• An analytical evaluation of network security modelling techniques applied to manage threats

      Viduto, Valentina; Maple, Carsten; Huang, Wei (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2010)
      The current ubiquity of information coupled with the reliance on such data by businesses has led to a great deal of resources being deployed to ensure the security of this information. Threats can come from a number of sources and the dangers from those insiders closest to the source have increased significantly recently. This paper focuses on techniques used to identify and manage threats as well as the measures that every organisation should consider to put into action. A novel game-based onion skin model has been proposed, combining techniques used in theory-based and hardware-based hardening strategies.
    • A multi-objective genetic algorithm for minimising network security risk and cost

      Viduto, Valentina; Maple, Carsten; Huang, Wei; Bochenkov, Alexey (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2012)
      Security countermeasures help ensure information security: confidentiality, integrity and availability(CIA), by mitigating possible risks associated with the security event. Due to the fact, that it is often difficult to measure such an impact quantitatively, it is also difficult to deploy appropriate security countermeasures. In this paper, we demonstrate a model of quantitative risk analysis, where an optimisation routine is developed to help a human decision maker to determine the preferred trade-off between investment cost and resulting risk. An offline optimisation routine deploys a genetic algorithm to search for the best countermeasure combination, while multiple risk factors are considered. We conduct an experimentation with real world data, taken from the PTA(Practical Threat Analysis) case study to show that our method is capable of delivering solutions for real world problem data sets. The results show that the multi-objective genetic algorithm (MOGA) approach provides high quality solutions, resulting in better knowledge for decision making.
    • A novel risk assessment and optimisation model for a multi-objective network security countermeasure selection problem

      Viduto, Valentina; Maple, Carsten; Huang, Wei; López-Peréz, David (els, 2012-06)
      Budget cuts and the high demand in strengthening the security of computer systems and services constitute a challenge. Poor system knowledge and inappropriate selection of security measures may lead to unexpected financial and data losses. This paper proposes a novel Risk Assessment and Optimisation Model (RAOM) to solve a security countermeasure selection problem, where variables such as financial cost and risk may affect a final decision. A Multi-Objective Tabu Search (MOTS) algorithm has been developed to construct an efficient frontier of non-dominated solutions, which can satisfy organisational security needs in a cost-effective manner.
    • A novel strategy for optimal security investments

      Viduto, Valentina; Huang, Wei; Maple, Carsten; University of Bedfordshire (2010)
    • Towards optimal multi-objective models of network security: survey

      Viduto, Valentina; Huang, Wei; Maple, Carsten; University of Bedfordshire, UK (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2011)
      Information security is an important aspect of a successful business today. However, financial difficulties and budget cuts create a problem of selecting appropriate security measures and keeping networked systems up and running. Economic models proposed in the literature do not address the challenging problem of security countermeasure selection. We have made a classification of security models, which can be used to harden a system in a cost effective manner based on the methodologies used. In addition, we have specified the challenges of the simplified risk assessment approaches used in the economic models and have made recommendations how the challenges can be addressed in order to support decision makers.
    • A visualisation technique for the identification of security threats in networked systems

      Maple, Carsten; Viduto, Valentina (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2010)
      This paper is primarily focused on the increased IT complexity problem and the identification of security threats in networked systems. Modern networking systems, applications and services are found to be more complex in terms of integration and distribution, therefore, harder to be managed and protected. CIOs have to put their effort on threat's identification, risk management and security evaluation processes. Objective decision making requires measuring, identifying and evaluating all enterprise events, either positive (opportunities) or negative (risks) and keeping them in perspective with the business objectives. Our approach is based on a visualisation technique that helps in decision making process, focusing on the threat identification using attack scenarios. For constructing attack scenarios we use the notion of attack graphs, as well as layered security approach. The proposed onion skin model combines attack graphs and security layers to illustrate possible threats and shortest paths to the attacker's goal. By providing few examples we justify the advantage of the threat identification technique in decision making process.