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International Journal of Information Security and Privacy is a peer-reviewed journal published by Taylor & Francis, covering Network Security and Intrusion Detection, Advanced Malware Detection Techniques, Cryptography and Data Security.
| Publisher | Taylor & Francis |
|---|---|
| Reference style | Author–year (Chicago, T&F) Author–year — (Smith, 2023) in the text Smith, Ada, Ben Jones, and Cara Lee. 2023. "A Representative Article Title." International Journal of Information Security and Privacy 12 (3): 45–58.
Formats any DOI in International Journal of Information Security and Privacy style. No sign-up. |
| Publishes research in | Network Security and Intrusion Detection Advanced Malware Detection Techniques Cryptography and Data Security Privacy-Preserving Technologies in Data Privacy, Security, and Data Protection |
| ISSN | 1930-1650 |
| Citation impact (2-yr) | 2.12 |
| h-index | 25 |
| i10-index | 86 |
| Total citations | 3,254 |
| Top institutions publishing here | Jaypee University of Information Technology |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
We present a publicly available, OWL-based ontology of information security which models assets, threats, vulnerabilities, countermeasures and their relations. The ontology can be used as a general vocabulary, roadmap, and extensible dictionary of the domain of information security. With its help, users can agree on a common language and definition of terms and relationships. In…
In this paper, the authors discuss security issues for cloud computing and present a layered framework for secure clouds and then focus on two of the layers, i.e., the storage layer and the data layer. In particular, the authors discuss a scheme for secure third party publications of documents in a cloud. Next, the paper…
IoT devices generate enormous amounts of data, which deep learning algorithms can learn from more effectively than shallow learning algorithms. The approach for threat detection may ultimately benefit fog computing or fog networking (fogging). The authors present a cutting-edge distributed DL method for detecting cyberattacks and vulnerability injection (CAVID) in this paper. In terms of…
The identity of patients must be protected when patient data are shared. The two most commonly used models to protect identity of patients are L-diversity and K-anonymity. However, existing work mainly considers data sets with a single sensitive attribute, while patient data often contain multiple sensitive attributes (e.g., diagnosis and treatment). This article shows that…
The purpose of this study is to identify the factors that impact on the behavioral intention of the Indian consumers to use devices embedded with the internet of things (IoT). While identifying the factors, due attention has been given on the security and privacy issues. With the inputs from the studies of available literature and…
