Self-efficacy in Information Security: A Replication Study

Xue, Botong; Warkentin, Merrill; Mutchler, Leigh A.; Balozian, Puzant

doi:10.1080/08874417.2021.2015725

Cited by 10 publications

(7 citation statements)

References 42 publications

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“…This combination of theories is produced to expand these theories by illustrating the extent to which these theories can influence the behavior of human's behavior protecting the security of their data in the face of the needs and challenges of the digital world. The use of different study subjects in research not only supports the original model developed by a scholar but also releases the opportunity to further expand existing constructs in different contexts and situations (Xue et al, 2021).…”

Section: Discussionmentioning

confidence: 79%

Developing A Model for The Security of Malaysian Youth Privacy Data: MyPROTECT

Mamat,

Wan Mahmud,

Azlan

et al. 2023

IJARBSS

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The personal data safety of cyber users is a threat in today's digital world. The public knows that the Covid-19 pandemic has become a catalyst for the digital technology transformation in the history of human civilization. This article aspires to test a model created to examine the factors protecting the safety of Malaysian youth's data. The questionnaire is circulated online among young people aged 19 years to 30 years using multistage random sampling. A total of 535 respondents were selected from Putrajaya and Cyberjaya as a free trial spot area provided by the government. The instruments are developed based on 11 constructs attitude, subjective norms, behavioral control, intention, environment support, usefulness, ease of use, trust, treatment assessment, coping skills, and self-efficacy. The model was analyzed using Structural Equation Modeling with IBM-SPSS AMOS 27.0 software. This approach is employed to test the developed model yielded from several established theories such as the Theory of Planned Behavior (TPB), Decomposed Theory of Planned Behavior (DTPB), Protection Motivation Theory (PMT), and Social Cognitive Theory (SCT). The results of this study show that all constructs referred to as MyPROTECT achieved the goodness fit model for this study.

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Section: Discussionmentioning

confidence: 79%

Developing A Model for The Security of Malaysian Youth Privacy Data: MyPROTECT

Mamat,

Wan Mahmud,

Azlan

et al. 2023

IJARBSS

View full text Add to dashboard Cite

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“…The dynamics highlight the challenges posed by the nuanced nature of security regulations, their enforcement, and their impact on organizational efficiency. The detailed security guidelines, combined with lenient enforcement, allow for potential employee negligence, diminishing the policies' effectiveness (Chang and Lin, 2007;Xue et al, 2023).…”

Section: Previous Researchmentioning

confidence: 99%

“…Furthermore, the ORC framework integrates considerations about the general awareness of Information Security (IS) threats. Such awareness is posited to encourage a more proactive approach to compliance, as suggested by Myyry et al (2013) and Xue et al (2023). It also assesses whether compliance is perceived as a rewarding endeavor, thereby motivating active employee engagement.…”

Section: Construct Orcmentioning

confidence: 99%

“…In this high-stakes game, Compliance ceases to be just a bureaucratic requirement. It morphs into a proactive shield, a bulwark against the potentially catastrophic consequences of security lapses and oversights, as you find comfort of this idea in published research findings (Huang and Lin, 2023;Palanisamy et al, 2023;Xue et al, 2023 andIfinedo, 2022).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Organizational Determinants and Compliance Behavior to Shape Information Security Plan

Cavallari

2023

Acad. J. Interdiscip. Stud.

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In the advanced field of Information and Communication Technology (ICT) within modern corporate frameworks, the pressing issue of non-compliance becomes increasingly crucial. Achieving the ideal balance—where one fosters consistent employee commitment without resorting to overly harsh penalties for possible violations—presents a complex problem. Such a nuanced relationship calls for a synchronized coordination among the company’s underlying factors, the principles of the Information Security Plan (ISP), and overarching compliance mandates. As companies step into a period where digital environments are in constant flux, the importance of securing information systems rises to a critical level. Against this backdrop, compliance stands out as a vital component, functioning as a stringent safeguard in the ongoing mission to protect precious digital assets—a mission comprehensively detailed within the ISP. This in-depth academic study sets out to rigorously explore and scrutinize the diverse opinions and beliefs of committed employees and insightful management concerning unwavering company alignment with the ISP. This is accomplished by defining a construct that centers on key dimensions: Organizational Culture, Personal Attitudes, Actors, Behavioral Intentions, and Motivational Dynamics. Eleven Hypotheses are outlined and represent the materialisation of the model. This model form a starting point from which future empirical exploration will be able to take place, propelling us towards a deeper understanding of the phenomena under scrutiny. Received: 15 September 2023 / Accepted: 23 October 2023 / Published: 5 November 2023

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“…Lack of data, however, makes it challenging to use artificial intelligence models in the medical world due to privacy concerns [21,22]. Private data cannot be guaranteed to be secure using machine learning algorithms since it is so simple for attackers to steal or change information, whether on purpose or accidentally [23].…”

Section: Introductionmentioning

confidence: 99%

Chest Radiographs Based Pneumothorax Detection Using Federated Learning

Almadhor¹,

Khan²,

Wechtaisong³

et al. 2023

Computer Systems Science and Engineering

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Pneumothorax is a thoracic condition that occurs when a person's lungs collapse, causing air to enter the pleural cavity, the area close to the lungs and chest wall. The most persistent disease, as well as one that necessitates particular patient care and the privacy of their health records. The radiologists find it challenging to diagnose pneumothorax due to the variations in images. Deep learning-based techniques are commonly employed to solve image categorization and segmentation problems. However, it is challenging to employ it in the medical field due to privacy issues and a lack of data. To address this issue, a federated learning framework based on an Xception neural network model is proposed in this research. The pneumothorax medical image dataset is obtained from the Kaggle repository. Data preprocessing is performed on the used dataset to convert unstructured data into structured information to improve the model's performance. Min-max normalization technique is used to normalize the data, and the features are extracted from chest Xray images. Then dataset converts into two windows to make two clients for local model training. Xception neural network model is trained on the dataset individually and aggregates model updates from two clients on the server side. To decrease the over-fitting effect, every client analyses the results three times. Client 1 performed better in round 2 with a 79.0% accuracy, and client 2 performed better in round 2 with a 77.0% accuracy. The experimental result shows the effectiveness of the federated learning-based technique on a deep neural network, reaching a 79.28% accuracy while also providing privacy to the patient's data.

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Self-efficacy in Information Security: A Replication Study

Cited by 10 publications

References 42 publications

Developing A Model for The Security of Malaysian Youth Privacy Data: MyPROTECT

Developing A Model for The Security of Malaysian Youth Privacy Data: MyPROTECT

Organizational Determinants and Compliance Behavior to Shape Information Security Plan

Chest Radiographs Based Pneumothorax Detection Using Federated Learning

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