Selection and Configuration Optimization for Customizable Cloud Services

Zhang, Hongxia; Wang, Fei; Xu, Jiuyun; Guo, Jianchun

doi:10.14257/ijsip.2016.9.4.39

Cited by 1 publication

(1 citation statement)

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“…Therefore, internet of things (IoT) infrastructure can be lightweight using NFV technology. A system using NFV technology utilizes resources dynamically and efficiently to satisfy users in virtualized space [3,4]. This advantage allows cloud services to combine microservices to create additional services.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Application Protection Mechanism for Transportation in V2C Environment

et al. 2020

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The emergence of vehicle-to-cloud (V2C) technology is changing cloud computing and transportation ecosystems. V2C technology enables the development of smart services, such as driving assistance and vehicle maintenance, that transmit information to the driver. Recent studies have primarily focused on services. To date, there has not been sufficient research on security functions to detect abnormal behaviors on virtual application. If an abnormal behavior occurs in the application, the service not only notices the wrong information to driver, but also affects the transportation system around the vehicle. To defend against distributed denial of service (DDoS) attacks, system resources should be monitored constantly. However, continuous monitoring is difficult because V2C services change dynamically according to the service environment. In addition, rule-based or supervised monitoring is impossible for each of the numerous services provided by a cloud computing center. In this paper, we propose an intelligent application protection mechanism for smart vehicle services in a V2C environment that detects abnormal behavior through image-based system resource monitoring using artificial intelligence (ISRM-AI) to improve cloud vehicle service security. The ISRM-AI generates images about system information such as CPU, network, memory on V2C cloud services. Also, the mechanism analyzes the status using a convolutional neural network (CNN) to detect abnormal behavior of the each services. We constructed a service environment to test the performance of the proposed mechanism. In addition, we simulated the proposed mechanism's ability to detect DDoS attacks using real attack data. The proposed mechanism guarantees the reliability of a smart service by enhancing the security of the V2C environment.

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Section: Introductionmentioning

confidence: 99%