Search Results (24)

This article develops an innovative and intelligent method for analysing the criminal community’s influence on risk-forming parameters based on an analysis of regional economic processes. The research motivation was the need to create an intelligent method for quantitative assessment and risk control arising from the interaction between regional economic processes and criminal activity. The method includes a three-level mathematical model in which the economic activity dynamics are described by a modified logistic equation, taking into account the criminal activity’s negative impact and feedback through the integral risk. The criminal activity itself is modelled by a similar logistic equation, taking into account the economic base. The risk parameter accumulates the direct impact and delayed effects through the memory core. To numerically solve the spatio-temporal optimal control problem, a neural network based on the convolutional architecture was developed: two successive convolutional layers (N₁ with 3 × 3 filters and N₂ with 3 × 3 filters) extract local features, after which two 1 × 1 convolutional layers (FC₁ and FC₂) form a three-channel output corresponding to the control actions U_E, U_C, and U_I. The loss function combines the supervised component and the residual terms of the differential equations, which ensures the satisfaction of physical constraints. The computational experiment showed the high accuracy of the model: accuracy is 0.9907, precision is 0.9842, recall is 0.9983, and F1-score is 0.9912, with a minimum residual loss of 0.0093 and superiority over alternative architectures in key metrics (MSE is 0.0124, IoU is 0.74, and Dice is 0.83). Full article

Recreational hunting is a highly regulated activity, in part because it can give rise to a variety of deleterious social, environmental, and economic harms. It provides an interesting area for those interested in community safety because of the way in which both formal (e.g., enforcement officers, proscribed areas and times for hunting, licensing, etc.) and informal (e.g., community awareness and education, conservation) methods of crime prevention are applied. And yet, the criminological literature on effective regulation is not only limited but diverse in terms of scope, types of behavior considered (e.g., poaching, wildlife trading, recreation, etc.), and the context that is considered (e.g., geographical, cultural, etc.). In this paper, we present how a crime prevention and compliance response can be used to understand the nature of the issue and the individual and socio-political processes that result in non-compliance with hunting regulations. We present an overview of the status of recreational hunting in an Australian jurisdiction and locate the regulatory issues that arise within the research literature that explores the various motivations that are known to drive illegal hunting. These are then considered in relation to how community-oriented and non-coercive measures might be employed to improve prevent criminal behavior at the primary, secondary, and tertiary levels. Full article

While the Organization for Economic Cooperation and Development (OECD)’s Anti-Bribery Convention is often considered a success in the fight against global corruption, ensuring its implementation remains challenging. As evidenced by the sustained decline in Transparency International’s ratings, the Korean government does not actively enforce anti-bribery legislation against companies and individuals engaged in business activities abroad. To support this argument, this article reviews the Korean legal apparatus designed to control foreign bribery and examines why the relevant authorities have insufficiently enforced them. Specifically, this paper discusses the Foreign Bribery Prevention Act, its legislative history, how the Korean legislature has failed to implement the OECD Working Group’s recommendations in a timely manner, and the consequences of this failure. Through a case study, this paper compares the practices of Korean law enforcement authorities with those of their counterparts abroad, particularly in the United States. This paper also illustrates how the traditional leniency of Korean prosecutors and judges toward bribe giving, especially by large conglomerates, has affected the enforcement of the relatively new legal apparatus designed to combat bribery of foreign public officials. Furthermore, a cultural leniency toward bribery, coupled with the Korean government’s unwillingness to raise public awareness of foreign bribery crimes and their punishments, poses a significant challenge to combating foreign bribery. Full article

The Dark Web is a subset of the Deep Web, requiring special browsers, the Dark Net refers to encrypted networks, the Deep Web encompasses non-indexed online content, and darknet includes unused IP address networks. The Dark Net has become a hotbed of cybercrime, with individuals and groups using the anonymity and encryption provided by the network to carry out a range of criminal activities. One of the most concerning trends in recent years has been the weaponization of cybercrimes, as criminals use their technical skills to create tools and techniques that can be used to launch attacks against individuals, businesses, and governments. This paper examines the weaponization of cybercrimes on the Dark Net, focusing on the question of detection and application. This paper uses a Systematic Literature Review (SLR) method to appraise the Dark Web, examine the crimes and their consequences and identify future measures to reduce crime threats. Data from 88 relevant articles from 2011 to 2023 were extracted and synthesized, along with the latest data from 2024 to answer research questions, providing comprehensive knowledge on growing crimes; assessing social, economic, and ethical impacts; and analyzing established techniques and methods to locate and apprehend criminals. Full article

The concept of a smart city is based on the extensive multidimensional use of information and communication technologies to create the most favorable living conditions for residents and visitors. It is also important to create favorable conditions for economic activity while respecting the environment. One of the most important dimensions of this concept is security in the broadest sense, particularly that which concerns urban residents. This article addresses this subject by analyzing crime and determining the state of safety in 16 Polish provincial cities between 2013–2022. The measure of this state was chosen to be a set of indicators characterizing a number of registered criminal and economic offenses in the studied cities. On this basis, values of the indices of the dynamics of change for these offenses in individual cities in the analyzed period were determined. In the next stage, the number of offenses was compared to the number of residents of the cities under study and the indices of concentration for total offenses (LQ_T) and for individual types of offenses (LQ_n) were determined. Based on these results, the studied cities were divided into four concentration levels. Afterward, these results were used for a multi-criteria analysis of the safety of studied cities, which was carried out using the TOPSIS method. The calculated values of the safety index (Pi) formed the basis for creating a ranking and specifying security levels of studied cities. The results indicate a wide variation among the cities in terms of safety levels. Gdańsk, Bydgoszcz, Olsztyn and Zielona Góra were found to be the safest cities, while Szczecin was found to be the least safe. The methodology developed and the results obtained show the validity of conducting comparative research in areas relevant to the implementation of the smart cities concept. The knowledge gained can be used to build strategies and conduct policies with regard to improving safety in cities, especially those aspiring to be smart cities. Full article

The purpose of this article is to reflect on the sustainability of informal artisanal mining in the Peruvian Andean area until the year 2022. The research is basic and non-experimental in design and ex post facto in scope. The sample consisted of crime prevention statistics on socio-environmental conflict from guardianship institutions and a television program on mining. Our research procedure focused on gathering secondary information for a documentary review analysis based on past proven and disseminated facts. Informal artisanal mining is strengthened in the Peruvian Andean area due to the following influencing factors: support represented as the social license granted by communal assemblies; the flexibility of governmental management in relaxing compliance related to formalization and preventive laws regarding environmental protection; the resistance to formalization and the 50% increase in socio-environmental conflict; and the 25% increase in production costs related agricultural activities, which promotes the displacement towards mining activities. The environmental sustainability consequences are as follows: limited reconversion of agricultural land-use change in one-third of the communal territories at the headwaters of the basin, which generates the displacement of environmentally friendly economic activity, and a parallel positive action is the impossibility of modification or intervention affecting water surfaces and wetlands due to communal agreements that mining companies must respect during operation. Full article

The European population is aging, which means more people aged sixty-five and over are at risk of financial exploitation. However, there is a lack of consensus regarding whether older persons are at greater risk of fraud than younger counterparts due to physical, economic, and social factors or, rather, whether they are slightly protected from fraud in the digital era due to less frequent online activity. Moreover, little is known about the financial, emotional, psychological, and physical impacts of fraud experiences amongst older generations in digital society. We employ multilevel modelling on a sample of EU citizens (n = 26,735) to analyze these issues. The results show that, holding other factors constant, older adults are more likely to suffer fraud in general, but not fraud via online channels. Identity theft in which the offender attempts to trick the victim by impersonating a reputable organization is found to be particularly relevant for citizens aged sixty-five and above. Older persons are less likely to suffer a financial impact but more likely to experience anger, irritation, embarrassment, and negative impacts on their physical health from fraud in general as well as from online fraud. Many organizations aim to help protect older adults from financial crime and its impacts; thus, the results emphasize the need to understand particular fraud categories suffered by older generations and to design support programs that fully take into account the non-financial impacts of this crime. Full article

With Chinese people’s increasing willingness to participate in night activities, local governments have begun regarding the nighttime economy as an important means to stimulate urban vitality and increase social employment. This study uses changes in urban nighttime light brightness as a measure of environmental factors to examine the social effects of nighttime activities. Based on panel data for 227 prefecture-level cities in China from 2000 to 2013, this study empirically investigates the effect and mechanism of nighttime light brightness on the urban crime rate. Empirical results show that (1) a 1% increase in nighttime light brightness increases criminal arrest rate and prosecution rate by 1.474% and 2.371%, respectively; (2) the effects are larger in developed areas with higher levels of lighting and economic development, or in urban areas (compared with rural areas), and (3) the mechanism test shows that such effects are more pronounced in cities with more nighttime business, confirming the existence of a crime opportunity effect. Full article

Legalization of the proceeds of crime represents a worldwide problem with serious economic and social consequences. Information technologies in conjunction with advanced computer techniques are important tools in the fight against money laundering (ML), financial crime (FC) and terrorism financing (TF). Nowadays, the applied literature on ML/FC/TF uses much more mathematical modelling as a solving strategy to estimate illicit money flows. However, we perceive that there is preference of linear models of economical dependences and sometimes lack of acceptance of nonlinearity of such investigated economic systems. To characterize the risk of legalization of crime proceeds in a certain country, the scientific researchers use the Basel anti-money laundering (AML) index. To better understand how the global indicators (WCI, CPI, EFI, GII, SEDA, DBI, GSCI, HDI, VAT_GAP, GDP per capita) affect the level of risk of ML/TF in the countries of EU, the authors use a unique data set of 24 destination countries of EU over the period 2012–2019. The article deals with two main research goals: to develop a nonlinear model and optimize the ML/TF risk by implementation of nonlinear optimization methods. The authors contribute: (i) providing the cross-country statistical analysis; (ii) creating the new nonlinear mathematical-statistical computational model (MSCM); and (iii) describing the observed dependent variable (Basel AML index). This study deepens previous knowledge in this research field and, in addition to the panel regression analysis, also applies nonlinear regression analysis to model the behavior of the investigated system (with nonlinearity). Our results point out the differences between the estimates of the investigated system behavior when using panel and nonlinear regression analysis. Based on the developed MSC model, the optimization procedure is conducted by applying an interior point method and MATLAB toolboxes and the second goal is achieved: the statement that such values of input variables at which the risk of legalization of income from criminal activity will be minimal. Full article

Detecting malicious activity in advance has become increasingly important for public safety, economic stability, and national security. However, the disparity in living standards incites the minds of certain undesirable members of society to commit crimes, which may disrupt society’s stability and mental calm. Breakthroughs in deep learning (DL) make it feasible to address such challenges and construct a complete intelligent framework that automatically detects such malicious behaviors. Motivated by this, we propose a convolutional neural network (CNN)-based Xception model, i.e., BlockCrime, to detect crimes and improve public safety. Furthermore, we integrate blockchain technology to securely store the detected crime scene locations and alert the nearest law enforcement authorities. Due to the scarcity of the dataset, transfer learning has been preferred, in which a CNN-based Xception model is used. The redesigned Xception architecture is evaluated against various assessment measures, including accuracy, F1 score, precision, and recall, where it outperforms existing CNN architectures in terms of train accuracy, i.e., 96.57%. Full article

Debates in urban social research indicate that one of the most significant problems facing cities of the global south is the dilemma of crime. This study explores the research question: what is the level of influence of economic deprivation and residential mobility weights on criminal activities within vulnerable neighborhoods in urban centres? This research focuses on the urban social structural theory of social disorganization, to investigate how socioeconomic, demographic, and physical characteristics affect criminal behaviour. The study adopted a qualitative research approach that is cross-sectional. With the use of volunteer self-selection sampling techniques, in-depth interviews were conducted with heads of households via a semi-structured interview guide. The data were analyzed using thematic analysis. The study found that sociological factors such as economic deprivation and socioeconomic inequality lead to the gradual integration of delinquency in cities. The findings of this research build on the existing theory of social disorganization. To ensure safety, residents’ economic status must be standardized by supporting the provision of more regulated informal sector opportunities and activities for active engagement in supervising and controlling youth behaviour. Full article

Traditional social network analysis can be generalized to model some networked systems by multilayer structures where the individual nodes develop relationships in multiple layers. A multilayer network is called multiplex if each layer shares at least one node with some other layer. In this paper, we built a unique criminal multiplex network from the pre-trial detention order by the Preliminary Investigation Judge of the Court of Messina (Sicily) issued at the end of the Montagna anti-mafia operation in 2007. Montagna focused on two families who infiltrated several economic activities through a cartel of entrepreneurs close to the Sicilian Mafia. Our network possesses three layers which share 20 nodes. The first captures meetings between suspected criminals, the second records phone calls and the third detects crimes committed by pairs of individuals. We used measures from multilayer network analysis to characterize the actors in the network based on their local edges and their relevance to each specific layer. Then, we used measures of layer similarity to study the relationships between different layers. By studying the actor connectivity and the layer correlation, we demonstrated that a complete picture of the structure and the activities of a criminal organization can be obtained only considering the three layers as a whole multilayer network and not as single-layer networks. Specifically, we showed the usefulness of the multilayer approach by bringing out the importance of actors that does not emerge by studying the three layers separately. Full article

We investigate whether a nexus exists between income inequality and criminal activity in Indonesia. Additionally, we examine socioeconomic variables and potential links with criminal actions (i.e., crime rate, murder, rape, physical abuse, robbery, and fraud). We use the generalized method of moments (GMM) approach, employing data for 34 provinces in Indonesia over the period of 2010–2019. The results indicate that income inequality is associated with higher criminal activity. Overall, lower unemployment, larger investment (foreign and domestic), and higher human development (education and health) can help reduce crime in Indonesia. However, higher income can reduce physical abuse and crime rates, but theft and fraud increase with income growth. Rising unemployment increases rape, abuse, robbery, and fraud. Still, unemployment does not affect murder, suggesting that non-economic factors are dominant in explaining murder and violent crimes. Furthermore, income inequality can increase robbery and fraud, although it has no significant effects on murder, rape, and abuse. Government spending on social assistance and more efficient settlement of criminal acts can lower crime rates. Full article

Perceived safety remains one of the main barriers for children to participate in active commuting to school (ACS). This ecological study examined the associations between the number of police-reported crimes in school neighborhoods and ACS. The percentage of active travel trips was assessed from a teacher tally survey collected from students across 63 elementary schools that were primarily classified as high-poverty (n = 27). Geographic Information System (GIS) was used to create a detailed measure of police-reported crimes during 2018 and neighborhood covariates that occurred within a one-mile Euclidean buffer of the schools. Statistical analyses included linear fixed effects regressions and negative binomial regressions. In fully-adjusted models, reported crime did not exhibit significant associations with ACS. Medium-poverty schools were indirectly associated with ACS when compared to high- and low-poverty schools in all models (p < 0.05). Connectivity and vehicle ownership were also directly associated with ACS (p < 0.05). Low- and medium-poverty schools were indirectly associated with all types of reported crime when compared to high-poverty schools (p < 0.05). Although reported crime was not associated with school-level ACS, differences in ACS and reported crime do exist across school poverty levels, suggesting a need to develop and promote safe and equitable ACS interventions. Full article

Organic foods carry a premium price. They are credence-based foods, i.e., it is difficult for consumers to evaluate the premium aspects of organic food under normal use. In global supply chains, organic food is purchased on institutional trust (certification, logos, standards) rather than on relational trust. Relying on institutional trust makes consumers vulnerable to criminals who intentionally label conventional product as organic or develop sophisticated organized crime networks to defraud businesses and consumers. The aim of this research is to explore cases of organic fraud that are emergent from academic and gray literature searches to identify ways to strengthen future capabilities to counter illicit activities in a globalized food environment. Each case is considered in terms of perpetrator motivations (differentiated as economic, cultural, and behaviorally orientated drivers), the mode of operation (simple or organized), the guardians involved/absent, and the business and supply chain level vulnerabilities the cases highlight. The study finds that institutional trust is particularly vulnerable to fraud. Supply chain guardians need to recognize this vulnerability and implement effective controls to reduce the likelihood of occurrence. However, in some cases considered in the study, the guardians themselves were complicit in the illicit behavior, further increasing consumer vulnerability. Future research needs to consider how additional controls can be implemented, without increasing supply chain friction that will impact on food trade and supply, that can ensure consumers are purchasing what they believe they are paying for. Full article