Applying Cognitive Control Modes to Identify Security Fatigue Hotspots

Simon Parkin, Kat Krol, Ingolf Becker and M. Angela Sasse


Security tasks can burden the individual, to the extent that security fatigue promotes had security habits. Here we revisit a series of user-centred studies of security mechanisms as part of regular routines, such as two-factor authentication. These studies inform reflection upon the perceived contributors and consequences of fatigue, and strategies that a person may adopt in response to feeling overburdened by security. The fatigue produced by security tasks is then framed using a model of cognitive control modes, which explores human performance and error. Security tasks are then considered in terms of modes such as unconscious routines and knowledge-based ad-hoc approaches. Conscious attention can support adaptation to novel security situations, but is error-prone and tiring; both simple security routines and technology-driven automation can minimise effort, but may miss cues from the environment that a nuanced response is required.

Date: 22 June 2016
Published: SOUPS Workshop on Security Fatigue                                                                                                           Publisher: USENIX
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Productive Security: A Scalable Methodology for Analysing Employee Security Behaviour

Adam Beautement, Ingolf Becker, Simon Parkin, Kat Krol and M. Angela Sasse


Organisational security policies are often written without sufficiently taking in to account the goals and capabilities of the employees that must follow them. Effective security management requires that security managers are able to assess the effectiveness of their policies, including their impact on employee behaviour. We present a methodology for gathering large scale data sets on employee behaviour and attitudes via scenario-based surveys. The survey questions are grounded in rich data drawn from interviews, and probe perceptions of security measures and their impact. Here we study employees of a large multinational company, demonstrating that our approach is capable of determining important differences between various population groups. We also report that our work has been used to set policy within the partner organisation, illustrating the real-world impact of our research.

Date: 22 June 2016
Published: Paper included in the Proceedings of the Twelfth Symposium on Usable Privacy and Security (SOUPS 2016).                                                                                                                                                                              Publisher: USENIX
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Social Learning in Systems Security Modelling

Tristan Caulfield, Michelle Catherine Baddeley and David Pym


Usable Systems modelling can be used to help improve decisions around security policy. By modelling a complex system, the interactions between its structure, environment, technology, policies, and human agents can be understood and the effects of different policy choices on the system can be explored. Of key importance is capturing the behaviour of human agents within the system. In this paper we present a model of social learning from behavioural economics and then integrate it into a mathematical systems modelling framework. We demonstrate this with an example: employees deciding whether or not to challenge people without ID badges in the office.
Date: 23 September 2016
Published: Social Stimulation Conference Paper September 2016
Publisher: Research Gate
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Optimising time allocation for network defence

Tristan Caulfield and Andrew Fielder


The presence of unpatched, exploitable vulnerabilities in software is a prerequisite for many forms of cyberattack. Because of the almost inevitable discovery of a vulnerability and creation of an exploit for all types of software, multiple layers of security are usually used to protect vital systems from compromise. Accordingly, attackers seeking to access protected systems must circumvent all of these layers. Resource- and budget-constrained defenders must choose when to execute actions such as patching, monitoring and cleaning infected systems in order to best protect their networks. Similarly, attackers must also decide when to attempt to penetrate a system and which exploit to use when doing so. We present an approach to modelling computer networks and vulnerabilities that can be used to find the optimal allocation of time to different system defence tasks. The vulnerabilities, state of the system and actions by the attacker and defender are used to build partially observable stochastic games. These games capture the uncertainty about the current state of the system and the uncertainty about the future. The solution to these games is a policy, which indicates the optimal actions to take for a given belief about the current state of the system. We demonstrate this approach using several different network configurations and types of player. We consider a trade-off for the system administrator, where they must allocate their time to performing either security-related tasks or performing other required non-security tasks. The results presented highlight that, with the requirement for other tasks to be performed, following the optimal policy means spending time on only the most essential security-related tasks, while the majority of time is spent on non-security tasks.

Date: 5 November 2015
Published: Journal of Cybersecurity, 2015, 1–15
Publisher: Oxford Academic
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Decision support approaches for cyber security investment

Andrew Fieldera, Emmanouil Panaousisb, Pasquale Malacariac, Chris Hankina, Fabrizio Smeraldi


When investing in cyber security resources, information security managers have to follow effective decision-making strategies. We refer to this as the cyber security investment challenge. In this paper, we consider three possible decision support methodologies for security managers to tackle this challenge. We consider methods based on game theory, combinatorial optimisation, and a hybrid of the two. Our modelling starts by building a framework where we can investigate the effectiveness of a cyber security control regarding the protection of different assets seen as targets in presence of commodity threats. As game theory captures the interaction between the endogenous organisation’s and attackers’ decisions, we consider a 2-person control game between the security manager who has to choose among different implementation levels of a cyber security control, and a commodity attacker who chooses among different targets to attack. The pure game theoretical methodology consists of a large game including all controls and all threats. In the hybrid methodology the game solutions of individual control-games along with their direct costs (e.g. financial) are combined with a Knapsack algorithm to derive an optimal investment strategy. The combinatorial optimisation technique consists of a multi-objective multiple choice Knapsack based strategy. To compare these approaches we built a decision support tool and a case study regarding current government guidelines. The endeavour of this work is to highlight the weaknesses and strengths of different investment methodologies for cyber security, the benefit of their interaction, and the impact that indirect costs have on cyber security investment. Going a step further in validating our work, we have shown that our decision support tool provides the same advice with the one advocated by the UK government with regard to the requirements for basic technical protection from cyber attacks in SMEs.

Date: June 2016
Published: Decision Support Systems Volume 86, June 2016, Pages 13–23
Publisher: Elsevier
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Efficient Numerical Frameworks for Multi-objective Cyber Security Planning

Simon Parkin, Samy Driss, Kat Krol and M. Angela Sasse


We consider the problem of optimal investment in cyber-security by an enterprise. Optimality is measured with respect to the overall (1) monetary cost of implementation, (2) negative side-effects of cyber-security controls (indirect costs), and (3) mitigation of the cyber-security risk. We consider “passive” and “reactive” threats, the former representing the case where attack attempts are independent of the defender’s plan, the latter, where attackers can adapt and react to an implemented cyber-security defence. Moreover, we model in three different ways the combined effect of multiple cyber-security controls, depending on their degree of complementarity and correlation. We also consider multi-stage attacks and the potential correlations in the success of different stages. First, we formalize the problem as a non-linear multi-objective integer programming. We then convert them into Mixed Integer Linear Programs (MILP) that very efficiently solve for the exact Pareto-optimal solutions even when the number of available controls is large. In our case study, we consider 27 of the most typical security controls, each with multiple intensity levels of implementation, and 37 common vulnerabilities facing a typical SME. We compare our findings against expert-recommended critical controls. We then investigate the effect of the security models on the resulting optimal plan and contrast the merits of different security metrics. In particular, we show the superior robustness of the security measures based on the “reactive” threat model, and the significance of the hitherto overlooked role of correlations.

Published: ESORICS 2016: Computer Security – ESORICS 2016 pp 179-197                                                    Publisher: Springer
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An Exploratory Study of User Perceptions of Payment Methods in the UK and the US

Kat Krol, Muhammad Sajidur Rahman, Simon Parkin, Emiliano De Cristofaro and Eugene Y. Vasserman


This paper presents the design and the results of a cross-cultural study of user perceptions and attitudes toward electronic payment methods. We conduct a series of semi-structured interviews involving forty participants (20 in London, UK, and 20 in Manhattan, KS, USA) to explore how individuals use the mechanisms available to them within their routine payment and banking activities. We also study their comprehension of payment processes, the perceived effort and impact of using different methods, as well as direct or indirect recollections of (suspected or actual) fraud and related interactions with banks and retailers. By comparing UK and US participants, we also elicit commonalities and differences that may help better understand, if not predict, attitudes of US customers once technologies like Chip-and-PIN are rolled out – for instance, several US participants were confused by how to use it, while UK participants found it convenient. Our results show that purchasing habits as well as the availability of rewards schemes are primary criteria influencing choices relating to payment technologies, and that inconsistencies, glitches, and other difficulties with newer technologies generate frustration sometimes leading to complete avoidance of new payment methods.

Date: 21 February 2016
Published: Workshop on Useable Security USEC 2016, San Diego, CA                                              Publisher: Internet Society
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Better the Devil You Know: A User Study of Two CAPTCHAs and a Possible Replacement Technology

Kat Krol, Simon Parkin and M. Angela Sasse


CAPTCHAs are difficult for humans to use, causing frustration. Alternatives have been proposed, but user studies equate usability to solvability. We consider the user perspective to include workload and context of use. We assess traditional text-based CAPTCHAs alongside PlayThru, a ‘gamified’ verification mechanism, and NoBot, which uses face biometrics. A total of 87 participants were tasked with ticket-buying across three conditions: (1) all three mechanisms in comparison, and NoBot three times (2) on a laptop, and (3) on a tablet. A range of quantitative and qualitative measurements explored the user perspective. Quantitative results showed that participants completed reCAPTCHAs quickest, followed by PlayThru and NoBot. Participants were critical of NoBot in comparison but praised it in isolation. Despite reporting negative experiences with reCAPTCHAs, they were the preferred mechanism, due to familiarity and a sense of security and control. Although slower, participants praised NoBot’s completion speeds, but regarded using personal images as invading privacy.

Date: 21 February 2016
Published: Workshop on Useable Security USEC 2016, San Diego, CA                                                                  Publisher: Internet Society                                                                                                                                                       Publisher URL:                                                                                       DOI:

Assessing the User Experience of Password Reset Policies in a University

Simon Parkin, Samy Driss, Kat Krol and M. Angela Sasse


Organisations often provide helpdesk services to users, to resolve any problems that they may have in managing passwords for their provisioned accounts. Helpdesk logs record password change events and support requests, but overlook the impact of compliance upon end-user productivity. System managers are not incentivised to investigate these impacts, so productivity costs remain with the end-user. We investigate how helpdesk log data can be analysed and augmented to expose the user’s personal costs. Here we describe exploratory analysis of a university’s helpdesk log data, spanning 30 months and 500,000 system events for approximately 10,000 staff and 20,000-plus students. The scale of end-user costs was identified in log data, where follow-on exploratory interviews and NASA-RTLX assessments with 20 students exposed issues which log data did not adequately represent. The majority of users reset passwords before expiration. Log analysis indicated that the online self-service system was vastly preferred to the helpdesk, but that there was a 4:1 ratio of failed to successful attempts to recover account access. Log data did not capture the effort in managing passwords, where interviews exposed points of frustration. Participants saw the need for security but voiced a lack of understanding of the numerous restrictions on passwords. Frustrations led to adoption of diverse coping strategies, for example deliberately waiting to reset a password after reaching the post-expiry grace period. We propose ways to improve support, including real-time communication of reasons for failed password creation attempts, and measurement of timing for both successful and failed login attempts.


Date: 7 December 2015
Published: Technology and Practice of Passwords 9th International Conference, Passwords 2015 (Volume 9551 of the book series Lecture Notes in Computer Science)
Publisher: Springer
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Discrete Choice, Social Interaction, and Policy in Encryption Technology Adoption

Tristan Caulfield, Christos Ioannidis and David Pym


We introduce a model for examining the factors that lead to the adoption of new encryption technologies. Building on the work of Brock and Durlauf, the model describes how agents make choices, in the presence of social interaction, between competing technologies given their relative cost, functionality, and usability. We apply the model to examples about the adoption of encryption in communication (email and messaging) and storage technologies (self-encrypting drives) and also consider our model’s predictions for the evolution of technology adoption over time.

Date: 22 February 2016
Published: Financial Cryptography and Data Security 2016, Twentieth International Conference               Published: Springer
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