Managing Intrusion Detection as a Service in Cloud Networks

Hamad, Hatem; Al-hoby, Mahmoud Omer Mohammed

doi:10.5120/5508-7533

Cited by 30 publications

(14 citation statements)

References 13 publications

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“…Arshad et al [85] proposed a model for intrusion detection with minimal human intervention and response time. Hamad et al [86] introduced intrusion detection system as a cloud service. Houmansadr et al [87] proposed a mobile phone-based intrusion detection system.…”

Section: Fog Computing Security Challengesmentioning

confidence: 99%

The Security of Big Data in Fog-Enabled IoT Applications Including Blockchain: A Survey

Tariq

Asim

Al-Obeidat

et al. 2019

Sensors

218

171

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The proliferation of inter-connected devices in critical industries, such as healthcare and power grid, is changing the perception of what constitutes critical infrastructure. The rising interconnectedness of new critical industries is driven by the growing demand for seamless access to information as the world becomes more mobile and connected and as the Internet of Things (IoT) grows. Critical industries are essential to the foundation of today’s society, and interruption of service in any of these sectors can reverberate through other sectors and even around the globe. In today’s hyper-connected world, the critical infrastructure is more vulnerable than ever to cyber threats, whether state sponsored, criminal groups or individuals. As the number of interconnected devices increases, the number of potential access points for hackers to disrupt critical infrastructure grows. This new attack surface emerges from fundamental changes in the critical infrastructure of organizations technology systems. This paper aims to improve understanding the challenges to secure future digital infrastructure while it is still evolving. After introducing the infrastructure generating big data, the functionality-based fog architecture is defined. In addition, a comprehensive review of security requirements in fog-enabled IoT systems is presented. Then, an in-depth analysis of the fog computing security challenges and big data privacy and trust concerns in relation to fog-enabled IoT are given. We also discuss blockchain as a key enabler to address many security related issues in IoT and consider closely the complementary interrelationships between blockchain and fog computing. In this context, this work formalizes the task of securing big data and its scope, provides a taxonomy to categories threats to fog-based IoT systems, presents a comprehensive comparison of state-of-the-art contributions in the field according to their security service and recommends promising research directions for future investigations.

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Section: Fog Computing Security Challengesmentioning

confidence: 99%

The Security of Big Data in Fog-Enabled IoT Applications Including Blockchain: A Survey

Tariq

Asim

Al-Obeidat

et al. 2019

Sensors

218

171

View full text Add to dashboard Cite

show abstract

“…Other proposals have addressed partial aspects of cloud security, such as an intrusion detection system for cloud computing environments offered as a service [ 22 ] or active monitoring schemes based on virtual machine introspection [ 23 ].…”

Section: Related Workmentioning

confidence: 99%

A Secure Multi-Tier Mobile Edge Computing Model for Data Processing Offloading Based on Degree of Trust

Gimeno

Mora

Marcos-Jorquera

et al. 2018

Sensors

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Current mobile devices need to run applications with high computational demands and critical response times. The mobile edge computing (MEC) paradigm was developed to improve the performance of these devices. This new computation architecture allows for the mobile devices to execute applications on fog nodes at the network edge; this process is called data processing offloading. This article presents a security model for the externalization of application execution in multi-tier MEC environments. The principal novelty of this study is that the model is able to modify the required security level in each tier of the distributed architecture as a function of the degree of trust associated with that tier. The basic idea is that a higher degree of trust requires a lower level of security, and vice versa. A formal framework is introduced that represents the general environment of application execution in distributed MEC architectures. An architecture is proposed that allows for deployment of the model in production environments and is implemented for evaluation purposes. The results show that the security model can be applied in multi-tier MEC architectures and that the model produces a minimal overhead, especially for computationally intensive applications.

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“…The work of Hamad and AI-Hoby [17] designed and implemented the Cloud Intrusion Detection Service (CIDS), which can be deployed by cloud providers to enable clients to subscribe with the IDS in a service-based manner, i.e. "Security-as-a-Service".…”

Section: Detecting Intrusions In the Cloud Environmentmentioning

confidence: 99%

Considering an elastic scaling model for cloud Security

MacDermott

Shi

Merabti

et al. 2013

8th International Conference for Internet Technology and Secured Transactions (ICITST-2013)

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Cloud computing usage is growing, and soon the vast majority of organisations will rely on some form of cloud computing services. Cloud computing is being adopted in critical sectors such as energy, transport and finance. This makes cloud computing services critical in themselves. When cyber-attacks and cyber disruptions happen, millions of users are affected. Infrastructure vendors will inevitably take advantage of the benefits offered by the cloud computing environment, but while this may offer improved performance and scalability, the associated security threats deter this progression. There needs to be an assurance that confidentiality, integrity and availability of the data and resources is maintained. This paper provides an overview to the cloud security conundrum, details existing intrusion detection methods, and presents our observation and proposed elastic scaling method for cloud security.

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Managing Intrusion Detection as a Service in Cloud Networks

Cited by 30 publications

References 13 publications

The Security of Big Data in Fog-Enabled IoT Applications Including Blockchain: A Survey

The Security of Big Data in Fog-Enabled IoT Applications Including Blockchain: A Survey

A Secure Multi-Tier Mobile Edge Computing Model for Data Processing Offloading Based on Degree of Trust

Considering an elastic scaling model for cloud Security

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