Antecedents for enhanced level of cyber-security in organisations

Kumar, Saurabh; Biswas, Baidyanath; Bhatia, Manjot Singh; Dora, Manoj

doi:10.1108/jeim-06-2020-0240

Cited by 27 publications

(23 citation statements)

References 141 publications

(246 reference statements)

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“…In most developed countries, shared housing is regarded as a short-term and cheap form of accommodation, and this form of accommodation often appears to meet the needs of single adults with limited income. 72 In other words, the form of shared housing is usually aimed at young people, especially when housing costs are rising and social housing is relatively scarce. These young people are often in a period of rising career and are more constrained by the economy, so they choose to share the housing to relieve the economic pressure.…”

Section: Discussionmentioning

confidence: 99%

The Impact of Trust on the Willingness of Co-Tenancy Behavior: Evidence from China

Yu¹,

Zhang²

2021

PRBM

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Introduction Nowadays, more and more people choose to rent houses in first-tier cities together with other people, which can alleviate certain economic pressure. Therefore co-tenancy has become an important field of academic research in recent years and a number of previous studies have discussed the phenomenon. However, fewer studies explore the influence of different variables on the willingness of co-tenancy behavior through quantitative methods. Methods This study conceptualizes and implements concepts such as trust, positive emotion, relationship strength, satisfaction, income, duration of co-tenancy required and the willingness of co-tenancy behavior(WOCB). We designed and collected a questionnaire and finally a questionnaire survey of users (n=525) was conducted, and a basic description and comparison of research objects’ willingness of co-tenancy behavior were made in terms of trust, and positive emotion, relationship strength and monthly income also affect the willingness of co-tenancy behavior. Results The trust effects have a positive impact on the WOCB, Trust effect will affect Relationship Strength and Positive Emotion, and will further affect the WOCB. However, this influence is negative when people are in high Monthly Income and negative when people are in low Monthly Income. Discussion Trust, relationship strength and positive emotion are key factors for people to rent houses with others. That is to say, the intensity of people’s willingness to rent houses with others depends on the degree of trust in others, the relationship strength and positive emotion. When the post-90s drifters in Shenzhen do not believe others, they will tend to live alone rather than the new model of co-tenancy. We also suspect that a person with negative emotion far greater than positive emotion prefers to live alone, rather than living in the same place with his roommates. It provided certain group implications for their willingness of co-tenancy behavior.

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Section: Discussionmentioning

confidence: 99%

The Impact of Trust on the Willingness of Co-Tenancy Behavior: Evidence from China

Yu¹,

Zhang²

2021

PRBM

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“…Additionally, this model will benefit organizations and services providers in smart cities because of the high costs of implementing and maintaining cyber security solutions [59]. The organizations and service providers in smart cities can take accurate proactive measures against detected cyber attacks such as data breaches, which will help in saving costs [60]. Furthermore, our proposed model can be implemented in the cloud to monitor cyber security and collect and update cyber threat data from the connected systems in smart cities.…”

Section: Theoretical and Practical Implicationsmentioning

confidence: 99%

Towards a Hybrid Machine Learning Model for Intelligent Cyber Threat Identification in Smart City Environments

Al-Taleb

Saqib

2022

Applied Sciences

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The concept of a smart city requires the integration of information and communication technologies and devices over a network for the better provision of services to citizens. As a result, the quality of living is improved by continuous analyses of data to improve service delivery by governments and other organizations. Due to the presence of extensive devices and data flow over networks, the probability of cyber attacks and intrusion detection has increased. The monitoring of this huge amount of data traffic is very difficult, though machine learning algorithms have huge potential to support this task. In this study, we compared different machine learning models used for cyber threat classification. Our comparison was focused on the analyzed cyber threats, algorithms, and performance of these models. We have identified that real-time classification, accuracy, and false-positive rates are still the major issues in the performance of existing models. Accordingly, we have proposed a hybrid deep learning (DL) model for cyber threat intelligence (CTI) to improve threat classification performance. Our model was based on a convolutional neural network (CNN) and quasi-recurrent neural network (QRNN). The use of QRNN not only resulted in improved accuracy but also enabled real-time classification. The model was tested on BoT-IoT and TON_IoT datasets, and the results showed that the proposed model outperformed the other models. Due to this improved performance, we emphasize that the application of this model in the real-time environment of a smart system network will help in reducing threats in a reasonable time.

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“…These measures should include both preventive and corrective actions if necessary. The involvement of the senior management and the proactive security measures are the most important antecedents for increasing cybersecurity in a company (Kumar et al, 2020). As a benefit of a corporate governance framework and standardized security measures, all employees of the company would apply the same information security practices, and it would Financial impacts of IS security breaches safeguard the information's integrity and value until it reaches the authorized outside recipients.…”

Section: Managerial Implicationsmentioning

confidence: 99%

The financial impacts of information systems security breaches on publicly traded companies: reactions of different sectors

Tayaksi

Ada

Kazançoğlu

et al. 2021

JEIM

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PurposeToday, information systems and technology provides a wide set of tools for companies to increase the efficiency of their businesses. Although technology offers many benefits to businesses, it also brings risks as the information systems security breaches. Security breaches and their financial impact is a constant concern of the researchers and practitioners. This paper explores information systems breaches and their financial impacts on the publicly traded companies in different sectors.Design/methodology/approachAfter a comprehensive data collection process, data from 192 events are analyzed by employing Event Study Methodology and a comparison of the results between the four highly affected sectors (Consumer Goods, Technology, Financial and Communications) is presented. The abnormal returns on the prices of stocks after the events are calculated with the Market Model. Also, the results of the Market Adjusted Model and Mean Adjusted Model are presented to support the results.FindingsWhile information systems security breaches have a significant negative impact on the Financials and the Technology sectors for all the event windows in the study ([−5, 0], [−5, 1], [−5, 5], and [−5, 10]), the significant negative impact is observed only on the [−5, 5] and [−5, 10] event windows for the Consumer Goods sector. No significant negative impact is observed in the Communications sector, in fact, the cumulative abnormal returns are positive for this sector.Originality/valueThe contribution of this paper to provide evidence about the financial impacts of the information systems breaches for businesses in different sectors. While there are studies that have previously focused on the information systems breaches and their financial impacts on businesses, to the best of our knowledge, this is the first study that compares this effect between the four highly impacted sectors. With a relatively larger sample size and broader event windows than the past studies in the literature, statistical evidence is provided to managers to justify their investments in information security and build preventive measures to secure the market value of their firms.

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Antecedents for enhanced level of cyber-security in organisations

Cited by 27 publications

References 141 publications

The Impact of Trust on the Willingness of Co-Tenancy Behavior: Evidence from China

The Impact of Trust on the Willingness of Co-Tenancy Behavior: Evidence from China

Towards a Hybrid Machine Learning Model for Intelligent Cyber Threat Identification in Smart City Environments

The financial impacts of information systems security breaches on publicly traded companies: reactions of different sectors

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