AI and Cybersecurity Research Publications

In this paper we present a new simulator to investigate consensus within organisations, based on organisational structure, team dynamics, and artefacts. We model agents who can interact with each other and with artefacts, as well as the mathematical models that govern agent behaviour. We show that for a fixed problem size, there is a maximum time within which all agents will reach consensus, independent of number of agents. We present the results from simulating wide ranges of problem sizes and agent group sizes and report on two significant statistics; the time to reach consensus and the effort to reach consensus. The time to reach consensus has implications for project delivery timelines, and the effort relates to project economics.

@{496,
  author = {Johannes Vorster and Louise Leenen},
  title = {Vorster, J. and Leenen L. Consensus Simulator for Organizational Structures. . Rome, Italy, 12 – 14 July 2023.},
  abstract = {In this paper we present a new simulator to investigate consensus within organisations, based on organisational
structure, team dynamics, and artefacts. We model agents who can interact with each other and with artefacts,
as well as the mathematical models that govern agent behaviour. We show that for a fixed problem size, there
is a maximum time within which all agents will reach consensus, independent of number of agents. We present
the results from simulating wide ranges of problem sizes and agent group sizes and report on two significant
statistics; the time to reach consensus and the effort to reach consensus. The time to reach consensus has
implications for project delivery timelines, and the effort relates to project economics.},
  year = {2018},
  journal = {The 13th International Conference on Simulation and Modelling Methodologies, Technologies and Applications (SimulTech)},
  month = {12 - 14 July 2023},
  address = {Rome, Italy},
}

In this paper we describe a research project to develop an optimal information retrieval system in an Information Operations domain. Information Operations is the application and management of information to gain an advantage over an opponent and to defend one’s own interests. Corporations, governments, and military forces are facing increasing exposure to strategic information-based actions. Most national defence and security organisations regard Information Operations as both a defensive and offensive tool, and some commercial institutions are also starting to recognise the value of Information Operations. An optimal information retrieval system should have the capability to extract relevant and reasonably complete information from different electronic data sources which should decrease information overload. Information should be classified in a way such that it can be searched and extracted effectively. The authors of this paper have completed an initial phase in the investigation and design of a knowledge system that can be used to extract relevant and complete knowledge for the planning and execution of Information Operations. During this initial phase of the project, we performed a needs analysis and problem analysis and our main finding is the recommendation of the use of logic-based ontologies: it has the advantage of an unambiguous semantics, facilitates intelligent search, provides an optimal trade-off between expressivity and complexity, and yields optimal recall of information. The risk of adopting this technology is its status as an emerging technology and therefore we include recommendations for the development of a prototype system.

@{465,
  author = {Louise Leenen and Ronell Alberts and Katarina Britz and Aurona Gerber and Tommie Meyer},
  title = {Developing a Knowledge System for Information Operations},
  abstract = {In this paper we describe a research project to develop an optimal information retrieval system in an Information Operations domain. Information Operations is the application and management of information to gain an advantage over an opponent and to defend one’s own interests. Corporations, governments, and military forces are facing increasing exposure to strategic information-based actions. Most national defence and security organisations regard Information Operations as both a defensive and offensive tool, and some commercial institutions are also starting to recognise the value of Information Operations. An optimal information retrieval system should have the capability to extract relevant and reasonably complete information from different electronic data sources which should decrease information overload. Information should be classified in a way such that it can be searched and extracted effectively. The authors of this paper have completed an initial phase in the investigation and design of a knowledge system that can be used to extract relevant and complete knowledge for the planning and execution of Information Operations. During this initial phase of the project, we performed a needs analysis and problem analysis and our main finding is the recommendation of the use of logic-based ontologies: it has the advantage of an unambiguous semantics, facilitates intelligent search, provides an optimal trade-off between expressivity and complexity, and yields optimal recall of information. The risk of adopting this technology is its status as an emerging technology and therefore we include recommendations for the development of a prototype system.},
  year = {2011},
  journal = {6th International Conference on Information Warfare and Security},
  month = {17/03-18/03},
  address = {Washington D.C., United States of America},
  isbn = {978-1-906638-93-1},
  doi = {10204/4951},
}