Browsing by Author "Sidorenko, Tatjana"

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    Agent-Based Modelling of Offensive Actors in Cyberspace
    (2021-12) Sidorenko, Tatjana; Hodges, D; Buckley, O
    With the rise of the Information Age, there has also been a growing rate of attacks targeting information. In order to better defend against these attacks being able to understand attackers and simulate their behaviour is of utmost importance. A recent approach of using serious games provides an avenue to explore offensive cyber attacks in a safe and fun environment. There exists a wide range of cyber attackers, with varying levels of expertise whose motivations are different. This project provides a novel contribution in using games to allow people to role play as malicious attackers and then using these games as inputs into the simulation. A board game has been designed that emulates a cyber environment, where players represent offensive actors, with seven roles - Cyber Mercenary (low and high capability), State-backed (low and high capability), Script Kiddy, Hacktivist and Counter-culture (not motivated by finances or ideology). The facilitator or the Games Master (GM) represents the organisation under attack, and players use the Technique cards to perform attacks on the organisation, all cards are sourced from existing Tools, Techniques and Procedures (TTPs). Along with the game, players also provided responses to a questionnaire that encapsulated three individual differences: Sneider's self-report, DOSPERT and Barratt's Impulsiveness scale. There were a total of 15 players participating in 13 games, and three key groups of individual differences players. No correlation was identifed with the individual Technique card pick rate and role. However, the complexity of the attack patterns (Technique card chains) was modulated by roles, and the players' individual differences. A proof-of-concept simulation has been made using an Agent-Based Modelling framework that re-plays the actions of a player. One of the aspects of future work is the exploitation of the game data to be used as a learning model to create intelligent standalone agents.
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    Automated Question Generation for Delphi Studies
    (Cranfield University, 2019-11-19 15:41) Sidorenko, Tatjana
    Surveys are a relatively easy and low-cost method for gathering a group opinion on a given subject. Despite there being several survey platforms the adaptation of these platforms for complex Delphi studies still leaves much to be desired. ‘Qualtrics Delphi Toolkit’ (QDT) is a tool that is designed to make the Qualtrics survey platform better adapted for Delphi studies.The Delphi method has been devised to aid forecasting and decision-making. It is a method that gauges the wisdom of crowds to estimate a solution or to come up with an accepted definition. A Delphi study consists of a number of rounds. In the first round, a panel of experts is gathered, each expert shares their opinion on the selected topic. In the second round, the opinions are compiled into a single unified summary that is then presented back to the experts. Each expert is then given an option to alter their original answer for the changes to then be propagated into the summary answer. This procedure is repeated until a consensus is reached. As the use of the Internet has become widespread it has allowed an increase in the magnitude of such studies, through facilitating access to a greater range of experts, as well as enabling the rapid gathering of more information. The tool support, however is often not able to efficiently manage this scale of data collection. Certain functionality, such as the ability to randomly sample a set of questions is not efficiently achievable at the scale required for large Delphi studies. The need for better tool support has become evident after facing the challenge of presenting a list of over 300 hacking techniques to a group of experts. This required stochastically presenting a subset of these techniques maximising expert engagement whilst minimising fatigue and performance decline.QDT is a tool that is written to extend the functionality of a well-known survey platform, Qualtrics, to automatically generate questions relating to a Delphi study. Currently, Qualtrics offers a feature called ‘Piped text’ that passes information from one question to the next. However this feature alone is not enough when there is a requirement to generate large volumes of questions based on previous questions. QDT is designed to automatically create questions from a list of strings. Together with Qualtrics's conditional formatting it allows efficient creation of large volumes of questions where the question text depends on user's previous choice. This will enable the efficient creation of large-scale survey-assisted Delphi studies where the list of topics is very large.
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    Board Games as a Behavioural Collection Method
    (Cranfield University, 2020-11-27 12:18) Sidorenko, Tatjana
    Traditionally, games have been viewed as a form of entertainment. Yet, given how engaging games can be their effects can be beneficial in many domains. This paper explores the use of games as a methodology of exploring the decision-making processes demonstrated by a group of information security specialists when role-playing as malicious actors.To achieve this a board game has been designed which enables players to impersonate different types of attackers each with different motivations and goals. Each player is given a set of tools, techniques and procedures (TTPs) in form of cards and a set of end goals which need to be achieved in order to ‘win’ the game. By interacting with the facilitator, who is also representing the defending organisation or location, they voice out their intended actions and decisions and play a TTP card of their choice. By adopting a persona in an engaging fictional setting players are freed from concerns associated with self-image maintenance and concerns about reputational damage and ultimately, are better able to construct creative and malicious attacks. The game methodology also provides a less limited framework for the data gathering, and with suitable facilitation allows the capture of a very diverse set of attacks.By using this methodology, it is possible to gather a more diverse set of both decision-making behaviour and attacks, improving our understanding of offensive actors. This understanding will then be used to influence the creation of an agent-based simulation of these actors and scenarios.