Examining personal, organizational and technological factors on job performance: A study on law enforcement officers.

Narcotics are substances that calm the nerves, relieve pain, induce drowsiness or stimulation, cause unconsciousness, and can lead to addiction. The misuse of narcotics is a global problem that threatens the future of nations, particularly through transnational smuggling by organised crime networks. This study examines the role of the Directorate General of Customs and Excise (DGCE) in combating narcotics smuggling and explores strategies to optimise its law enforcement functions against increasingly sophisticated international operations. Using a normative juridical method based on legislative analysis, with data collected through literature studies of scientific papers and journals, the research finds that DGCE plays a strategic role in protecting society from the circulation of dangerous goods, including narcotics. As the frontline authority at national borders, DGCE monitors cross-border goods flows and prevents the entry of illegal substances. However, combating narcotics is not solely the responsibility of customs. Effective enforcement requires enhanced inter-agency and international cooperation. DGCE collaborates with the National Narcotics Agency, the police, the Indonesian Navy, and the Food and Drug Supervisory Agency (BPOM) through joint operations and interdiction task forces. Through such synergy, DGCE strengthens its role as a primary gatekeeper against transnational narcotics crimes.

This study discusses the legal gap in determining criminal liability for Transnational Organized Crime (TOC) networks that use false concealment methods in smuggling liquid methamphetamine at Yogyakarta International Airport. The main problem lies in the limitations of Indonesian criminal law in reaching criminal liability not only for the direct perpetrators, but also for the entire syndicate structure, such as coordinators, facilitators, and financiers, because the method of concealment makes it difficult to prove. This study uses a normative juridical approach by analyzing the integration between the Narcotics Law (Law No. 35 of 2009) as lex specialis and the Criminal Code, specifically Articles 55 and 56, in determining collective criminal liability. The results show that the method of disguising narcotics in the form of consumer goods reveals normative and structural weaknesses in the current criminal liability system. As a scientific contribution, this study proposes an expanded model of criminal liability that integrates narcotics law, the doctrine of participation, and money laundering provisions to cover the entire TOC network. This study concludes that strengthening criminal liability for transnational narcotics crimes requires updating legal doctrines, strengthening international cooperation, and implementing additional legal provisionsto make law enforcement more effective and provide a deterrent effect.

Detecting multi-layered financial crime networks remains a major challenge in anti-money laundering (AML) due to high false positives, evolving adversarial behaviors, limited relational modeling, and stringent regulatory requirements for transparency and auditability. This study presents a novel, integrated Graph Neural Network–Explainable Artificial Intelligence (GNN-XAI) framework optimized for multi-layered AML detection, explicitly addressing accuracy, scalability, privacy preservation, and regulatory compliance. A heterogeneous Graph Attention Network architecture models transaction flows, entity relationships, device linkages, and temporal interactions within complex financial ecosystems. Over 400 engineered features capture velocity patterns, behavioral deviations, network centrality, and geopolitical risk. The framework was validated on benchmark datasets (IEEE-CIS Fraud Detection, Kaggle Credit Card Fraud, Elliptic Bitcoin) and large-scale synthetic transaction graphs. Results demonstrate robust performance, achieving an AUC-ROC of 0.874, precision of 89.3%, recall of 82.1%, and F1-score of 0.857, outperforming XGBoost and conventional GCN baselines by 5–6%. Relational features accounted for over 51% of predictive contribution. SHAP, LIME, and attention-based explanations enabled regulator-ready interpretability, supporting compliance, auditability, and supervisory review. Scalability experiments confirmed stable performance on networks exceeding 5.6 million transactions with sub-millisecond inference latency, while federated learning and differential privacy ensured viable privacy-utility trade-offs. The findings demonstrate that GNN-XAI architectures provide a practical, regulation-aligned pathway for next-generation AML systems.

After-Market Compartments: The hidden broker of organized crime networks in British Columbia

In the shadow of silence: Modelling missing data in the dark networks of crime and terrorists

While the Circular Economy (CE) is widely regarded as a strategy for sustainability, little research has examined how its principles are distorted and exploited by criminal ecosystems. This study investigates the deviant appropriation of CE practices—such as refurbishing, recycling, and reselling—by organized crime networks, conceptualized as the “malignant circle” of the CE. Using a qualitative approach, the paper synthesizes empirical evidence from global case reports and the literature to analyze how illicit actors distort CE flows to profit and fund criminal activities. The findings reveal six overarching criminal practices that subvert CE principles, including e-fencing, illegal waste dumping, and counterfeit upcycling, perpetuating criminal ecosystems while undermining sustainability goals. A conceptual model and structured typology are introduced to illustrate the feedback loops that sustain this malignant system. The study contributes to the CE and criminology literature by highlighting policy gaps and discussing solutions to disrupt illicit circular flows, with implications for traceability, digital governance, and consumer education.

Abstract This study examines how social embeddedness and multiplex relationships shape criminal collaboration within organized crime networks. Drawing on data from three major investigations into the ‘Ndrangheta, we analyze how kinship, clan affiliation, leadership, and prior interactions influence participation in meetings and phone calls. Using relational hyperevent models, we assess the dynamic and multiplex nature of these networks across time and investigations. Results show that kinship, leadership, and shared clan affiliation consistently increase the likelihood of interaction, with stronger effects for face‐to‐face meetings. Prior joint interactions also predict future collaboration, especially when the mode remains consistent. We find contrasting patterns of closure: meetings resist triadic closure, reinforcing exclusivity and hierarchy, whereas phone calls promote connectivity by bridging structural holes. By modeling multiple relational mechanisms simultaneously and across different networks, this study contributes to research on criminal embeddedness and the structural organization of illicit collaboration.

Financial crime detection faces unparalleled challenges as criminal networks exploit digital payment channels, cryptocurrency platforms, and cross-border transaction systems outside traditional monitoring frameworks. In this respect, AFCI introduces a novel framework for federated machine learning, regulatory reasoning engines, and real-time risk propagation analytics to build unified global privacy-preserving anti-crime intelligence ecosystems. The framework lets organizations train collaborative models with decentralized institutions, safely aggregating information from multiple parties without sharing sensitive transaction data by means of secure aggregation protocols and differential privacy mechanisms. Large language models coupled with knowledge graphs automate the processes of regulatory interpretation and rule generation, and graph neural networks enable the detection of coordinated criminal activities on a large scale in transaction networks through temporal message passing mechanisms. Reinforcement learning agents continuously optimize detection policies to balance the identification of genuine threats against the goal of minimizing false alarms. The framework bridged critical gaps in cross-border compliance coordination and empowered institutions to develop shared detection capabilities in support of data localization requirements and an array of diverse regulatory frameworks. Long-term security of privacy-preserving federated computation would be guaranteed with post-quantum cryptography. This convergence of advanced technologies allows next-generation financial crime prevention systems to remain effective against evolving criminal methodologies while preserving fundamental privacy rights.

Our understanding of pharmacists as Nazi perpetrators remains rather vague. Considerable research has examined the Nazification and transformation of German pharmaceutical research, practice, and education between 1933 and 1945. The names of several SS pharmacists who served in concentration camps are also known. Yet little is known about their actual practices and their concrete involvement in medical crimes. What tasks did pharmacists perform in the concentration camps, what scope of action did they have, and in which perpetrator networks were they embedded? This article addresses these questions through the biographical example of Herbert Siggelkow (1906-1976), chief pharmacist of the concentration camps. Drawing on extensive archival records, we reconstruct the biography of Siggelkow, who, already as a grammar school student, had joined a völkisch-nationalist paramilitary association and, in 1932, the Nazi Party and the SS. We then analyze his responsibilities, individual scope of action, and involvement in medical crimes across the various settings of his service in the Waffen-SS and within the concentration camp system. As camp pharmacist at Dachau and Sachsenhausen and as chief pharmacist of the concentration camp medical service, Siggelkow shared responsibility for both the individual and the structural medical neglect of inmates. In fact, he was among the very few who had precise knowledge of the extent of medical shortages throughout the entire camp system. Through the distribution of poisons, he facilitated the systematic killing of sick and incapacitated prisoners by injection, while the provision of drugs and equipment for the camp research stations sustained the criminal practice of coerced human experimentation. We demonstrate that, over the course of his service, Siggelkow operated within markedly varying but generally limited scopes of action. While he had initially used his individual latitude clearly to the detriment of prisoners, his demeanor shifted markedly as hopes of a German victory waned. However, as part of a multi-professional perpetrator network, he bore substantial co-responsibility for atrocious medical crimes committed in the camps.

Abstract The rapid evolution of AI-enabled future crimes, including synthetic identity fraud, deepfake scams, and cryptocurrency-based money laundering, has exposed critical gaps in traditional regulatory frameworks. Yet, few studies have examined how multi-layered responsive policing strategies can protect potential victims of future crimes in China and Southeast Asia, where digital payment adoption is surging. This article fills this gap by empirically investigating AI-empowered responsive regulation, drawing on 30 in-depth interviews with frontline police officers and 12 senior digital experts from major digital platforms in China and Southeast Asia. Our study introduces a novel AI-empowered “regulatory pyramid” framework, synthesizing insights from law enforcement and private-sector cybersecurity innovations to combat modular, adaptive, and decentralized crime networks. The AI-empowered regulatory pyramid is a set of tech-driven responsive policing at three layers: (1) AI-empowered capacity building for protecting potential victims, (2) restorative community policing disrupting cyber money mule networks, and (3) incapacitative policing targeting cybercrime syndicates. Empirical evidence indicates all three levels of responsive policing have been observed and are available in China, but cyberfraud policing practices in Southeast Asia often focus on capacity building due to a lack of state capacity and resources, which explains why the strict policing enforcement in China led to the relocation of cyberfraud criminals from China to Southeast Asia and the rise of transnational future crimes. We also found that while escalating enforcement via AI-empowered strategies yields short-term deterrence in China, long-term resilience depends on poverty-alleviation-oriented capacity-building and cross-border police cooperation against transnational future crimes.

This study analyzes this relationship in the context of international law and security dynamics by focusing on the PYD/YPG, which is supported politically, militarily, and economically by the West under the US umbrella. For this purpose, relevant literature, field data, and intelligence reports available from open sources were utilized. The findings show that Türkiye and EU countries use the organization in line with regional interests. The organization, which has adopted an asymmetric warfare strategy, is waging proxy wars in Syria with the support of the West and acting on its behalf. On the other hand, it easily organizes and continues its activities in the West, especially in Europe. These activities cover a wide range of areas such as lobbying, finance, propaganda, and the recruitment of militants. The Western media, on the other hand, positions the organization as a fighter for freedom and democracy on the grounds of the fight against DAESH and mediates the formation of public opinion in its favor. However, the organization's terrorist acts targeting NATO member Türkiye, its relationship with the PKK, and the mass migrations it causes are ignored. It is understood that the West tries to legitimize the organization to justify its support, which erodes international law and order. While the support provided to the organization deepens regional instability and conflicts, the regional and global security architecture is negatively affected by mass migration, foreign fighters, and cooperation with organized crime networks. Moreover, this relationship causes strategic incompatibilities and trust crises within the Western and NATO alliance, damaging alliance relations and making collaboration difficult.

Globalization, while fostering economic interdependence, technological advancement, and mobility across borders, has also facilitated the proliferation of transborder crimes in West Africa. This study examines the nexus between globalization and the surge of cross-border criminal activities in the region, including drug trafficking, human trafficking, arms smuggling, money laundering, cybercrime, and irregular migration. Drawing on empirical data from regional security reports, UNODC assessments, and ECOWAS monitoring frameworks, the paper analyzes how porous borders, weak institutional capacity, governance deficits, and socioeconomic inequalities interact with global networks of organized crime. The findings reveal that transnational criminal syndicates exploit advancements in transportation, communication, and trade liberalization to expand illicit markets and evade detection. Moreover, the convergence of globalization and local structural vulnerabilities has deepened security and developmental challenges, undermining state authority and regional stability. The study argues for a multidimensional response anchored in regional cooperation, intelligence sharing, harmonized legal frameworks, and strengthened law enforcement institutions. It concludes that addressing the globalization–crime nexus requires not only robust security mechanisms but also inclusive governance and socioeconomic reforms that tackle the root causes of vulnerability across West Africa.

In judicial practice concerning the crime of assisting and facilitating information network crimes, cases involving "payment and settlement" scenarios account for the highest proportion. Among these, the determination of the subjective element of "knowing" is the most contentious, directly impacting the distinction between criminal and non-criminal conduct, as well as the delineation between this crime and others. To address these issues, this paper aims to explore corrective measures for judicial determinations of "knowingly" in payment settlement-related aiding and abetting of cybercrime cases. First, guided by the principle of "unifying subjective and objective elements," it proposes establishing precise and operational rules for determining "knowingly" to prevent the crime from becoming a "catch-all." Second, it accurately distinguishes between aiding and abetting cybercrimes and related offenses through comprehensive assessment of multiple factors, including the perpetrator's stage of involvement in the crime. Finally, based on a rebuttable presumption rule, it establishes a "rebuttable presumption" mechanism to prevent the improper expansion of the crime's scope. This provides theoretical support and adjudication guidance for judicial practice while safeguarding citizens' legitimate rights and interests and maintaining the order of online financial activities.

This Working Paper explores the drivers and strategies of corruption as a facilitator of drug trafficking in the port of Rotterdam, with a specific focus on cocaine trafficking. Through in-depth interviews with stakeholders, a review of judicial cases and desk research, it aims to: deepen understanding of the systems and mechanisms of corruption that enable drug trafficking; show how trafficking and corruption strategies are changing in response to increased enforcement pressure; and provide practical insights on how to further strengthen port resilience. It contributes to the growing body of work that looks at corruption from a systemic viewpoint, analysing the relationships and adaptive capabilities that allow organised crime to thrive. This research supports efforts to develop more robust and foresight-focused approaches to combat corruption and drug trafficking. About this Working Paper This paper is published as part of the Basel Institute on Governance Working Paper series, ISSN: 2624-9650. You may share or republish it under a Creative Commons BY-NC-ND 4.0 International Licence. This Working Paper was written as part of the FALCON (Fight Against Largescale Corruption and Organised Crime Networks) project. FALCON is funded under the European Union’s Horizon Europe Framework Program Grant Agreement ID 101121281. The Basel Institute on Governance, as an associated partner without the right to receive funds directly from the European Research Executive Agency, has received funding from the Swiss State Secretariat for Education, Research and Innovation (SERI). The contents of this document are the sole responsibility of the authors and do not necessarily reflect the views of the European Union, the European Research Executive Agency or SERI. Suggested citation: Kassa, Saba and Jacopo Costa. 2025. ‘Corruption as a facilitator of drug trafficking in the port of Rotterdam: Drivers, strategies and implications.’ Working Paper 58, Basel Institute on Governance. Available at: baselgovernance.org/publications/wp-58.

In view of the high incidence of information network crimes, the Amendment (IX) to the Criminal Law of mainland China added the offence of aiding information network criminal activities, aiming at cutting off the chain of cybercrime and preventing information network crimes. However, in judicial practice, there are great differences in the determination standard of "knowledge", which has become a key difficulty in the judgement of crime and non-crime. In this regard, the presumption of "knowledge" should be explicitly adopted, and the subjective knowledge of the perpetrator should be presumed through the basic facts, in order to cope with the difficulty of obtaining evidence. At the same time, the term "knowingly" should be interpreted as meaning that the perpetrator clearly recognised or should have known of the unlawfulness of the act of assistance, rather than generalising it to mean that he or she "may have known". In addition, it is not appropriate to mechanically equate the object of knowledge - "another person using information network to commit a crime" - with a completed offence in the sense of a sub-rule of the Criminal Law. Instead, it should be based on the logic of criminalisation of the act, adopt independent judgment, emphasise the ambiguity of the perpetrator's cognition of the improper act and causal foresight, so as to achieve a balance between combating crime and safeguarding rights, and maintain the principle of modesty of criminal law.

Timely and transparent registration of criminal complaints is pivotal to the rule of law. Yet in India and many developing jurisdictions, manual, station‑centric processes for lodging a First Information Report (FIR) or obtaining a Community Service Register (CSR) receipt continue to create bottlenecks, subjective gate‑keeping and opportunities for corruption. This paper presents the architecture, prototype implementation and evaluation of an Integrated Online FIR & CSR Management Application (IFC‑MA) that unifies citizen self‑service, police workflow and analytics on a single secure cloud platform. A mixed‑methods pilot across two districts demonstrates a 62 % reduction in average FIR registration time and a 41 % increase in CSR issuance for non‑cognisable offences, while maintaining evidentiary integrity and regulatory compliance. The findings indicate that IFC‑MA can serve as a modular plug‑in to the national Crime and Criminal Tracking Network & Systems (CCTNS) and accelerate the Government of India’s Digital Police vision. Keywords: Online FIR, Community Service Register, CCTNS, e‑Governance, Crime Reporting, Data Analytics, Citizen Service Delivery

Abstract Understanding the structure and resilience of organized crime groups like mafias is critical for designing strategies to disrupt their operations. This paper proposes a new protocol– proxy targeting– for network disruption analyses. By separating the targeting of nodes and their removal from the network of interest, this approach allows researchers to consider multiple dimensions in a multiplex network simultaneously, as well as the sort of information available to law enforcement in the early stages of an investigation rather than complete knowledge of the network. Multiplex network data is collected from a pre-trial detention notice and the Italian business register on an `Ndrangheta group as its members and associates sought to infiltrate legitimate businesses. Using the newly-developed proxy targeting approach, results suggest that open-source business registers can be an effective, low-cost, and easy-to-access network data source for targeting surveillance and disruption of corporate interlock dimensions that represent which actors are affiliated to the same company together; however, these data are less successful for targeting disruption of the communication dimension between actors. Further, findings suggest that multiplexity can reinforce a network’s resilience against disruption by providing fallback connectivity in the event that one dimension is destabilized. The proxy targeting protocol proposed here creates opportunities to answer new questions and to better understand how criminal networks are structured and how they can be disrupted.

The amount of information shared amongst different devices and the variety of novel methods of network crimes have exponentially increased in recent years because of the widespread use of the internet. Quick identification of all types of attacks would not be possible with conventional methods including firewalls, which focused on data filtering. Dealing with the timely recognition of these types of assaults is very successful for intrusion detection systems (IDS) grounded on ML algorithms. They can efficiently manage the enormous amount of data in order to identify any harmful behaviour. Every network activity is searched for any possibly dangerous activity using IDS based on machine learning. The main objective of the planned effort is to provide analytical analyses of such current intrusion detection systems. Furthermore, examined in this work are the useful data sets and several techniques already in use to develop an effective IDS using single, hybrid, and ensemble machine learning algorithms. The approaches in the literature have then been investigated under several criteria in line to provide a clear road and direction for the next projects that will be successful. Nowadays, companies of all kinds include an intrusion detection system (IDS), which inhibits cybercrime to protect the network, resources, and private data. Many strategies have been suggested and implemented up till now to prevent uncivil behaviour. Since machine learning (ML) approaches are successful, the proposed approach applied several ML models for the intrusion detection system. The CIC IOT 2023 Dataset is the one applied in this paper. Tested were several techniques including random forest, XG Boost, logistic regression, MLP model, and RNN. Following fine-tuning, the federated learning model using neural networks had the best accuracy—99.84%.

This study examines the environmental and criminal law policies in force in Indonesia, as well as the effectiveness of law enforcement in dealing with organized crime related to the trade in endangered fauna. Although existing regulations such as Law Number 5 of 1990 concerning Conservation of Natural Resources and Ecosystems and Law Number 32 of 2009 concerning Protection and Management of the Environment have regulated the protection of endangered fauna, this study found that its implementation in the field still faces various challenges, including weak coordination between law enforcement agencies, lack of human resources and technology, and limitations in enforcing criminal sanctions. Using the “deterrence theory” and “collaborative governance theory” approaches, this study analyzes how criminal sanctions and cross-sectoral cooperation can improve the effectiveness of law enforcement against organized crime. The results of the study show that although the criminal sanctions regulated are quite strict, their effectiveness is still weak due to the lack of certainty of enforcement and low collaboration between agencies. This study also highlights the importance of the role of local communities (Customary Institutions) and monitoring technology to support efforts to conserve endangered fauna in the TNKS area. This study provides strategic recommendations to strengthen law enforcement through increased inter-agency coordination, the use of more sophisticated monitoring technology, and expanding international cooperation to address organized crime networks operating across borders.