Human Factors in Cybersecurity最新文献

{"title":"Bringing humans at the core of cybersecurity: Challenges and future research directions","authors":"K. Kioskli, H. Mouratidis, Nineta Polemi","doi":"10.54941/ahfe1003722","DOIUrl":"https://doi.org/10.54941/ahfe1003722","url":null,"abstract":"The prompt response to successfully adopt good cybersecurity practices from protecting passwords to security incidents’ responding to activating a disaster recovery or a business continuity plan depends upon the level of operators’ ability in problem solving, resilience, readiness, maturity, observation, and perception. New technologies, such as Artificial Intelligence (AI) can also be helpful to more effectively forecast or respond to serious incidents, especially to massive attacks. However, the cybersecurity operators need to alter their mindsets, adopt new behavioural patterns, and work attitudes to embrace and interact with AI-assistance during cyber defence activities. in addition, when the operators need to assess or mitigate AI socio-technical risks related to bias, transparency and equality, they will base their decisions for estimating or mitigating these risks on their behavioural, social, cultural, and ethical characteristics. In this paper, we are presenting challenges related to human and psychosocial factors of the cybersecurity operators. We also discuss the motives and drivers that impact the cognitive aspects (e.g., focus on operational tasks, attention, objectivity) of the cyber operations. We further identify how the cybersecurity operators’ personality traits impact the success of the cybersecurity practices and estimations and analyse research challenges, regarding the impact of operators’ profiles on their perceptions and interactions, with AI cyber defending tools and management of AI risks. Finally, we consider the impact these human factors may have on successful cybersecurity operations and practices and provide proposals for interdisciplinary research directions requiring the collaboration of cybersecurity experts, psychologists, and behavioural scientists.","PeriodicalId":373044,"journal":{"name":"Human Factors in Cybersecurity","volume":"200 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131541685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Privacy Concerns about Smart Home Devices: A Comparative Analysis between Non-Users and Users","authors":"Chola Chhetri, Vivian Genaro Motti","doi":"10.54941/ahfe1002207","DOIUrl":"https://doi.org/10.54941/ahfe1002207","url":null,"abstract":"Privacy concerns of smart home device (SHD) users have been largely explored but those of non-users are under-explored. The success of smart home technology comes to fruition only when concerns of both users and non-users are addressed. Understanding of non-user concerns is essential to inform the design of user-centric privacy-preserving SHDs, facilitate acceptance, and bridge the digital divide between non-users and users. To address this gap, we conducted a survey of SHD non-users and comparatively analyzed their privacy concerns with those of users.Methods: We used university email list-servs, snowball sampling and random sampling methods to recruit participants (n=91) for an IRB-approved online survey, titled ‘smart home study’. Our pre-tested questionnaire asked about SHD (non-)usage, privacy concerns (open-ended), suggestions for developers and demographics. We followed a mixed-methods approach to analyze privacy concerns (qualitative/thematic), explore non-use reasons (qualitative/thematic), compare non-users and users concerns (quantitative), and analyze design suggestions (qualitative/thematic). Results: Thematic analysis of privacy concerns of non-users (n=41) and users (n=50) by two researchers performing open-coding (Cohen’s kappa = 0.8) resulted in 17 codes. We then performed axial coding to generate three thematic areas of privacy concerns. The first theme was ‘data collection concerns’ which included five codes: recording audio/video, tracking occupancy, listening to private conversations, monitoring usage/behavior, and identity theft. The second theme was ‘data sharing concerns’ which included four codes: selling data, third party data access, leakage without consent, and marketing data. The third theme was ‘data protection concerns’ which included eight codes: hacking, data handling, protecting data, secondary use, aggregation, data abuse, data loss, and fraud. The three privacy concerns themes belong to the personal communication and personal data privacy dimensions of privacy. Chi-square test between non-users and users showed the privacy concerns of non-users differed significantly (X2=8.46, p<0.05) from users. Non-users reported higher level of concerns in data collection and data protection themes than those of users (46% vs 24% and 34% vs 30% respectively). However, non-users reported fewer concerns in the data sharing theme than those of users (15% vs 28% respectively).Most non-users reported their non-use reason to be privacy concerns (68%). Other non-use reasons included lack of interest in SHDs (32%), cost (22%), lack of perceived usefulness (12%), insecurity or potential of hacking (10%), and perceived difficulty of usage (7%).The thematic analysis of participants’ suggestions for developers resulted in four main themes: (a) data anonymization and minimization, (b) data protection and security, (c) transparent data use policies, and (d) user-centric practices. Based on our findings, we recommend that developers addres","PeriodicalId":373044,"journal":{"name":"Human Factors in Cybersecurity","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132992993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}