Jassim Happa

Illuminating the past: state of the art

Virtual reconstruction and representation of historical environments and objects have been of research interest for nearly two decades. Physically based and historically accurate illumination allows archaeologists and historians to authentically visualise a past environment to deduce new knowledge. This report reviews the current state of illuminating cultural heritage sites and objects using computer graphics for scientific, preservation and research purposes. We present the most noteworthy and up-to-date examples of reconstructions employing appropriate illumination models in object and image space, and in the visual perception domain. Finally, we also discuss the difficulties in rendering, documentation, validation and identify probable research challenges for the future. The report is aimed for researchers new to cultural heritage reconstruction who wish to learn about methods to illuminate the past.

Virtual relighting of a Roman statue head from Herculaneum: a case study

High-fidelity computer graphics offer the possibility for archaeologists to put excavated cultural heritage artefacts virtually back into their original setting and illumination conditions. This enables hypotheses about the perception of objects and their environments to be investigated in a safe and controlled manner. This paper presents a case study of the pipeline for the acquisition, modelling, rapid prototyping and virtual relighting of a Roman statue head preserved at Herculaneum in Italy. The statue head was excavated in 2006, after having been buried during the eruption of Mount Vesuvius in AD79.

The virtual reconstruction and daylight illumination of the Panagia Angeloktisti

High-fidelity virtual reconstructions can be used as accurate 3D representations of historical environments. After modelling the site to high precision, physically-based and historically correct light models must be implemented to complete an authentic visualisation. Sunlight has a major visual impact on a site; from directly lit areas to sections in deep shadow. The scene illumination also changes substantially at different times of the day. In this paper we present a virtual reconstruction of the Panagia Angeloktisti; a Byzantine church on Cyprus. We investigate lighting simulations of the church at different times of the day, making use of Image-Based Lighting, using High Dynamic Range Environment Maps of photographs and interpolated spectrophotometer data collected on site. Furthermore, the paper also explores the benefits and disadvantages of employing unbiased rendering methods such as Path Tracing and Metropolis Light Transport for cultural heritage applications.

Validating an Insider Threat Detection System: A Real Scenario Perspective

There exists unequivocal evidence denoting the dire consequences which organisations and governmental institutions face from insider threats. While the in-depth knowledge of the modus operandi that insiders possess provides ground for more sophisticated attacks, organisations are ill-equipped to detect and prevent these from happening. The research community has provided various models and detection systems to address the problem, but the lack of real data due to privacy and ethical issues remains a significant obstacle for validating and designing effective and scalable systems. In this paper, we present the results and our experiences from applying our detection system into a multinational organisation, the approach followed to abide with the ethical and privacy considerations and the lessons learnt on how the validation process refined the system in terms of effectiveness and scalability.

CyberVis: Visualizing the potential impact of cyber attacks on the wider enterprise

A variety of data-mining tools and filtering techniques exist to detect and analyze cyber-attacks by monitoring network traffic. In recent years many of these tools use visualization designed to make traffic patterns and impact of an attack tangible to a security analyst. The visualizations attempt to facilitate understanding elements of an attack, including the location of malicious activity on a network and the consequences for the wider system. The human observer is able to detect patterns from useful visualizations, and so discover new knowledge about existing data sets. Because of human reasoning, such approaches still have an advantage over automated detection, data-mining and analysis. The core challenge still lies in using the appropriate visualization at the right time. It is this lack of situational awareness that our CyberVis framework is designed to address. In this paper we present a novel approach to the visualization of enterprise network attacks and their subsequent potential consequences. We achieve this by combining traditional network diagram icons with Business Process Modeling and Notation (BPMN), a risk-propagation logic that connects the network and business-process and task layer, and a flexible alert input schema able to support intrusion alerts from any third-party sensor. Rather than overwhelming a user with excessive amounts of information, CyberVis abstracts the visuals to show only noteworthy information about attack data and indicates potential impact both across the network and on enterprise tasks. CyberVis is designed with the Human Visual System (HVS) in mind, so severe attacks (or many smaller attacks that make up a large risk) appear more salient than other components in the scene. A Deep-Dive window allows for investigation of data, similar to a database interface. Finally, a Forensic Mode allows movie-style playback of past alerts under user-defined conditions for closer examination.

Cultural Heritage Predictive Rendering

High‐fidelity rendering can be used to investigate Cultural Heritage (CH) sites in a scientifically rigorous manner. However, a high degree of realism in the reconstruction of a CH site can be misleading insofar as it can be seen to imply a high degree of certainty about the displayed scene—which is frequently not the case, especially when investigating the past. So far, little effort has gone into adapting and formulating a Predictive Rendering pipeline for CH research applications. In this paper, we first discuss the goals and the workflow of CH reconstructions in general, as well as those of traditional Predictive Rendering. Based on this, we then propose a research framework for CH research, which we refer to as ‘Cultural Heritage Predictive Rendering’ (CHPR). This is an extension to Predictive Rendering that introduces a temporal component and addresses uncertainty that is important for the scene’s historical interpretation. To demonstrate these concepts, two example case studies are detailed.

A Model to Facilitate Discussions About Cyber Attacks

The evolution of the Internet and digital systems is making it increasingly difficult to understand cyber attacks. Politicians, ethicists, lawyers, business owners and other stakeholders are all affected by them, yet many lack necessary technical background to make correct decisions in dealing with them. Conversely, cyber-security analysts have a better understanding about the technical aspects of cyber attacks, but many do not understand the repercussions of decisions made from their perspective alone. Both contextual (e.g. societal, political, legal, financial, reputational aspects etc.) as well as technical considerations must be taken into account in making decisions that relate to a cyber attack. A plethora of cyber-attack models exist today that aid (to some degree) understanding of attacks. Most of these however focus on delivering insight from a single perspective: technical detail or understanding of human-centric factors. These approaches do not outline how a discussion among expert-domain people of different backgrounds should be conducted to establish a basic situational awareness understanding, from which to make collective decisions. In this chapter, we present our efforts towards establishing such a model to enable a collective approach in discussing cyber attacks. In this paper, we propose a first version, but believe extensions should be made. We also acknowledge that testing and assessment in real environments is necessary.

High dynamic range video for cultural heritage documentation and experimental archaeology

Video recording and photography are frequently used to document Cultural Heritage (CH) objects and sites. High Dynamic Range (HDR) imaging is increasingly being used as it allows a wider range of light to be considered that most current technologies are unable to natively acquire and reproduce. HDR video content however has only recently become possible at desirable, high definition resolution and dynamic range. In this paper we explore the potential use of a 20 f-stop HDR video camera for CH documentation and experimental archaeology purposes. We discuss data acquisition of moving caustics, flames, distant light and in participating media. Comparisons of Low Dynamic Range (LDR) and HDR content are made to illustrate the additional data that this new technology is able to capture, and the benefits this is likely to bring to CH documentation and experimental archaeology.

Assessing a virtual baby feeding training system

Currently a considerable amount of time and resources are spent helping parents overcome issues related to feeding young infants. Designing interactive virtual feeding scenarios is a preventative means to reduce the adaptation process time for newly made parents, but also help new parents improve their approach to feeding their children. In this paper, we present a case study on using and assessing a virtual reality infant feeding application. Our results show that virtual training can increase the efficiency of feeding depending on the different behaviour of the child.

GARMDROID: IoT Potential Security Threats Analysis through the Inference of Android Applications Hardware Features Requirements

Applications and services based on the Internet of Things (IoT) are increasingly vulnerable to disruption from attack or information theft. Developers and researchers attempt to prevent the growth of such disruption models, mitigate and limit their impact. Meeting these challenges requires understanding the characteristics of things and the technologies that empower the IoT since traditional protection mechanisms are not enough. Moreover, as the growth in mobile device market is pushing the deployment of the IoT, tools and mechanisms to evaluate, analyze and detect security threats in these devices are strongly required. In this context, this paper presents a web tool, named GARMDROID, aimed to help IoT software developers and integrators to evaluate IoT security threats based on the visualization of Android application hardware requests. This procedure is based on the static analysis of permissions requested by Android applications.