Cloud Computing Security Issues of Sensitive Data

Walia, Manpreet Kaur; Halgamuge, Malka N.; Hettikankanamage, Nadeesha D.; Bellamy, Craig

doi:10.4018/978-1-5225-7335-7.ch004

Cited by 5 publications

(3 citation statements)

References 17 publications

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“…This research, based on a comprehensive review of cloud insecurities [16], aims to develop, test, and validate a prototype framework for Information Flow Tracking (IFT) in cloud environments. As such, this work seeks to enhance transparency and control over data propagation, thereby bolstering client trust in the security and privacy of their data.…”

Section: Objectivesmentioning

confidence: 99%

Cloud Security Using Fine-Grained Efficient Information Flow Tracking

Alqahtani,

Almutairi,

Sheldon

2024

Future Internet

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This study provides a comprehensive review and comparative analysis of existing Information Flow Tracking (IFT) tools which underscores the imperative for mitigating data leakage in complex cloud systems. Traditional methods impose significant overhead on Cloud Service Providers (CSPs) and management activities, prompting the exploration of alternatives such as IFT. By augmenting consumer data subsets with security tags and deploying a network of monitors, IFT facilitates the detection and prevention of data leaks among cloud tenants. The research here has focused on preventing misuse, such as the exfiltration and/or extrusion of sensitive data in the cloud as well as the role of anonymization. The CloudMonitor framework was envisioned and developed to study and design mechanisms for transparent and efficient IFT (eIFT). The framework enables the experimentation, analysis, and validation of innovative methods for providing greater control to cloud service consumers (CSCs) over their data. Moreover, eIFT enables enhanced visibility to assess data conveyances by third-party services toward avoiding security risks (e.g., data exfiltration). Our implementation and validation of the framework uses both a centralized and dynamic IFT approach to achieve these goals. We measured the balance between dynamism and granularity of the data being tracked versus efficiency. To establish a security and performance baseline for better defense in depth, this work focuses primarily on unique Dynamic IFT tracking capabilities using e.g., Infrastructure as a Service (IaaS). Consumers and service providers can negotiate specific security enforcement standards using our framework. Thus, this study orchestrates and assesses, using a series of real-world experiments, how distinct monitoring capabilities combine to provide a comparatively higher level of security. Input/output performance was evaluated for execution time and resource utilization using several experiments. The results show that the performance is unaffected by the magnitude of the input/output data that is tracked. In other words, as the volume of data increases, we notice that the execution time grows linearly. However, this increase occurs at a rate that is notably slower than what would be anticipated in a strictly proportional relationship. The system achieves an average CPU and memory consumption overhead profile of 8% and 37% while completing less than one second for all of the validation test runs. The results establish a performance efficiency baseline for a better measure and understanding of the cost of preserving confidentiality, integrity, and availability (CIA) for cloud Consumers and Providers (C&P). Consumers can scrutinize the benefits (i.e., security) and tradeoffs (memory usage, bandwidth, CPU usage, and throughput) and the cost of ensuring CIA can be established, monitored, and controlled. This work provides the primary use-cases, formula for enforcing the rules of data isolation, data tracking policy framework, and the basis for managing confidential data flow and data leak prevention using the CloudMonitor framework.

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Section: Objectivesmentioning

confidence: 99%

Cloud Security Using Fine-Grained Efficient Information Flow Tracking

Alqahtani,

Almutairi,

Sheldon

2024

Future Internet

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“…However, although the characteristics of cloud computing bring great convenience to tenants, they pose a serious threat to the security of tenants' sensitive data [2]. The cloud platform has the following characteristics [3,4]:…”

Section: Introductionmentioning

confidence: 99%

“…This method can realize self-control of tenant information flow within the boundary as well as dynamic control and security sharing of information flow between tenants. 4. Based on the effective identification of the tenant virtual boundary and the dynamic control method of tenant information flow, we provide a detailed design of the dynamic security control application system of cloud tenants' sensitive information flow.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Control Method for Tenants’ Sensitive Information Flow Based on Virtual Boundary Recognition

Lu¹,

Cao²,

Du³

2020

IEEE Access

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In the cloud environment, owing to the large-scale sharing of the upper application instance and the underlying virtual machine resources, the tenants' information flow boundary in the shared virtual machine is fuzzy and difficult to identify. In addition, protection of tenant information flow between processes is inadequate, resulting in the leakage of sensitive information of tenants. Therefore, a dynamic control method for tenants' sensitive information flow based on virtual boundary recognition is proposed. By analyzing the behavior and operation log of tenants, the behavior feature vectors of tenants are constructed, and an automatic recognition algorithm of tenant virtual boundary based on the dynamic spiking neural network is designed. This algorithm can realize dynamic identification of the tenant virtual security boundary when the application service demand changes dynamically. Further, combined with the concept of centralized and decentralized information flow control, a dynamic control method of sensitive information flow is established. The security label is formally defined by using the lattice structure, and the control rules of tenants' information flow and the rules of tenant label encryption-declassification are designed. Thus, the independent, dynamic and secure control of tenants' information flow inside and outside the tenant virtual boundary. Finally, the detailed design of a dynamic security control application system for cloud tenants' sensitive information flow is provided. Experiments confirm that the proposed algorithm can identify the security boundary of tenants more accurately and efficiently than the traditional spiking neural network classification methods. Further, the security and effectiveness of the method is verified by the intransitive noninterference theory and the experiment of information flow control.

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What Are Cloud Business Concerns?

2021

Cloud Technologies

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Cloud Computing Security Issues of Sensitive Data

Cited by 5 publications

References 17 publications

Cloud Security Using Fine-Grained Efficient Information Flow Tracking

Cloud Security Using Fine-Grained Efficient Information Flow Tracking

Dynamic Control Method for Tenants’ Sensitive Information Flow Based on Virtual Boundary Recognition

What Are Cloud Business Concerns?

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