Computational intelligence intrusion detection techniques in mobile cloud computing environments: Review, taxonomy, and open research issues

2020 ◽  
Vol 55 ◽  
pp. 102582 ◽  
Author(s):  
Shahab Shamshirband ◽  
Mahdis Fathi ◽  
Anthony T. Chronopoulos ◽  
Antonio Montieri ◽  
Fabio Palumbo ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Intrusion Detection ◽  
Computational Intelligence ◽  
Mobile Cloud Computing ◽  
Mobile Cloud ◽  
Research Issues ◽  
Detection Techniques ◽  
Open Research ◽  
Computing Environments

scholarly journals Intrusion detection techniques for mobile cloud computing in heterogeneous 5G

2015 ◽  
Vol 9 (16) ◽  
pp. 3049-3058 ◽  
Author(s):  
Keke Gai ◽  
Meikang Qiu ◽  
Lixin Tao ◽  
Yongxin Zhu
Keyword(s):  
Cloud Computing ◽  
Intrusion Detection ◽  
Mobile Cloud Computing ◽  
Mobile Cloud ◽  
Detection Techniques

scholarly journals A Trust-Based Agent Learning Model for Service Composition in Mobile Cloud Computing Environments

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 34207-34226 ◽  
Author(s):  
Wenjuan Li ◽  
Jian Cao ◽  
Keyong Hu ◽  
Jie Xu ◽  
Rajkumar Buyya
Keyword(s):  
Cloud Computing ◽  
Service Composition ◽  
Mobile Cloud Computing ◽  
Learning Model ◽  
Mobile Cloud ◽  
Agent Learning ◽  
Computing Environments

scholarly journals Mobile Cloud Computing: Taxonomy and Challenges

2020 ◽  
Vol 2020 ◽  
pp. 1-23
Author(s):  
Ahmed Aliyu ◽  
Abdul Hanan Abdullah ◽  
Omprakash Kaiwartya ◽  
Syed Hamid Hussain Madni ◽  
Usman Mohammed Joda ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Mobile Cloud Computing ◽  
Cost Effective ◽  
Qualitative Assessment ◽  
The Internet ◽  
Mobile Cloud ◽  
Energy Aware ◽  
Research Issues ◽  
Delivery Platform ◽  
Cloud Users

Mobile cloud computing (MCC) holds a new dawn of computing, where the cloud users are attracted to multiple services through the Internet. MCC has a qualitative, flexible, and cost-effective delivery platform for providing services to mobile cloud users with the aid of the Internet. Due to the advantage of the delivery platform, several studies have been conducted on how to address different issues in MCC. The issues include energy efficiency in MCC, secured MCC, user-satisfied applications and Quality of Service-aware MCC (QoS). In this context, this paper qualitatively reviews different proposed MCC solutions. Therefore, taxonomy for MCC is presented considering major themes of research including energy-aware, security, applications, and QoS-aware developments. Each of these themes is critically investigated with comparative assessments considering recent advancements. Analysis of metrics and implementation environments used for evaluating the performance of existing techniques are presented. Finally, some open research issues and future challenges are identified based on the critical and qualitative assessment of literature for researchers in this field.

scholarly journals Context-Aware Cloud Service Selection Model for Mobile Cloud Computing Environments

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Xu Wu
Keyword(s):  
Cloud Computing ◽  
Mobile Cloud Computing ◽  
Service Selection ◽  
Cloud Service ◽  
Cloud Services ◽  
Mobile Cloud ◽  
Relational Degree ◽  
Computing Environments ◽  
Traditional Approaches ◽  
Trustworthy Service

Mobile cloud computing (MCC) has attracted extensive attention in recent years. With the prevalence of MCC, how to select trustworthy and high quality mobile cloud services becomes one of the most urgent problems. Therefore, this paper focuses on the trustworthy service selection and recommendation in mobile cloud computing environments. We propose a novel service selection and recommendation model (SSRM), where user similarity is calculated based on user context information and interest. In addition, the relational degree among services is calculated based on PropFlow algorithm and we utilize it to improve the accuracy of ranking results. SSRM supports a personalized and trusted selection of cloud services through taking into account mobile user’s trust expectation. Simulation experiments are conducted on ns3 simulator to study the prediction performance of SSRM compared with other two traditional approaches. The experimental results show the effectiveness of SSRM.

An Architecture for Providing Context-Aware Security as a Service in Mobile Cloud Computing Environments

2017 ◽  
Vol 23 (11) ◽  
pp. 11074-11077
Author(s):  
Muaamar Amer Alkubati ◽  
Syed Ahmad Aljunid ◽  
Normaly Kamal Ismail
Keyword(s):  
Cloud Computing ◽  
Mobile Cloud Computing ◽  
Mobile Cloud ◽  
Context Aware ◽  
Computing Environments ◽  
Security As A Service
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