Искусственный интеллект в криминалистическом использовании технологий автоматического распознания лиц

Аннотация

The article deals with the issues of ensuring national security through deployment of facial recognition technologies in forensics. It also takes a close look at the emerging trend of utilizing artificial intelligence in this field and aims to unravel the mystery of the so-called Deep learning by focusing on the phenomena being incorporated into facial recognition technologies. Keywords: Forensics, Artificial intelligence, Deep learning, Algorithms, Facial recognition, Technology, Crime, National security, Identification, Verification Introduction. The issues of ensuring national security are now becoming increasingly relevant affecting the interests of a wide range of subjects. The volume of information as well as information technologies and the processes of globalization form the conditions under which the world information arena becomes a means of achieving various goals, namely a unique phenomenon and a new sphere of society’s day-to-day life. Taking into account the increasing volume and availability of information and information resources, the changing technological landscape of modern society, it seems necessary to take into consideration the challenges and problems unique to our time requiring close attention from the legislative and executive branches of the government. On the international level, the problem of combating crime is quickly gaining worldwide relevancy and significance. The world economy is being actively transformed and is characterized by increased instability, caused in part by transition to a new technological order. On a global scale, markets are being redistributed, financial flows and productive forces are also being redistributed, and competition is becoming tougher through escalation of interests. Technological evolution is rapidly becoming a source of fundamentally new 202 Цифровые технологии в системе уголовно-правовых отношений threats and opportunities, providing previously inaccessible options for both negative and positive influence on the individual, state, and society in general. Many indicators of crime (dynamics, structure, latency, detection) largely depend on the effectiveness of the fight against professional crime and its prevention, which cannot be fully conducted without the use of modern technological advances. Successful crime prevention in 2022 is characterized in large part by new strategies and approaches to its implementation. It should be noted that one of the most promising tools for the investigation, solving and prevention of crimes can be the technology capable to strip a perpetrator of his actual or perceived (in case of crime prevention) anonymity. In modern days, the main driving force of crime, in addition to the motive for committing a crime (usually it’s greed, jealousy or hatred), is the expectation of the criminal that his identity will remain unknown. Thus, a potential criminal, hiding his identity, eventually commits a felony or misdemeanor (depending on the illegal activity) – as examples of this could be seen the riots and property destruction by mobs in Minsk on August 20, 2020; uprising on the Capitol Hill in the USA on January 6, 2020; riots and damage to property by the Black Lives Matter organization on May 25 in the USA; aggressive protests by truckers on February 12, 2022 in Canada, etc. For the same reason, we can observe an exponential increase in cybercrime around the world, namely perceived or actual anonymity of a perpetrator. The most effective way to deprive a criminal of his anonymity appears to be the automatic face recognition technology (AFRT). However, in the Russian-language literature, there is almost no analysis of the concepts of face recognition proposed by various researchers – a clear classification of face recognition in the investigation of crimes is not proposed; prospects for further implementation in the investigation of crimes in the future are not offered. All these aspects are extremely important for the current stage of the development of criminalistics. Main body. Throughout its development, face recognition in criminalistics has gone through several stages of its development: 1) verbal portrait; 2) bertillonage-anthropometry; 3) photo-video technology; 4) automatic recognition by facial characteristics. In turn, the process of development of automatic recognition by facial characteristics and other signs can also be divided into the following stages of the formation of this technology: 1) quasi-automatic computerized face recognition systems; 2) fully automatic recognition and the emergence of biometric databases of persons for identification; 3) the use of linear algebra to work with images; 4) the implementation of this technology to ensure the safety of public order, disclosure and investigation of crimes; 5) the development and use of numerous algorithms in the development of automatic face recognition systems; 6) 3D face recognition and artificial intelligence [1. P. 16–17]. Over the past 10 ye