Perceived security and privacy of cloud computing applications used in educational ecosystem

2017 ◽  
Author(s):  
Tihomir Orehovacki ◽  
Darko Etinger ◽  
Snjezana Babic
Keyword(s):  
Cloud Computing ◽  
Security And Privacy ◽  
Perceived Security

Issues in security and privacy of big data

2018 ◽  
Vol 7 (12) ◽  
pp. 1
Author(s):  
Shaveta Bhatia
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Approximate Method ◽  
Biomedical Research ◽  
Cyber Security ◽  
Data Science ◽  
Third Party ◽  
Security And Privacy ◽  
Security Threats ◽  
The Third

 The epoch of the big data presents many opportunities for the development in the range of data science, biomedical research cyber security, and cloud computing. Nowadays the big data gained popularity.  It also invites many provocations and upshot in the security and privacy of the big data. There are various type of threats, attacks such as leakage of data, the third party tries to access, viruses and vulnerability that stand against the security of the big data. This paper will discuss about the security threats and their approximate method in the field of biomedical research, cyber security and cloud computing.

Cloud computing security and privacy: Standards and regulations

2017 ◽  
Vol 54 ◽  
pp. 1-2 ◽  
Author(s):  
Yong Yu ◽  
Atsuko Miyaji ◽  
Man Ho Au ◽  
Willy Susilo
Keyword(s):  
Cloud Computing ◽  
Security And Privacy ◽  
Cloud Computing Security ◽  
Standards And Regulations

scholarly journals Data Security and Privacy in Cloud Computing

2014 ◽  
Vol 10 (7) ◽  
pp. 190903 ◽  
Author(s):  
Yunchuan Sun ◽  
Junsheng Zhang ◽  
Yongping Xiong ◽  
Guangyu Zhu
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Security And Privacy

Users’ attitude on perceived security of enterprise systems mobility: an empirical study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ramaraj Palanisamy ◽  
Yang Wu
Keyword(s):  
Cloud Computing ◽  
Best Practices ◽  
Empirical Study ◽  
Mobile Systems ◽  
Mobile Technologies ◽  
Content Type ◽  
Security Issues ◽  
Study Results ◽  
Perceived Security ◽  
High Level

Purpose This study/ paper aims to empirically examine the user attitude on perceived security of enterprise systems (ES) mobility. Organizations are adopting mobile technologies for various business applications including ES to increase the flexibility and to gain sustainable competitive advantage. At the same time, end-users are exposed to security issues when using mobile technologies. The ES have seen breaches and malicious intrusions thereby more sophisticated recreational and commercial cybercrimes have been witnessed. ES have seen data breaches and malicious intrusions leading to more sophisticated cybercrimes. Considering the significance of security in ES mobility, the research questions in this study are: What are the security issues of ES mobility? What are the influences of users’ attitude towards those security issues? What is the impact of users’ attitude towards security issues on perceived security of ES mobility? Design/methodology/approach These questions are addressed by empirically testing a security model of mobile ES by collecting data from users of ES mobile systems. Hypotheses were evolved and tested by data collected through a survey questionnaire. The questionnaire survey was administered to 331 users from Chinese small and medium-sized enterprises (SME). The data was statistically analysed by tools such as correlation, factor analysis, regression and the study built a structural equation model (SEM) to examine the interactions between the variables. Findings The study results have identified the following security issues: users’ attitude towards mobile device security issues; users’ attitude towards wireless network security issues; users’ attitude towards cloud computing security issues; users’ attitude towards application-level security issues; users’ attitude towards data (access) level security issues; and users’ attitude towards enterprise-level security issues. Research limitations/implications The study results are based on a sample of users from Chinese SMEs. The findings may lack generalizability. Therefore, researchers are encouraged to examine the model in a different context. The issues requiring further investigation are the role of gender and type of device on perceived security of ES mobile systems. Practical implications The results show that the key security issues are related to a mobile device, wireless network, cloud computing, applications, data and enterprise. By understanding these issues and the best practices, organizations can maintain a high level of security of their mobile ES. Social implications Apart from understanding the best practices and the key issues, the authors suggest management and end-users to work collaboratively to achieve a high level of security of the mobile ES. Originality/value This is an empirical study conducted from the users’ perspective for validating the set of research hypotheses related to key security issues on the perceived security of mobile ES.

Proposed Back Propagation Deep Neural Network for Intrusion Detection in Internet of Things Fog Computing

2021 ◽  
Vol 9 (4) ◽  
pp. 464-469
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Fog Computing ◽  
Denial Of Service ◽  
Back Propagation ◽  
Security And Privacy ◽  
Brute Force ◽  
Iot Platform ◽  
Proposed Model

Internet of things (IoT) is an emerging concept which aims to connect billions of devices with each other anytime regardless of their location. Sadly, these IoT devices do not have enough computing resources to process huge amount of data. Therefore, Cloud computing is relied on to provide these resources. However, cloud computing based architecture fails in applications that demand very low and predictable latency, therefore the need for fog computing which is a new paradigm that is regarded as an extension of cloud computing to provide services between end users and the cloud user. Unfortunately, Fog-IoT is confronted with various security and privacy risks and prone to several cyberattacks which is a serious challenge. The purpose of this work is to present security and privacy threats towards Fog-IoT platform and discuss the security and privacy requirements in fog computing. We then proceed to propose an Intrusion Detection System (IDS) model using Standard Deep Neural Network's Back Propagation algorithm (BPDNN) to mitigate intrusions that attack Fog-IoT platform. The experimental Dataset for the proposed model is obtained from the Canadian Institute for Cybersecurity 2017 Dataset. Each instance of the attack in the dataset is separated into separate files, which are DoS (Denial of Service), DDoS (Distributed Denial of Service), Web Attack, Brute Force FTP, Brute Force SSH, Heartbleed, Infiltration and Botnet (Bot Network) Attack. The proposed model is trained using a 3-layer BP-DNN

scholarly journals Secure Data Aggregation Scheme for IOT Applications in Cloud

2020 ◽  
Vol 9 (4S2) ◽  
pp. 70-76
Keyword(s):  
Cloud Computing ◽  
Data Hiding ◽  
Data Aggregation ◽  
Dynamic Network ◽  
Security And Privacy ◽  
Iot Applications ◽  
P Gene ◽  
Private Data ◽  
Aggregation Scheme ◽  
And Storage

While Internet of Things (IoT) technology comprises of nodes that are self-configuring and intelligent which are interconnected in a dynamic network, utilization of shared resources has been revolutionized by the cloud computing effectively reducing the cost overheadamong the cloud users.The major concerns of IoT infrastructure are reliability, performance, security and privacy. Cloud computing is popular for its unlimited storage and processing power. Cloud computing is much more matured with the capability to resolve most of the issues in IoT technology. A suitable way to address most of the issues in IoT technology is by integrating IoTparadigm into the Cloud technology.In this regard, we propose a methodology of applying our EPAS scheme for IoT applications. In our previous work[2] , we have proposed an Enhanced Privacy preserving gene based data Aggregation Scheme (EPAS) for private data transmission and storage by utilizing Enhanced P-Gene erasable data hiding approach. Enhanced P-Gene scheme ensures secure transmission and storage of private data by relying on a data aggregation scheme fully dependent on erasable data hiding technique. In the current work we analyse the applicability of the EPAS scheme for IoT applications. Experimental results show the suitability of the proposed scheme for application involving numeric data and also demonstrates performance improvement with existing proposals for data aggregation in cloud.

scholarly journals An Examination on Cloud Computing Future, Privacy of Data and Possibilities

2019 ◽  
Vol 8 (6S2) ◽  
pp. 949-953
Keyword(s):  
Cloud Computing ◽  
Theoretical Basis ◽  
The Other ◽  
Security And Privacy ◽  
Research Trend ◽  
Computing Environment ◽  
Storage Virtualization ◽  
Security Issues ◽  
The Core ◽  
New Research

Cloud computing is the theoretical basis for future computing. All the global frameworks are now looking up to architecture which is purely based on cloud. Being the core of such a large web of network, it is important to consider the security aspects in a cloud based computing environment. This has resulted in a new research trend on the security issues of cloud. Cloud is a popular paradigm with extreme abilities and benefits for trending ICT environment. On the other end the major concern came in terms of security and privacy while adopting the cloud technology. This article is an effort to cover the challenges in fields like storage, virtualization and communication in cloud .Also it is a try to elaborate relevance of current cryptographic approach in order to increase security of cloud in ICT.

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