Adaptive spike detection for resilient data stream mining

Automated adversarial detection systems can fail when under attack by adversaries. As part of a resilient data stream mining system to reduce the possibility of such failure, adaptive spike detection is attribute ranking and selection without class-labels. The first part of adaptive spike detection requires weighing all attributes for spiky-ness to rank them. The second part involves filtering some attributes with extreme weights to choose the best ones for computing each example’s suspicion score. Within an identity crime detection domain, adaptive spike detection is validated on a few million real credit applications with adversarial activity. The results are F-measure curves on eleven experiments and relative weights discussion on the best experiment. The results reinforce adaptive spike detection’s effectiveness for class-label-free attribute ranking and selection.

Caracterização de crime ambiental de poluição por meio de abordagem multiparamétrica e incorporando incerteza de amostragem

Tese (Doutorado em Tecnologia Nuclear)

Adaptive unsupervised learning of human actions

Automatic detection of suspicious activities in CCTV camera feeds is crucial to the success of video surveillance systems. Such a capability can help transform the dumb CCTV cameras into smart surveillance tools for fighting crime and terror. Learning and classification of basic human actions is a precursor to detecting suspicious activities. Most of the current approaches rely on a non-realistic assumption that a complete dataset of normal human actions is available. This paper presents a different approach to deal with the problem of understanding human actions in video when no prior information is available. This is achieved by working with an incomplete dataset of basic actions which are continuously updated. Initially, all video segments are represented by Bags-Of-Words (BOW) method using only Term Frequency-Inverse Document Frequency (TF-IDF) features. Then, a data-stream clustering algorithm is applied for updating the system's knowledge from the incoming video feeds. Finally, all the actions are classified into different sets. Experiments and comparisons are conducted on the well known Weizmann and KTH datasets to show the efficacy of the proposed approach.

The Felon and the Angel Copier: Criminal Identity and the Promise of Photography in Victorian England and Wales

Ireland Richard, 'The Felon and the Angel Copier: Criminal Identity and the Promise of Photography in Victorian England and Wales', In: Policing and War in Europe, Criminal Justice History, (Westport, CT, Greenwood Press), volume 16, pp.53-86, 2002 RAE2008

Exploring the Influence of Reporting Delay on Criminal Justice Outcomes: Comparing Child and Adult Reporters of Childhood Sexual Abuse

Delay between disclosure and reporting child sexual abuse is common and has significant implications for the prosecution of such offenses. While we might expect the relationship to be a linear one with longer delay reducing the likelihood of prosecution, the present study confirms a more complex interaction. Utilizing data from 2,079 police records in Northern Ireland, the study investigated the impact of reporting delay on pretrial criminal justice outcomes for child and adult reporters of child sexual abuse. While teenagers were found to be the group most disadvantaged by reporting delay, increased delay actually appeared advantageous for some groups, notably adult females reporting offenses that occurred when they were 0 to 6 years old. Conversely, adult males reporting child sexual abuse did not appear to benefit from increased delay, suggesting both an adult and gender bias within decision-making processes. The implications for future research are discussed. 

Territorialización de la inseguridad ciudadana en Bogotá: La Calle del Bronx

La tesis devela la connotación sistemática y multicausal de lo que a través de la investigación se denomina como "Procesos de Territorialización de la Inseguridad Ciudadana". Mediante un estudio de caso, se pone en evidencia la apropiación y captura sostenida en el tiempo de fenómenos como la inseguridad y la criminalidad, sobre determinadas zonas o barrios urbanos que por sus características socioeconómicas, políticas, geográficas, culturales, laborales y de mercado de quienes los habitan o frecuentan, se consideran como sectores "críticos y/o vulnerables".

People counting with re-identification using depth cameras

[EN]Low cost real-time depth cameras offer new sensors for a wide field of applications apart from the gaming world. Other active research scenarios as for example surveillance, can take ad- vantage of the capabilities offered by this kind of sensors that integrate depth and visual information. In this paper, we present a system that operates in a novel application context for these devices, in troublesome scenarios where illumination conditions can suffer sudden changes. We focus on the people counting problem with re-identification and trajectory analysis.

Adaptive communal detection in search of adversarial identity crime

This paper is on adaptive real-time searching of credit application data streams for identity crime with many search parameters. Specifically, we concentrated on handling our domain-specific adversarial activity problem with the adaptive Communal Analysis Suspicion Scoring (CASS) algorithm. CASS's main novel theoretical contribution is in the formulation of State-of- Alert (SoA) which sets the condition of reduced, same, or heightened watchfulness; and Parameter-of-Change (PoC) which improves detection ability with pre-defined parameter values for each SoA. With pre-configured SoA policy and PoC strategy, CASS determines when, what, and how much to adapt its search parameters to ongoing adversarial activity. The above approach is validated with three sets of experiments, where each experiment is conducted on several million real credit applications and measured with three appropriate performance metrics. Significant improvements are achieved over previous work, with the discovery of some practical insights of adaptivity into our domain.