Towards optimal multi-objective models of network security: survey

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

An Analytical Evaluation of Network Security Modelling Techniques Applied to Manage Threats

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

Toward optimal multi-objective models of network security: Survey

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 novel risk assessment and optimisation model for a multi-objective network security countermeasure selection problem

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 Graph-Based Approach to Address Trust and Reputation in Ubiquitous Networks

The increasing popularity of virtual computing environments such as Cloud and Grid computing is helping to drive the realization of ubiquitous and pervasive computing. However, as computing becomes more entrenched in everyday life, the concepts of trust and risk become increasingly important. In this paper, we propose a new graph-based theoretical approach to address trust and reputation in complex ubiquitous networks. We formulate trust as a function of quality of a task and time required to authenticate agent-to-agent relationship based on the Zero-Common Knowledge (ZCK) authentication scheme. This initial representation applies a graph theory concept, accompanied by a mathematical formulation of trust metrics. The approach we propose increases awareness and trustworthiness to agents based on the values estimated for each requested task, we conclude by stating our plans for future work in this area

To Trust or Not to Trust? Developing Trusted Digital Spaces through Timely Reliable and Personalized Provenance

Organizations are increasingly dependent on data stored and processed by distributed, heterogeneous services to make critical, high-value decisions. However, these service-oriented computing environments are dynamic in nature and are becoming ever more complex systems of systems. In such evolving and dynamic eco-system infrastructures, knowing how data was derived is of significant importance in determining its validity and reliability. To address this, a number of advocates and theorists postulate that provenance is critical to building trust in data and the services that generated it as it provides evidence for data consumers to judge the integrity of the results. This paper presents a summary of the STRAPP (trusted digital Spaces through Timely Reliable And Personalised Provenance) project, which is designing and engineering mechanisms to achieve a holistic solution to a number of real-world service-based decision-support systems

A risk assessment and optimisation model for minimising network security risk and cost

A thesis submitted for the degree of Doctor of PhilosophyNetwork security risk analysis has received great attention within the scientific community, due to the current proliferation of network attacks and threats. Although, considerable effort has been placed on improving security best practices, insufficient effort has been expanded on seeking to understand the relationship between risk-related variables and objectives related to cost-effective network security decisions. This thesis seeks to improve the body of knowledge focusing on the trade-offs between financial costs and risk while analysing the impact an identified vulnerability may have on confidentiality, integrity and availability (CIA). Both security best practices and risk assessment methodologies have been extensively investigated to give a clear picture of the main limitations in the area of risk analysis. The work begins by analysing information visualisation techniques, which are used to build attack scenarios and identify additional threats and vulnerabilities. Special attention is paid to attack graphs, which have been used as a base to design a novel visualisation technique, referred to as an Onion Skin Layered Technique (OSLT), used to improve system knowledge as well as for threat identification. By analysing a list of threats and vulnerabilities during the first risk assessment stages, the work focuses on the development of a novel Risk Assessment and Optimisation Model (RAOM), which expands the knowledge of risk analysis by formulating a multi-objective optimisation problem, where objectives such as cost and risk are to be minimised. The optimisation routine is developed so as to accommodate conflicting objectives and to provide the human decision maker with an optimum solution set. The aim is to minimise the cost of security countermeasures without increasing the risk of a vulnerability being exploited by a threat and resulting in some impact on CIA. Due to the multi-objective nature of the problem a performance comparison between multi-objective Tabu Search (MOTS) Methods, Exhaustive Search and a multi-objective Genetic Algorithm (MOGA) has been also carried out. Finally, extensive experimentation has been carried out with both artificial and real world problem data (taken from the case study) to show that the method is capable of delivering solutions for real world problem data sets

A Visualisation Technique for the Identification of Security Threats in Networked Systems

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

Managing threats by the use of visualisation techniques

Identification of threats in networked systems is one of the important risk management processes that should be followed in order to be aware of all risks. In general, risk assessment guidelines for threat analysis propose to use historical organisation's data, thus, novel and unheard threats often are skipped from an analysis. In this paper, we propose a novel onion skin model (OSM) which consists of visualisation techniques, such as attack graphs, often applied for qualitative and quantitative risk assessment analyses. The model can be used to facilitate in threat identification and decision-making process by focusing on attack scenarios that illustrate vulnerable nodes, threats and shortest attack paths to the attacker's goal. The model can be used as part of risk management practices to improve security awareness through different attack scenarios and manage all system risks