The success of an organisation depends on its employees’ skills and the extent to which they are developed. Although organisations often assume employees are fit and ready for a new position or new developments in their functions, employees need adequate training before, during and after effective performance in their respective roles. Amongst other important roles, training is significant in problem-solving, continuously improving skills, and creating consistency or culture in the work environment. Nonetheless, the significance of training is often disregarded or not understood by organisations as there are often inadequacies, inconsistencies, and ignorance from the employer. Furthermore, organisations are facing cybersecurity skills shortages. Some specialists leave the profession due to a lack of skills or support. The lack of experienced and qualified cyber security specialists increases the risk of IT system systems being targeted with cyber-attacks. Having insufficient cybersecurity staff, companies may struggle to protect their networks from attacks. Organisations are being placed into a troubling position as the threat landscape continues to evolve. With the growth in volume and sophistication of cyber security attacks, the problem of a skilled workforce is exasperated. In order to support the cybersecurity workforce, this paper proposes the implementation of learning factories. Typically, learning factories have been used in the manufacturing sector. However, the fundamental principles and guiding ideologies can also be applied in the cybersecurity domain. Learning factories provide a mechanism to remove the barriers of entering the field of cybersecurity by cultivating and nurturing a cybersecurity workforce. They enable the broadening of the scope for talent and change our current working practices and tighten the gap between education and experience. The closing of the talent gap is an important imperative for cybersecurity. In this paper, a motivation and description of the functionality of learning factories for cybersecurity is provided. Through this paper the benefits of learning factories will be highlighted in order to show the advantages of active engagements in learning activities, real-world application and information sharing.
Misinformation can be rapidly spread in cyberspace. It thrives in the social media landscape as well as news platforms. Misinformation can readily gain momentum in the race to influence people or intentionally deceive. With the use of bots, misinformation can be easily shared, especially in environments like Twitter and Facebook. While, some measures are taken to stop the spread of misinformation, threats like Deepfakes are posing a higher challenge. Deepfakes provide a means to generate fake digital content in order to impersonate a person. With the use of audio, images and videos, artificial intelligence is used to depict the speech and actions of people. Deepfakes are typically made of presidents or influential businessmen such as Donald Trump and Mark Zuckerberg. Deep Fakes can be very realistic and convincing as this form of synthetic media is raising concerns about its possible misuse. The effects of Deepfakes are to spread disinformation, confuse users or create influence. This can lead to further effects like political factions, blackmail, harassment and extortion. Deepfakes could lead to a distrust in digital content as many may feel that anything we see is actually just a manipulation. Deepfakes has arisen as a new generation of misinformation through the manipulation of digital media in order to create realistic videos. This paper looks at the governing, communal and technical issues relating to Deepfakes. At the technical level, the use of audio and text analysis used to create Deepfake videos is advancing at a rapid pace which has also made its affordability and accessibility easier. An evaluation of the threats stemming from Deepfakes reveals that there are various mental, monetary and group dynamics involved. In this paper, the various types of threats emanating from Deepfakes is discussed. This paper also looks at five factors in the field of Deepfakes that should be taken into consideration (Technical Source Dissemination Victim Viewers). The paper discussed these five factors in order to help identify measures to help curb the spread of Deepfakes. A combination of these measures can help limit the spread of Deepfakes and support mitigation of the threat. Due to prominence and power that digital media has, it is imperative that this threat not be overlooked. The paper provides a holistic approach to understanding the risk and impact of Deepfakes, as well measures to help mitigate abuse thereof.
The use of social network sites has exploded with its multitude of functions which include posting pictures, interests, activities and establishing contacts. However, users may be unaware of the lurking dangers of threats originating from Social Networking Sites (SNS) which include malware or fake profiles. This paper investigates the indicators to arouse suspicion that a social networking account is invalid with a specific focus on Facebook as an illustrative example. The results from a survey on users’ opinions on social networks, is presented in the paper. This helps reveal some of the trust indicators that leads users to ascertaining whether a social networking profile is valid or not. Finally, indicators of potentially deceptive agents and profiles are given as a guideline to help users decide whether they should proceed with interaction with certain contacts.
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