ABSTRACT. Digitisation is being adopted across industry sectors, accelerated by events such as Covid-19 and Brexit. Amongst other industries, agriculture has rightfully been a major focal point in demonstrating the potential benefits that could be realised through digitisation. However, what does become challenging are the security implications in managing these physical production environments in the cloud across multiple vendors technologies and standards. Our goal is to engage in discussing practical approaches to achieving end-to-end security controls in a feasible manner.

ABSTRACT. The assessment of perceived safeness and risk by individuals is extremely useful for safety and security managing. Every person is founded on the opinion of other individuals to get a selection and the Internet personifies the location where these opinions are mostly sought, obtained, and evaluated. From this point of view, social networks are characterized by a significant effect. For this reason, Opinion Mining and Sentiment Analysis have found remarkable applications in various environments and one of the most interesting is represented by public safety and security. The aim of this work is to study the perception of risk within the air and airport environments of London (UK) and Rome (Italy) during COVID-19 pandemic. In particular, the airports of London Heathrow and Gatwick and the airports of Rome Fiumicino and Ciampino were studied, from March 23 to July 9, 2020, highlighting the emotional components in three distinct pandemic phases of the considered period in the two countries, using the semantic analysis of the textual contents present in Twitter.

ABSTRACT. The development and use of Artificial Intelligence (AI) within security technologies presents a number of opportunities and risks for security professionals. The study was undertaken to investigate the use of AI in security technologies within the functional categories of Observing, Detecting, Controlling and Responding technologies, exploring the risks associated with enhanced AI across these technologies. In exploring these risks, the study developed a novel scale to define the level of intelligent autonomy a technology may possess during operation, in addition the degree of human involvement retained at each level across the various stages of the AI operational cycle. The Security Technologies Intelligent Autonomy Scale may be used to consider the risks which may emerge at each level, with a weighting towards consequences of outcome.

ABSTRACT. The evaluation of perceived risk by people is particularly valuable for safety and security management. Each person is based on the opinion of others to make a choice and the Internet embodies the place where these opinions are mainly researched, found, and reviewed. Social networks have a significant impact: 92% of consumers declare they trust more of social media reviews than in any other form of advertising. For this reason, Opinion Mining and Sentiment Analysis have found noteworthy uses in different context, among which the most advanced is surely represented by public safety and security. Security managers can use the perceptions communicated by people to find the unpredicted and possible faults of a monitored environment or anyway the risk and security perception of people that sometimes can be truly diverse from real level of risk and security of a given site. Since the perceptions are the effect of mostly unconscious elaborations, it is necessary to go deeper and to search for the emotions, triggered by the sensorial stimuli, that define them. The purpose of this paper is to study the perception of risk within the Hercolaneum Archaeological Park, providing emphasis to the emotional components, applying the semantic analysis of the textual contents present in Twitter.

ABSTRACT. Safety engineering and cyber security have complementary aims, but typically realise these using different techniques, risk assessment methods and cultural approaches. As a result, the integration of safety and cyber security concerns is a complex process, with potential for conflict. We present a generalized taxonomy of common conflict areas between safety and cyber security, oriented around the development and deployment lifecycle, and supplement this with a discussion of concepts and methodologies for resolution based on the shared principle of defence-in-depth.

ABSTRACT. - The evaluation of perceived safeness and risk by persons is particularly valuable for safety and security handling. Each individual is influenced by others’ opinions on safety and security and the Internet embodies the place where these opinions are mostly pursued, acquired, and estimated. From this point of view, social networks play a considerable influential role. For this reason, Opinion Mining and Sentiment Analysis have found noteworthy uses in a variety of situations and one of the most interesting is embodied by public safety and security. The goal of this work is to examine the perception of safety and risk within the railway stations of London (UK) and Rome (Italy) during COVID-19 pandemic. In particular, the railway stations of London Victoria and Waterloo and the railway stations of Rome Termini and Tiburtina were considered, from March 23 to July 9, 2020, highlighting the emotional components in three distinct pandemic phases of the considered period in the two countries, by means of the semantic analysis of the textual contents present in Twitter.

ABSTRACT. The estimation of perceived safeness and risk by individuals is very significant for safety and security managing. Every person is based on the judgments of other persons to do a choosing and the Internet personifies the location where these judgments are mostly tracked, obtained, and assessed. From this point of view, social networks have a significant influence. For this reason, Opinion Mining and Sentiment Analysis have found remarkable utilizes in a multiplicity of circumstances and one of the most notable is represented by public safety and security. The purpose of the present work is to investigate the perception of safeness and risk of drones during COVID-19 pandemic in Italy. It was considered the period from Aprile 15 to December 10, 2020, properly divided into 4 significant phases, highlighting the emotional components using the semantic analysis of the textual contents present in Twitter.

ABSTRACT. The article discusses theoretical problems of identification and determination of soft targets described by legislative documents. Currently, the definition of soft targets is not clear, so a methodology has been developed that eliminates this problem. To ensure the user-friendliness of the methodology, a software tool will be designed to assist users in distinguishing between soft, hard targets and critical infrastructure elements. This is a complicated task; therefore, the problem will be simplified only to the transport sector where could be covered almost all options. The article will describe the concept of the software tool, including user requirements and criteria.