Risk Analysis for the Digital Age

Gerunov, Anton

doi:10.1007/978-3-031-18100-9

Cited by 2 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Privacy and security -The use of AI in disaster risk management often involves processing large amounts of personal data, which raises privacy and security concerns (Douglass et al, 2023). It is crucial to ensure that the data is securely stored and processed in accordance with privacy regulations and that the rights of individuals are protected (Gerunov, 2023;Montasari, 2022).…”

Section: Artificial Intelligence Limitations For Disaster Risk Manage...mentioning

confidence: 99%

Challenges of Artificial Intelligence Application for Disaster Risk Management

Velev

Златева

2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

Abstract. Artificial Intelligence (AI) has the potential to play a significant role in disaster risk management – from predicting disasters to optimizing response efforts. However, its application in disaster management also presents significant challenges. These challenges include the need for high-quality and diverse data, compatibility with existing systems and technologies, ethical and social implications, and ongoing research and development. In addition, data privacy and security is a critical issue as the use of AI in disaster management often involves the collection and analysis of sensitive information. Addressing these challenges is crucial to ensuring that AI is developed and used in ways that are fair, equitable, and effective in reducing the impact of disasters. The aim of the paper is to provide an analysis of challenges of artificial intelligence application for disaster risk management.

show abstract

Section: Artificial Intelligence Limitations For Disaster Risk Manage...mentioning

confidence: 99%

Challenges of Artificial Intelligence Application for Disaster Risk Management

Velev

Златева

2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

show abstract

“…Regarding the analyses of the information gathered from phase 1, we proceed to classify the IT infrastructure's components per priority levels. Once this is done, we can identify the asset's vulnerabilities [16] in order to mitigate security risks and give a cyber-security [17] solution. The objective of this phase is to know in detail the procedures, elements, policies, and IT infrastructure risks.…”

Section: Identify Infrastructure Vulnerabilitiesmentioning

confidence: 99%

Leveraging Security Modeling and Information Systems Audits to Mitigate Network Vulnerabilities

Arenas,

Yactayo-Arias,

Quispe

et al. 2023

IJSSE

View full text Add to dashboard Cite

Advancements in digital technologies have significantly enhanced the functional capabilities of consumers and businesses alike, yet have concurrently amplified the complexities associated with cybersecurity, including theft and cyber-attacks. Consequently, auditing of information systems has emerged as a crucial security apparatus for organizations aiming to safeguard their data assets, specifically with respect to customer information. This study aims to design an information systems security and audit model that emphasizes the fortification of an organization's crucial assets via IT infrastructure security and information security management systems, in alignment with ISO 27001 standards. The proposed model seeks to assure information confidentiality, integrity, availability, and compliance with legal mandates. The study adopted the OCTAVE v2.0 method, executed in three distinct phases. In the first phase, profiles of asset-based threats were constructed. The second phase involved the identification of infrastructure vulnerabilities, whereas the final phase focused on the development of a security strategy and plans. The implementation of the proposed model yielded a marked impact, with a positive shift from 46% to 94% following the establishment of IT infrastructure security policies. The study underscores the importance of conducting a comparative analysis prior to implementation and asserts that well-defined and identified security models and information systems auditing can effectively counteract potential data leaks and cyber-attacks such as malware, phishing, spam, and ransomware. The findings suggest that a meticulous and preemptive approach to auditing and security planning can significantly bolster the resilience of an organization's digital infrastructure.

show abstract

Risk Analysis for the Digital Age

Cited by 2 publications

References 0 publications

Challenges of Artificial Intelligence Application for Disaster Risk Management

Challenges of Artificial Intelligence Application for Disaster Risk Management

Leveraging Security Modeling and Information Systems Audits to Mitigate Network Vulnerabilities

Contact Info

Product

Resources

About