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Cyber threats affect all kinds of organisations. Risk analysis is an essential methodology for cybersecurity as it allows organisations to deal with the cyber threats potentially affecting them, prioritise the defence of their assets and…
Automated techniques for rigorous floating-point round-off error analysis are important in areas including formal verification of correctness and precision tuning. Existing tools and techniques, while providing tight bounds, fail to analyze…
Modern ERP systems contain flexible report generators but the tendency exists for users to export data to spreadsheets for manipulation, reporting and decision making. A purported reason for this is that some users are more familiar with…
Over the last century, risk scores have been the most popular form of predictive model used in healthcare and criminal justice. Risk scores are sparse linear models with integer coefficients; often these models can be memorized or placed on…
CubeSats have democratised access to space for universities, start-ups and emerging space nations, but the same design decisions that reduce cost and complexity introduce distinctive cybersecurity risks. Existing risk assessment…
Spreadsheet collaboration provides valuable opportunities for learning and expertise sharing between colleagues. Sharing expertise is essential for the retention of important technical skillsets within organisations, but previous studies…
Organizations routinely make strategic budget allocations under operational constraints, but often lack a principled way to assess whether realized allocations were close to the best feasible choices in hindsight. We present a retrospective…
Whilst not all spreadsheet defects are structural in nature, poor layout choices can compromise spreadsheet quality. These defects may be avoided at the development stage by some simple mistake prevention and detection devices. Poka-Yoke…
According to different typologies of activity and priority, risks can assume diverse meanings and it can be assessed in different ways. In general risk is measured in terms of a probability combination of an event (frequency) and its…
Taiwan's auditors have suffered from processing excessive audit data, including drawing audit evidence. This study advances sampling techniques by integrating machine learning with sampling. This machine learning integration helps avoid…
We intend to demonstrate the innate problems with existing spreadsheet products and to show how to tackle these issues using a new type of spreadsheet program called Resolver. It addresses the issues head-on and thereby moves the 1980's…
Students learning how to apply spreadsheets to accounting problems are not always well served by the built-in financial functions. Problems can arise because of differences between UK and US practice, through anomalies in the functions…
It is often the case that risk assessment and prognostics are viewed as related but separate tasks. This chapter describes a risk-based approach to prognostics that seeks to provide a tighter coupling between risk assessment and fault…
Cyber risk assessment is a fundamental activity for enhancing the protection of an organization, identifying and evaluating the exposure to cyber threats. Currently, this activity is carried out mainly manually and the identification and…
Existing approaches to bias evaluation in large language models (LLMs) trade ecological validity for statistical control, relying either on artificial prompts that poorly reflect real-world use or on naturalistic tasks that lack scale and…
Scientists increasingly recognize the importance of providing rich, standards-adherent metadata to describe their experimental results. Despite the availability of sophisticated tools to assist in the process of data annotation,…
Several approaches have recently used automated techniques to generate architecture design alternatives by means of optimization techniques. These approaches aim at improving an initial architecture with respect to quality aspects, such as…
Previous works on the CERT insider threat detection case have neglected graph and text features despite their relevance to describe user behavior. Additionally, existing systems heavily rely on feature engineering and audit data aggregation…
To safely deploy deep learning-based computer vision models for computer-aided detection and diagnosis, we must ensure that they are robust and reliable. Towards that goal, algorithmic auditing has received substantial attention. To guide…
Spreadsheets are widely used in various fields to do large numerical analysis. While several companies have relied on spreadsheets for decades, data scientists are going in the direction of using scientific programming languages such as…