Marco Angelini

An Enhanced Visualization Process Model for Incremental Visualization

With todays technical possibilities, a stable visualization scenario can no longer be assumed as a matter of course, as underlying data and targeted display setup are much more in flux than in traditional scenarios. Incremental visualization approaches are a means to address this challenge, as they permit the user to interact with, steer, and change the visualization at intermediate time points and not just after it has been completed. In this paper, we put forward a model for incremental visualizations that is based on the established Data State Reference Model, but extends it in ways to also represent partitioned data and visualization operators to facilitate intermediate visualization updates. In combination, partitioned data and operators can be used independently and in combination to strike tailored compromises between output quality, shown data quantity, and responsiveness-i.e., frame rates. We showcase the new expressive power of this model by discussing the opportunities and challenges of incremental visualization in general and its usage in a real world scenario in particular.

VIRTUE: A visual tool for information retrieval performance evaluation and failure analysis

Objective: Information Retrieval (IR) is strongly rooted in experimentation where new and better ways to measure and interpret the behavior of a system are key to scientific advancement. This paper presents an innovative visualization environment: Visual Information Retrieval Tool for Upfront Evaluation (VIRTUE), which eases and makes more effective the experimental evaluation process. Methods: VIRTUE supports and improves performance analysis and failure analysis. Performance analysis: VIRTUE offers interactive visualizations based on well-known IR metrics allowing us to explore system performances and to easily grasp the main problems of the system. Failure analysis: VIRTUE develops visual features and interaction, allowing researchers and developers to easily spot critical regions of a ranking and grasp possible causes of a failure. Results: VIRTUE was validated through a user study involving IR experts. The study reports on (a) the scientific relevance and innovation and (b) the comprehensibility and efficacy of the visualizations. Conclusion: VIRTUE eases the interaction with experimental results, supports users in the evaluation process and reduces the user effort. Practice: VIRTUE will be used by IR analysts to analyze and understand experimental results. Implications: VIRTUE improves the state-of-the-art in the evaluation practice and integrates visualization and IR research fields in an innovative way.

PERCIVAL: proactive and reactive attack and response assessment for cyber incidents using visual analytics

Situational awareness is a key concept in cyber-defence. Its goal is to make the user aware of different and complex aspects of the network he or she is monitoring. This paper proposes PERCIVAL, a novel visual analytics environment that contributes to situational awareness by allowing the user to understand the network security status and to monitor security events that are happening on the system. The proposed visualization allows for comparing the proactive security analysis with the actual attack progress, providing insights on the effectiveness of the mitigation actions the system has triggered against the attack and giving an overview of the possible attacks evolution. Moreover, the same visualization can be fruitfully used in the proactive analysis since it allows for getting details on computed attack paths and evaluating the mitigation actions that have been proactively computed by the system. A preliminary user study provided a positive feedback on the prototype implementation of the system. A video of the system is available at: https://youtu.be/uMpYCJCX95k.

Cumulated relative position: a metric for ranking evaluation

The development of multilingual and multimedia information access systems calls for proper evaluation methodologies to ensure that they meet the expected user requirements and provide the desired effectiveness. IR research offers a strong evaluation methodology and a range of evaluation metrics, such as MAP and (n)DCG. In this paper, we propose a new metric for ranking evaluation, the CRP. We start with the observation that a document of a given degree of relevance may be ranked too early or too late regarding the ideal ranking of documents for a query. Its relative position may be negative, indicating too early ranking, zero indicating correct ranking, or positive, indicating too late ranking. By cumulating these relative rankings we indicate, at each ranked position, the net effect of document displacements, the CRP. We first define the metric formally and then discuss its properties, its relationship to prior metrics, and its visualization. Finally we propose different visualizations of CRP by exploiting a test collection to demonstrate its behavior.

A Visual Analytics Approach for What-If Analysis of Information Retrieval Systems

We present the innovative visual analytics approach of the VATE system, which eases and makes more effective the experimental evaluation process by introducing the what-if analysis. The what-if analysis is aimed at estimating the possible effects of a modification to an IR system to select the most promising fixes before implementing them, thus saving a considerable amount of effort. VATE builds on an analytical framework which models the behavior of the systems in order to make estimations, and integrates this analytical framework into a visual part which, via proper interaction and animations, receives input and provides feedback to the user.

Visual Cyber Situational Awareness for Critical Infrastructures

The increasing number of security accidents, due to failures or cyber attacks, that critical infrastructures/smart grids are experimenting is pushing researchers to investigate on the different issues associated with such a problem. Among them, an increasing attention has been devoted to the development of monitoring systems that exploit geographical data about the network under control. This papers focuses on situational awareness and describes a Visual Analytics solution for monitoring and put in tight relation data from network level (computers, routers, etc.) with organizations mission. The goal of the proposed solution is to make security officers aware of both the actual network endangerment level and the impact it actually has on the infrastructure mission, making clear the relationships and the responsibilities that exist between the network level and the business level. The solution proposed is then instantiated on ACEA infrastructure, a company that provides power and water purification services to cities in central Italy (millions of end users).

Cyber situational awareness: from geographical alerts to high-level management

This paper focuses on cyber situational awareness and describes a visual analytics solution for monitoring and putting in tight relation data from network level with the organization business. The goal of the proposed solution is to make different security profiles (network security officer, network security manager, and financial security manager) aware of the actual network state (e.g., risk and attack progress) and the impact it actually has on the business tasks, making clear the relationships that exist between the network level and the business level. The proposed solution is instantiated on the ACEA infrastructure, the Italian company that provides power and water purification services to cities in central Italy (millions of end users).Graphical Abstract

CRUMBS: A cyber security framework browser

In the last years, several standards and frameworks have been developed to help organizations to increase the security of their Information Technology (IT) systems. In order to deal with the continuous evolution of the cyberattacks complexity, such solutions have to cope with an overwhelming set of concepts, and are perceived as complex and hard to implement. This paper presents a visual analytics solution targeted at dealing with the Italian Adaptation of the Cyber Security Framework (IACSF), derived by the National Institute of Standards and Technology (NIST) proposal, adaptation that, in its full complexity, presents the security managers with hundreds of scattered concepts, like functions, categories, subcategories, priorities, maturity levels, current and target profiles, and controls, making its adoption a complex activity. The system has been designed together with the security experts of one of the largest Italian public organization and has the goal of providing a continuous overview of the adoption process, providing a prioritizing view that helps in effectively planning the required activities. A prototype is available at: http://awareserver.dis.uniroma1.it:11768/crumbs/

A Visual Interactive Environment for Making Sense of Experimental Data

We present the Visual Information Retrieval Tool for Upfront Evaluation VIRTUE which is an interactive and visual system supporting two relevant phases of the experimental evaluation process: performance analysis and failure analysis.

Information retrieval failure analysis: Visual analytics as a support for interactive “what-if” investigation

This poster provides an analytical model for examining performances of IR systems, based on the discounted cumulative gain family of metrics, and visualization for interacting and exploring the performances of the system under examination. Moreover, we propose machine learning approach to learn the ranking model of the examined system in order to be able to conduct a “what-if” analysis and visually explore what can happen if you adopt a given solution before having to actually implement it.