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Posts tagged risk assessment
Nonfatal Firearm Injury and Firearm Mortality in High-risk Youths and Young Adults 25 Years After Detention

By Nanzi Zheng, Karen M. Abram,  Leah J. Welty; et alDavid A

Importance  Youths, especially Black and Hispanic males, are disproportionately affected by firearm violence. Yet, no epidemiologic studies have examined the incidence rates of nonfatal firearm injury and firearm mortality in those who may be at greatest risk—youths who have been involved with the juvenile justice system.

Objectives  To examine nonfatal firearm injury and firearm mortality in youths involved with the juvenile justice system and to compare incidence rates of firearm mortality with the general population.

Design, Setting, and Participants  The Northwestern Juvenile Project is a 25-year prospective longitudinal cohort study of 1829 youths after juvenile detention in Chicago, Illinois. Youths were randomly sampled by strata (sex, race and ethnicity, age, and legal status [juvenile or adult court]) at intake from the Cook County Juvenile Temporary Detention Center. Participants were interviewed at baseline (November 1995 to June 1998) and reinterviewed as many as 13 times over 16 years, through February 2015. Official records on mortality were collected through December 2020. Data analysis was conducted from November 2018 to August 2022.

Main Outcomes and Measures  Participants self-reported nonfatal firearm injuries. Firearm deaths were identified from county and state records and collateral reports. Data on firearm deaths in the general population were obtained from the Illinois Department of Public Health. Population counts were obtained from the US census.

Results  The baseline sample of 1829 participants included 1172 (64.1%) males and 657 (35.9%) females; 1005 (54.9%) Black, 524 (28.6%) Hispanic, 296 (16.2%) non-Hispanic White, and 4 (0.2%) from other racial and ethnic groups (mean [SD] age, 14.9 [1.4] years). Sixteen years after detention, more than one-quarter of Black (156 of 575 [27.1%]) and Hispanic (103 of 387 [26.6%]) males had been injured or killed by firearms. Males had 13.6 (95% CI, 8.6-21.6) times the rate of firearm injury or mortality than females. Twenty-five years after the study began, 88 participants (4.8%) had been killed by a firearm. Compared with the Cook County general population, most demographic groups in the sample had significantly higher rates of firearm mortality (eg, rate ratio for males, 2.8; 95% CI, 2.0-3.9; for females: 6.5; 95% CI, 3.0-14.1; for Black males, 2.5; 95% CI, 1.7-3.7; for Hispanic males, 9.6; 95% CI, 6.2-15.0; for non-Hispanic White males, 23.0; 95% CI, 11.7-45.5).

Conclusions and Relevance  This is the first study to examine the incidence of nonfatal firearm injury and firearm mortality in youths who have been involved with the juvenile justice system. Reducing firearm injury and mortality in high-risk youths and young adults requires a multidisciplinary approach involving legal professionals, health care professionals, educators, street outreach workers, and public health researchers.

JAMA Netw Open. 2023;6(4):e238902. doi:10.1001/jamanetworkopen.2023.8902

Multimodal Classification of Onion Services for Proactive Cyber Threat Intelligence Using Explainable Deep Learning

By Harsha Moraliyage; Vidura Sumanasena; Daswin De Silva; Rashmika Nawaratne; Lina Sun; Damminda Alahakoon

The dark web has been confronted with a significant increase in the number and variety of onion services of illegitimate and criminal intent. Anonymity, encryption, and the technical complexity of the Tor network are key challenges in detecting, disabling, and regulating such services. Instead of tracking an operational location, cyber threat intelligence can become more proactive by utilizing recent advances in Artificial Intelligence (AI) to detect and classify onion services based on the content, as well as provide an interpretation of the classification outcome. In this paper, we propose a novel multimodal classification approach based on explainable deep learning that classifies onion services based on the image and text content of each site. A Convolutional Neural Network with Gradient-weighted Class Activation Mapping (Grad-CAM) and a pre-trained word embedding with Bahdanau additive attention are the core capabilities of this approach that classify and contextualize the representative features of an onion service. We demonstrate the superior classification accuracy of this approach as well as the role of explainability in decision-making that collectively enables proactive cyber threat intelligence in the dark web. 

IEEE Access, vol. 10, pp. 56044-56056, 2022,

Evolution of Dark Web Threat Analysis and Detection: A Systematic Approach

By Saiba Nazah; Shamsul Huda; Jemal Abawajy; Mohammad Mehedi Hassan

The Dark Web is one of the most challenging and untraceable mediums adopted by the cyber criminals, terrorists, and state-sponsored spies to fulfil their illicit motives. Cyber-crimes happening inside the Dark Web are like real world crimes. However, the sheer size, unpredictable ecosystem and anonymity provided by the Dark Web services are the essential confrontations to trace the criminals. To discover the potential solutions towards cyber-crimes evaluating the sailing Dark Web crime threats is a crucial step. In this paper, we will appraise the Dark Web by analysing the crimes with their consequences and enforced methods as well as future manoeuvres to lessen the crime threats. We used Systematic Literature Review (SLR) method with the aspiration to provide the direction and aspect of emerging crime threats in the Dark Web for the researchers and specialist in Cyber security field. For this SLR 65 most relevant articles from leading electronic databases were selected for data extraction and synthesis to answer our predefined research questions. The result of this systematic literature review provides (i) comprehensive knowledge on the growing crimes proceeding with Dark Web (ii) assessing the social, economic and ethical impacts of the cyber-crimes happening inside the Dark Web and (iii) analysing the challenges, established techniques and methods to locate the criminals and their drawbacks. Our study reveals that more in depth researches are required to identify criminals in the Dark Web with new prominent way, the crypto markets and Dark Web discussion forums analysis is crucial for forensic investigations, the anonymity provided by Dark Web services can be used as a weapon to catch the criminals and digital evidences should be analysed and processed in a way that follows the law enforcement to make the seizure of the criminals and shutting down the illicit sites in the Dark Web. 

 IEEE Access, vol. 8, pp. 171796-171819, 2020,