Exploring the potential of the internet of things at a heritage site through co-design practice

Our multidisciplinary team faced the challenge of creating an engaging visiting experience for Chesters museum that hosts John Clayton’s collection of Roman antiquities found along Hadrian’s Wall. The museum, created in 1896, is still in its original form and has a large collection of altars and religious sculptures displayed in a continuous sequence on several rows, as was the fashion in Victorian and Edwardian times. This layout was overwhelming for most visitors who only spent very little time in the museum. In an iterative co-design process we generated multiple concepts and prototyped the most promising: the aim was to make the visitors slow down and look around in a meaningful way. We assessed three prototypes in place finding physical impediments and management issues for two. The design and implementation then focused on a single concept that explores the relationship between the Romans and their gods. The final interactive installation uses the Internet of Things technology to offer a personalised experience that engages visitors at a physical level while simultaneously provoking them to explore and take action. This paper contributes to a better understanding of how design practice can create a novel interactive visiting experience centered on meaning-making rather than on the latest technology

Embedding Fuzzy Rules with YARA Rules for Performance Optimisation of Malware Analysis

YARA rules utilises string or pattern matching to perform malware analysis and is one of the most effective methods in use today. However, its effectiveness is dependent on the quality and quantity of YARA rules employed in the analysis. This can be managed through the rule optimisation process, although, this may not necessarily guarantee effective utilisation of YARA rules and its generated findings during its execution phase, as the main focus of YARA rules is in determining whether to trigger a rule or not, for a suspect sample after examining its rule condition. YARA rule conditions are Boolean expressions, mostly focused on the binary outcome of the malware analysis, which may limit the optimised use of YARA rules and its findings despite generating significant information during the execution phase. Therefore, this paper proposes embedding fuzzy rules with YARA rules to optimise its performance during the execution phase. Fuzzy rules can manage imprecise and incomplete data and encompass a broad range of conditions, which may not be possible in Boolean logic. This embedding may be more advantageous when the YARA rules become more complex, resulting in multiple complex conditions, which may not be processed efficiently utilising Boolean expressions alone, thus compromising effective decision-making. This proposed embedded approach is applied on a collected malware corpus and is tested against the standard and enhanced YARA rules to demonstrate its success