stakeholders, data might only be opened partly, different sources of data need to be combined, and data might not be easy to use, might be biased or even manipulated. The study was conducted using a literature review approach. The reviews implied that corruption can be detected using Open Government Data, Thus, by conducting the open data technique within the government, the public could monitor the activities of the governments. The practical contribution of this paper is expected to assist the government in detecting corruption by using a data-driven approach. Furthermore, the scientific contribution will originate from the development of a framework reference architecture to uncover corruption cases.
Co-Authors Ashman, Helen DIVANI, FRANSISKUS ERMAN ERMAN Iskandar, Austin Fascal Janssen, Marijn Komaruddin Komaruddin Omar, Normah Pangestu, Arief Yoga Rosyidin, Adjie Said, Jamaliah Sohag, Kazi Tantri Palupi