Who’s holding the bag? Accountability in the criminal justice system

Lack of accountability and transparency are major impediments in efforts to minimize delays, ensure due process of law and reduce backlogged cases in the criminal justice system of . Existing oversight mechanisms to track cases through physical files and archives are prone to tampering and damage. The problem is particularly acute since there is little or no coordination between police, prosecution, and courts. There is no meaningful consolidation of crime and prosecution analytics and a total absence of transparency in the process. The current system makes it difficult to see who’s holding the proverbial bag. _x000D_ This paper presents results from a first of its-kind survey of our criminal justice system in . We highlight the importance and policy implications of our work by presenting empirical data from 750 prosecution vouchers using the results to motivate a case-flow design that integrates and maps the case-management practices of all three institutions involved

Aspect Based Sentiment Analysis for Large Documents with Applications to US Presidential Elections 2016

Aspect based sentiment analysis (ABSA) deals with the fine grained analysis of text to extract entities and aspects and analyze sentiments expressed towards them. Previous work in this area has mostly focused on data of short reviews for products, restaurants and services. We explore ABSA for human entities in the context of large documents like news articles. We create the first-of-its-kind corpus containing multiple entities and aspects from US news articles consisting of approximately 1000 annotated sentences in 300 articles. We develop a novel algorithm to mine entity-aspect pairs from large documents and perform sentiment analysis on them. We demonstrate the application of our algorithm to social and political factors by analyzing the campaign for US presidential elections of 2016. We analyze the frequency and intensity of newspaper coverage in a cross-sectional data from various newspapers and find interesting evidence of catering to a partisan audience and consumer preferences by focusing on selective aspects of presidential candidates in different demographics

Characterizing Key Stakeholders in an Online Black-Hat Marketplace

Over the past few years, many black-hat marketplaces have emerged that facilitate access to reputation manipulation services such as fake Facebook likes, fraudulent search engine optimization (SEO), or bogus Amazon reviews. In order to deploy effective technical and legal countermeasures, it is important to understand how these black-hat marketplaces operate, shedding light on the services they offer, who is selling, who is buying, what are they buying, who is more successful, why are they successful, etc. Toward this goal, in this paper, we present a detailed micro-economic analysis of a popular online black-hat marketplace, namely, SEOClerks.com. As the site provides non-anonymized transaction information, we set to analyze selling and buying behavior of individual users, propose a strategy to identify key users, and study their tactics as compared to other (non-key) users. We find that key users: (1) are mostly located in Asian countries, (2) are focused more on selling black-hat SEO services, (3) tend to list more lower priced services, and (4) sometimes buy services from other sellers and then sell at higher prices. Finally, we discuss the implications of our analysis with respect to devising effective economic and legal intervention strategies against marketplace operators and key users.Comment: 12th IEEE/APWG Symposium on Electronic Crime Research (eCrime 2017

WASEF: Web Acceleration Solutions Evaluation Framework

The World Wide Web has become increasingly complex in recent years. This complexity severely affects users in the developing regions due to slow cellular data connectivity and usage of low-end smartphone devices. Existing solutions to simplify the Web are generally evaluated using several different metrics and settings, which hinders the comparison of these solutions against each other. Hence, it is difficult to select the appropriate solution for a specific context and use case. This paper presents Wasef, a framework that uses a comprehensive set of timing, saving, and quality metrics to evaluate and compare different web complexity solutions in a reproducible manner and under realistic settings. The framework integrates a set of existing state-of-the-art solutions and facilitates the addition of newer solutions down the line. Wasef first creates a cache of web pages by crawling both landing and internal ones. Each page in the cache is then passed through a web complexity solution to generate an optimized version of the page. Finally, each optimized version is evaluated in a consistent manner using a uniform environment and metrics. We demonstrate how the framework can be used to compare and contrast the performance characteristics of different web complexity solutions under realistic conditions. We also show that the accessibility to pages in developing regions can be significantly improved, by evaluating the top 100 global pages in the developed world against the top 100 pages in the lowest 50 developing countries. Results show a significant difference in terms of complexity and a potential benefit for our framework in improving web accessibility in these countries.Comment: 15 pages, 4 figure

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Foresight: Countering Malware through Cooperative Forensics Sharing

<p>With the Internet's rapid growth has come a proportional increase in exposure to attacks, misuse and abuse. Modern viruses and worms are causing damage much more quickly than those created in the past. The fast replication and epidemic nature of the spreads limits the time security experts have to respond and be able to protect and fortify their systems. A pathogen might infect thousands of machines and cascade across the network producing consequences that could overwhelm the internet very quickly. Such attacks have the potential of making a human response to them all but ineffective. While pathogens are becoming much more aggressive, there is also a significant delay between the identification of a new threat and the generation of a cure for it. Worms and viruses have been able to cause significant damage in this 'submission to cure generation' window of vulnerability. Having timely and credible security information is thus becoming critical to network and security management.</p><p>The main hypothesis behind our research is that sharing threat information and forensic evidence among cooperating domains yields important benefits for dealing with modern day pathogens in a timely fashion. The idea is that each host might have an incomplete, approximate or inexact information about a particular threat or attack. We can get a more comprehensive view of the extent and nature of developing threats by observing suspect behavior and combining information gathered from different vantage points. A better understanding of the pathogen allows for effective and timely immunization in order to thwart epidemic cascading of threats. We also propose cooperative policing mechanisms as an effective approach to trace large scale distributed threats like Ddos attacks. Increased cooperation amongst domains helps to mitigate such attacks nearer to the sources so that their effects on the overall network are minimized.</p><p>This thesis leverages experiences and ideas from fields of cryptography, machine learning, security and multi-agent systems to build Foresight: an internet scale threat analysis, indication, early warning and response architecture. Foresight allows cooperating domains to share a global threat view in order to detect zero-day pathogens and isolate them using cooperative policing mechanisms.</p><p>- We describe a novel behavioral signature scheme to extract a generalized footprint for multi-modal threats. Blended or multi-modal threats combine the characteristics of viruses, worms, trojan horses and malicious code to initiate, transmit and spread attacks. By using multiple methods and techniques, blended threats can quickly spread and surpass defenses that address only a single type of malicious activity and hence are much more difficult to defend against. System performance analysis, through trace-based simulations, shows significant benefits for sharing forensics data between cooperating domains.</p><p>- We present Mail-trap, an anomaly based system that catches zero-day email borne pathogens and retards their growth through effective behavior monitoring of mail traffic and active forensics sharing between cooperating domains. Mail-trap relies on Foresight's cooperative policing model to identify and pre-empt email-borne threats. Our results show that behavior monitoring alone can be an effective tool for malware detection. Cooperation amongst domains greatly increases the effectiveness of our approach. Domains are able to pre-empt attacks and respond to malware behavior that they have not seen before. We also analyze various immunization/prevention and containment techniques.</p><p>- We present AMP, a service architecture for countering distributed denial of service attacks using alert sharing and cooperative policing mechanisms. Our simulation architecture enables us to test the system with actual, benign and worm traffic traces, and realistic network topologies. AMP does not require universal deployment and is complementary to other schemes for countering Ddos attacks, however with the use of collaborative policing techniques, the performance of the scheme can be improved greatly.</p><p>- We also present a prototype implementation for Paranoid, a novel global secure file sharing mechanism which can be used to allow secure resource access across administrative domains. We describe the design of a trust-based cooperation scheme to create a global community which is more accountable and hence less vulnerable to attacks and abuse.</p>Dissertatio