A Visual Analytics Approach for User Behaviour Understanding through Action Sequence Analysis

Analysis of action sequence data provides new opportunities to understand and model user behaviour. Such data are often in the form of timestamped and labelled series of atomic user actions. Cyber security is one of the domains that show the value of the analysis of these data. Elaborate and specialised models of user-behaviour are desired for effective decision making during investigation of cyber threats. However, due to their complex nature, activity sequences are not yet well-exploited within cyber security systems. In this paper, we describe the initial phases of a visual analytics approach that aims to enable a rich understanding of user behaviour through the analysis of user activity sequences. First, we discuss a motivating case study and discuss a number of high level requirements as derived from a series of workshops within an ongoing research project. We then present the components of a visual analytics approach that constitutes a novel combination of ``action space'' analysis, pattern mining, and the interactive visual analysis of multiple sequences to take the initial steps towards a comprehensive understanding of user behaviour

Understanding User Behaviour through Action Sequences: from the Usual to the Unusual

Action sequences, where atomic user actions are represented in a labelled, timestamped form, are becoming a fundamental data asset in the inspection and monitoring of user behaviour in digital systems. Although the analysis of such sequences is highly critical to the investigation of activities in cyber security applications, existing solutions fail to provide a comprehensive understanding due to the complex semantic and temporal characteristics of these data. This paper presents a visual analytics approach that aims to facilitate a user-involved, multi-faceted decision making process during the identification and the investigation of “unusual” action sequences. We first report the results of the task analysis and domain characterisation process. Then we describe the components of our multi-level analysis approach that comprises of constraint-based sequential pattern mining and semantic distance based clustering, and multi-scalar visualisations of users and their sequences. Finally, we demonstrate the applicability of our approach through a case study that involves tasks requiring effective decision-making by a group of domain experts. Although our solution here is tightly informed by a user-centred, domain-focused design process, we present findings and techniques that are transferable to other applications where the analysis of such sequences is of interest

VASABI: Hierarchical User Profiles for Interactive Visual User Behaviour Analytics

User behaviour analytics (UBA) systems offer sophisticated models that capture users’ behaviour over time with an aim to identify fraudulent activities that do not match their profiles. Making decisions based on such systems; however, requires an in-depth understanding of user behaviour both at an individual and at a group level where a group can consist of users with similar roles. We present a visual analytics approach to help analysts gain a comprehensive, multifaceted understanding of user behaviour at multiple levels. We take a user-centred approach to design a visual analytics framework supporting the analysis of collections of users and the numerous sessions of activities they conduct within digital applications. The framework is centred around the concept of hierarchical user profiles, where the profiles are built based on features derived from sessions they perform and visualised with task-informed designs to facilitate interactive exploration and investigation. We also present techniques to extract user tasks that summarise the behaviour and to cluster users according to these tasks for providing hierarchical overviews of groups of users along with individual users and the sessions they conduct. We externalise a series of analysis goals and tasks, and evaluate our methods through a number of use cases that demonstrate how these tasks are addressed. We observe that with the aid of interactive visual hierarchical user profiles, analysts were able to conduct exploratory and investigative analysis effectively, and able to understand the characteristics of user behaviour to make informed decisions whilst evaluating suspicious users and activities

LDA Ensembles for Interactive Exploration and Categorization of Behaviors

We define behavior as a set of actions performed by some agent during a period of time. We consider the problem of analyzing a large collection of behaviors by multiple agents, more specifically, identifying typical behaviors as well as spotting behavior anomalies. We propose an approach leveraging topic modeling techniques -- LDA (Latent Dirichlet Allocation) Ensembles -- for representing categories of typical behaviors by topics obtained through applying topic modeling to a behavior collection. When such methods are applied to text documents, the goodness of the extracted topics is usually judged based on the semantic relatedness of the terms pertinent to the topics. This criterion, however, may not be applicable to topics extracted from non-textual data, such as action sets, since relationships between actions may not be obvious. We have developed a suite of visual and interactive techniques supporting the construction of an appropriate combination of topics based on other criteria, such as distinctiveness and coverage of the behavior set. Our case studies in the operation behaviors in the security management system and visiting behaviors in an amusement park and the expert evaluation of the first case study demonstrate the effectiveness of our approach

Tracing Noble Gas Radionuclides in the Environment

Trace analysis of radionuclides is an essential and versatile tool in modern science and technology. Due to their ideal geophysical and geochemical properties, long-lived noble gas radionuclides, in particular, 39Ar (t1/2 = 269 yr), 81Kr (t1/2 = 2.3x10^5 yr) and 85Kr (t1/2 = 10.8 yr), have long been recognized to have a wide range of important applications in Earth sciences. In recent years, significant progress has been made in the development of practical analytical methods, and has led to applications of these isotopes in the hydrosphere (tracing the flow of groundwater and ocean water). In this article, we introduce the applications of these isotopes and review three leading analytical methods: Low-Level Counting (LLC), Accelerator Mass Spectrometry (AMS) and Atom Trap Trace Analysis (ATTA)

Phase I/II Trial of Liver-derived Mesenchymal Stem Cells in Pediatric Liver-based Metabolic Disorders: A Prospective, Open Label, Multicenter, Partially Randomized, Safety Study of One Cycle of Heterologous Human Adult Liver-derived Progenitor Cells (HepaStem) in Urea Cycle Disorders and Crigler-Najjar Syndrome Patients

Background. Regenerative medicine using stem cell technology is an emerging field that is currently tested for inborn and acquired liver diseases. Objective. This phase I/II prospective, open label, multicenter, randomized trial aimed primarily at evaluating the safety of Heterologous Human Adult Liver–derived Progenitor Cells (HepaStem) in pediatric patients with urea cycle disorders (UCDs) or Crigler-Najjar (CN) syndrome 6 months posttransplantation. The secondary objective included the assessment of safety up to 12 months postinfusion and of preliminary efficacy. Methods. Fourteen patients with UCDs and 6 with CN syndrome were divided into 3 cohorts by body weight and intraportally infused with 3 doses of HepaStem. Clinical status, portal vein hemodynamics, morphology of the liver, de novo detection of circulating anti–human leukocyte antigen antibodies, and clinically significant adverse events (AEs) and serious adverse events to infusion were evaluated by using an intent-to-treat analysis. Results. The overall safety of HepaStem was confirmed. For the entire study period, patient-month incidence rate was 1.76 for the AEs and 0.21 for the serious adverse events, of which 38% occurred within 1 month postinfusion. There was a trend of higher events in UCD as compared with CN patients. Segmental left portal vein thrombosis occurred in 1 patient and intraluminal local transient thrombus in a second patient. The other AEs were in line with expectations for catheter placement, cell infusion, concomitant medications, age, and underlying diseases. Conclusions. This study led to European clinical trial authorization for a phase II study in a homogeneous patient cohort, with repeated infusions and intermediate doses

GABA Receptors and the Pharmacology of Sleep

Current GABAergic sleep-promoting medications were developed pragmatically, without making use of the immense diversity of GABAA receptors. Pharmacogenetic experiments are leading to an understanding of the circuit mechanisms in the hypothalamus by which zolpidem and similar compounds induce sleep at α2βγ2-type GABAA receptors. Drugs acting at more selective receptor types, for example, at receptors containing the α2 and/or α3 subunits expressed in hypothalamic and brain stem areas, could in principle be useful as hypnotics/anxiolytics. A highly promising sleep-promoting drug, gaboxadol, which activates αβδ-type receptors failed in clinical trials. Thus, for the time being, drugs such as zolpidem, which work as positive allosteric modulators at GABAA receptors, continue to be some of the most effective compounds to treat primary insomnia