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Article
Publication date: 16 August 2023

Jialiang Xie, Shanli Zhang, Honghui Wang and Mingzhi Chen

With the rapid development of Internet technology, cybersecurity threats such as security loopholes, data leaks, network fraud, and ransomware have become increasingly prominent…

Abstract

Purpose

With the rapid development of Internet technology, cybersecurity threats such as security loopholes, data leaks, network fraud, and ransomware have become increasingly prominent, and organized and purposeful cyberattacks have increased, posing more challenges to cybersecurity protection. Therefore, reliable network risk assessment methods and effective network security protection schemes are urgently needed.

Design/methodology/approach

Based on the dynamic behavior patterns of attackers and defenders, a Bayesian network attack graph is constructed, and a multitarget risk dynamic assessment model is proposed based on network availability, network utilization impact and vulnerability attack possibility. Then, the self-organizing multiobjective evolutionary algorithm based on grey wolf optimization is proposed. And the authors use this algorithm to solve the multiobjective risk assessment model, and a variety of different attack strategies are obtained.

Findings

The experimental results demonstrate that the method yields 29 distinct attack strategies, and then attacker's preferences can be obtained according to these attack strategies. Furthermore, the method efficiently addresses the security assessment problem involving multiple decision variables, thereby providing constructive guidance for the construction of security network, security reinforcement and active defense.

Originality/value

A method for network risk assessment methods is given. And this study proposed a multiobjective risk dynamic assessment model based on network availability, network utilization impact and the possibility of vulnerability attacks. The example demonstrates the effectiveness of the method in addressing network security risks.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 17 no. 1
Type: Research Article
ISSN: 1756-378X

Keywords

Book part
Publication date: 27 June 2023

Mingzhi Li, Jill Sible, Helene Goetz, Adyan Atiq and Keshav Bhateja

The VTBound program was implemented at Virginia Tech to ensure international student enrollment despite travel and visa restrictions during the pandemic. The program was a…

Abstract

The VTBound program was implemented at Virginia Tech to ensure international student enrollment despite travel and visa restrictions during the pandemic. The program was a partnership across academic affairs, student affairs, and admissions. Eighty-two first-year undergraduate international students from 19 countries participated in a full-time remote curriculum directed to their intended major (mostly engineering). Instruction was primarily asynchronous with synchronous office hours and recitations attentive to global time differences. Support mechanisms to maximize student success included dedicated academic advising and a customized first-year experience (FYE) course with peer mentors. The academic performance of and adherence to academic integrity standards by these students exceeded that of domestic and international first-year students on campus. Many VTBound students became engaged in co- and extracurricular programming while studying remotely. The greatest challenge was limited access to visa appointments and global travel restrictions necessitating a second remote semester for most VTBound students. Overall, the VTBound program demonstrates the value of a customized first-year transition program for international students and the potential to engage students for a successful semester of remote learning from their home Countries.

Article
Publication date: 5 September 2023

Maha Khalifa, Haykel Zouaoui, Hakim Ben Othman and Khaled Hussainey

The authors examine the effect of climate risk on accounting conservatism for a sample of listed companies operating in 26 developing countries.

Abstract

Purpose

The authors examine the effect of climate risk on accounting conservatism for a sample of listed companies operating in 26 developing countries.

Design/methodology/approach

The authors employ the Climate Risk Index (CRI) developed by Germanwatch to capture the severity of losses due to extreme weather events at the country level. The authors use different approaches to measure firm-level accounting conservatism.

Findings

The authors find that greater climate risk leads to a lower level of accounting conservatism. The results hold even after using different estimation methods.

Research limitations/implications

Although the authors' analysis is limited to the period 2007–2016, it could be helpful for standard setters such as International Accounting Standards Board (IASB) and International Sustainable Standards Board (ISSB) as they may consider the potential effect of climate risk in their international standards.

Practical implications

The negative impacts of climate risk on the quality of financial reporting as proxied by accounting conservatism could trigger regulators and standard setters to require disclosure of information relating to climate risks and to incorporate climate-related risks in their risk management systems. In addition, for policymakers, incorporating accounting conservatism as a financial quality reporting standard could help promote greater transparency, accuracy and reliability in financial reporting in the context of climate risk.

Originality/value

The authors add to the literature on international differences in accounting conservatism by showing that climate risk significantly affects unconditional and conditional conservatism. The authors' results provide fresh evidence of the dark side of climate change. That is, climate risk is shown to decrease financial reporting quality.

Details

Journal of Applied Accounting Research, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0967-5426

Keywords

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