Intelligent Application of Artificial Intelligence Internet of Things Technology in the Economic and Legal Fields

In today’s globalized situation, people on the one hand enjoy the great convenience brought by the Internet and artificial intelligence Internet of Things (IoT) technology, and, on the other hand, they are also inevitably subject to a series of harms brought by network technology. Internet economic crime is a new type of crime based on Internet technology. Criminals use Internet technology to conduct illegal visits and Trojan horse program attacks, steal user information, and defraud victims of money. This has resulted in the people’s personal and property safety and social harmony and stability. Strictly cracking down on cyber economic crimes in accordance with the law is of great significance to safeguarding the interests of the people and maintaining social stability. However, as the methods and forms of cyber economic crimes emerge endlessly, it is very important to collect intelligence information on such crimes. This paper proposes using the sensor technology, embedded system technology, radio frequency automatic identification technology, and cloud computing technology in artificial intelligence Internet of Things technology to design and build a data-mining-based network economic crime intelligent information aggregation collection system to realize network economic crime intelligence of aggregation and analyze and help combat cyber economic crimes. This article takes cyber economic crime cases in various cities in our province as an example, selects 9 cyber economic criminals’ intelligence information as sample data, and tests and applies the designed cyber economic crime intelligence information system. The final results show that the numbers of cyber economic crime cases in four cities A, B, C, and D in four provinces are roughly the same, but city A has the largest number; the minimum confidence of the 9 criminals is above 0.60, indicating that the economic crimes of cyber economic criminals are related to their academic background and family status and criminal history are related to a certain extent; illegal fund-raising fraud and online credit card fraud account for the largest proportion of the four cities and are currently the main forms of online economic crime.

Social media: the double-edged sword for perpetuating and preventing criminal activities in Zimbabwe

Purpose This study aims to evaluate social media’s role in facilitating criminal activities in Zimbabwe and determine how social media platforms have been embraced by the Zimbabwean police to curb criminal activities. Design/methodology/approach A total of 72 participants from the Zimbabwean police and 5 non-police security experts were invited to participate in this study through questionnaires and in-depth interviews. The study was confined to an urban policing area, which is policed by approximately 400 police officers. Findings The facilitation of violent protests was found to be the major threat that is posed by social media in Zimbabwe, with social media platforms playing a catalytic role in fuelling these violent protests. Social media is also playing a significant role in the spread of fake news, with the intention of causing fear and panic amongst citizens. Findings also reveal that the Zimbabwe police have embraced social media platforms for sharing crime prevention tips, receiving crime reports, engaging with citizens and gathering crime intelligence. Originality/value The study provides context-specific information on the threats posed by social media on a developing nation that has been characterised by a myriad of socio-economic challenges, as well as how these social media platforms have been embraced for crime prevention and control. Given limited empirical research on social media and national security in Zimbabwe, this study adds to the existing body of knowledge.

Intelligence-Led Policing in Practice: Reflections From Intelligence Analysts

Intelligence-led policing (ILP) is a managerial law enforcement model that seeks to place crime intelligence at the forefront of decision-making. This model has been widely adopted, at least notionally, in the United States, United Kingdom, Canada, and Australia. Drawing on interviews with intelligence analysts from two Australian state law enforcement agencies, this article contributes to the relatively small body of literature that has examined ILP in practice. The article identifies three relational themes that inhibit the successful implementation of ILP: analysts and data, analysts and tools, and analysts and decision makers. Furthermore, it calls attention to the need to better understand the structure and operations within law enforcement agencies, including the similarities and differences among organizational units, in order to better understand how these nuances shape the practice of ILP.