While many researchers have investigated soft skills for different roles related to business, engineering, healthcare and others, the soft skills needed by the chief information security officer (CISO) in a leadership position are not studied in-depth. This paper describes a first study aimed at filling this gap. In this multimethod research, both the business leaders perspective as well as an analysis of CISO job ads is studied. The methodology used to capture the business leaders perspective is via a Delphi study and the jobs adds are studied using a quantitative content analysis. With an increasing threat to information security for companies, the CISO role is moving from a technical role to an executive role. This executive function is responsible for information security across all layers of an organisation. To ensure compliance with the security policy among different groups within the company, such as employees, the board, and the IT department, the CISO must be able to adopt different postures. Soft skills are thus required to be able to assume this leadership role in the organisation. We found that when business leaders were asked about the most important soft skills the top three consisted out of 'communication', ‘leadership’ and 'interpersonal' skills while 'courtesy' was last on the list for a CISO leadership role.
MULTIFILE
In today’s world, information security is a trending as well as a crucial topic for both individuals and organizations. Cyber attacks cause financial loss for businesses with data breaches and production loss. Data breaches can result in loss of reputation, reduced customer loyalty, and fines. Also due to cyber attacks, business continuity is affected so that organizations cannot provide continuous production. Therefore, organizations should reduce cyber risks by managing their information security. For this purpose, they may use ISO/IEC 27001 Information Security Management Standard. ISO/IEC 27001:2013 includes 114 controls that are in both technical and organizational level. However, in the practice of security management, individuals’ information security behavior could be underestimated. Herein, technology alone cannot guarantee the safety of information assets in organizations, thereby a range of human aspects should be taken into consideration. In this study, the importance of security behavior with respect to ISO/IEC 27001 information security management implementation is presented. The present study extensively analyses the data collected from a survey of 630 people. The results of reliability measures and confirmatory factor analysis support the scale of the study.
MULTIFILE
Amsterdam Airport Schiphol has faced capacity constraints, particularly during peak periods. At the security screening checkpoint, this is due to the growing number of passengers and a shortage of security staff. To improve operating performance, there is a need to integrate newer technologies that improve passing times. This research presents a discrete event simulation (DES) model for the inclusion of a shoe scanner at the security screening checkpoint at Amsterdam Airport Schiphol. Simulation is a frequently used method to assess the influence of process changes, which, however, has not been applied for the inclusion of shoe scanners in airport security screenings yet. The simulation model can be used to assess the implementation and potential benefits of an optical shoe scanner, which is expected to lead to significant improvements in passenger throughput and a decrease in the time a passenger spends during the security screening, which could lead to improved passenger satisfaction. By leveraging DES as a tool for analysis, this study provides valuable insights for airport authorities and stakeholders aiming to optimize security screening operations and enhance passenger satisfaction.
Despite the benefits of the widespread deployment of diverse Internet-enabled devices such as IP cameras and smart home appliances - the so-called Internet of Things (IoT) has amplified the attack surface that is being leveraged by cyber criminals. While manufacturers and vendors keep deploying new products, infected devices can be counted in the millions and spreading at an alarming rate all over consumer and business networks. The objective of this project is twofold: (i) to explain the causes behind these infections and the inherent insecurity of the IoT paradigm by exploring innovative data analytics as applied to raw cyber security data; and (ii) to promote effective remediation mechanisms that mitigate the threat of the currently vulnerable and infected IoT devices. By performing large-scale passive and active measurements, this project will allow the characterization and attribution of compromise IoT devices. Understanding the type of devices that are getting compromised and the reasons behind the attacker’s intention is essential to design effective countermeasures. This project will build on the state of the art in information theoretic data mining (e.g., using the minimum description length and maximum entropy principles), statistical pattern mining, and interactive data exploration and analytics to create a casual model that allows explaining the attacker’s tactics and techniques. The project will research formal correlation methods rooted in stochastic data assemblies between IoT-relevant measurements and IoT malware binaries as captured by an IoT-specific honeypot to aid in the attribution and thus the remediation objective. Research outcomes of this project will benefit society in addressing important IoT security problems before manufacturers saturate the market with ostensibly useful and innovative gadgets that lack sufficient security features, thus being vulnerable to attacks and malware infestations, which can turn them into rogue agents. However, the insights gained will not be limited to the attacker behavior and attribution, but also to the remediation of the infected devices. Based on a casual model and output of the correlation analyses, this project will follow an innovative approach to understand the remediation impact of malware notifications by conducting a longitudinal quasi-experimental analysis. The quasi-experimental analyses will examine remediation rates of infected/vulnerable IoT devices in order to make better inferences about the impact of the characteristics of the notification and infected user’s reaction. The research will provide new perspectives, information, insights, and approaches to vulnerability and malware notifications that differ from the previous reliance on models calibrated with cross-sectional analysis. This project will enable more robust use of longitudinal estimates based on documented remediation change. Project results and methods will enhance the capacity of Internet intermediaries (e.g., ISPs and hosting providers) to better handle abuse/vulnerability reporting which in turn will serve as a preemptive countermeasure. The data and methods will allow to investigate the behavior of infected individuals and firms at a microscopic scale and reveal the causal relations among infections, human factor and remediation.
