Threat Modeling for Cloud Infrastructures

Alhebaishi, Nawaf; Wang, Lingyu; Singhal, Anoop

doi:10.4108/eai.10-1-2019.156246

Cited by 7 publications

(17 citation statements)

References 35 publications

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“…Though the above questions have not been addressed by existing studies, there have instead been varying opinions regarding effective threat modelling methods for cloud computing [6], [14], [26]- [29]. Additionally, threat modeling methods are being used in their isolated ways in threat modeling healthcare systems.…”

Section: Scope Research Problem and Contributionmentioning

confidence: 99%

“…Threat modeling is the use of methods to help in thinking, identifying and enumerating possible risks and threats [6], [14], [26]- [29]. Threat modelling also helps in the identification of the lack of security controls for mitigating risks [6], [14], [26]- [29].…”

Section: Healthcare Related Information Security Threats Threat Mmentioning

confidence: 99%

“…Various type of threat modelling which were identified in this study include Attack Tree (AT), Attack Graph (AG),Attack Surface (AS), Practical Threat Analysis (PTA) , Threat Model Framework for Personal Network (PN), STRIDE, Threat modeling in pervasive computing paradigm (TMP), [6], [14], [26]- [29], [50] and LINDDUN (Likability, Identifiability, Non-Repudiation, Detectability, Disclosure of Information, Unawareness and Non-Compliance) [30] as defined below:…”

Section: Healthcare Related Information Security Threats Threat Mmentioning

confidence: 99%

“…Attack trees provide a structured way of describing [10] threats and vulnerabilities of a system, with regards to varying attacks and shows the possible attack paths which attackers can follow to be able to compromise the system [26].The attacks are represented against the system in the form of a tree. The goals are placed as root nodes while the leaves nodes represent the different ways of achieving the goals.…”

Section: Healthcare Related Information Security Threats Threat Mmentioning

confidence: 99%

“…Attack trees are widely used for security modelling and analysis in the cloud computing. The general steps involves in the attack tree include [26]:…”

Section: Healthcare Related Information Security Threats Threat Mmentioning

confidence: 99%

See 4 more Smart Citations

Comparative Analysis of Threat Modeling Methods for Cloud Computing towards Healthcare Security Practice

Yeng¹,

Wolthusen²,

Yang³

2020

IJACSA

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Healthcare organizations consist of unique activities including collaborating on patients care and emergency care. The sector also accumulates high sensitive multifaceted patients' data such as text reports, radiology images and pathological slides. The large volume of the data is often stored as Electronic Health Records (EHR) which must be frequently updated while ensuring higher percentage up-time for constant availability of patients' records. Healthcare as a critical infrastructure also needs highly skilled IT personnel, Information and Communication Technology (ICT) and infrastructure with regular maintenance culture. Fortunately, cloud computing can provide these necessary services at a lower cost. But with all thees enormous benefits of cloud computing, it is characterized with various information security issues which is not enticing to healthcare. Amid many threat modelling methods, which of them is suitable for identifying cloud related threats towards the adoption of cloud computing for healthcare? This paper compared threat modelling methods to determine their suitability for identifying and managing healthcare related threats in cloud computing. Threat modelling in pervasive computing (TMP) was identified to be suitable and can be combined with Attack Tree (AT), Attack Graph (AG) and Practical Threat Analysis (PTA) or STRIDE (spoofing, tampering, repudiation, information disclosure, denial of service and elevation of privilege). Also Attack Tree (AT) could be complemented with TMP, AG and STRIDE or PTA. Healthcare IT security professionals can hence rely on these methods in their security practices, to identify cloud related threats for healthcare. Essentially, privacy related threat modeling methods such as LINDDUN framework, need to be included in these synergy of cloud related threat modelling methods towards enhancing security and privacy for healthcare needs.

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Section: Scope Research Problem and Contributionmentioning

confidence: 99%

Section: Healthcare Related Information Security Threats Threat Mmentioning

confidence: 99%

Section: Healthcare Related Information Security Threats Threat Mmentioning

confidence: 99%

Section: Healthcare Related Information Security Threats Threat Mmentioning

confidence: 99%

“…Attack trees are widely used for security modelling and analysis in the cloud computing. The general steps involves in the attack tree include [26]:…”

Section: Healthcare Related Information Security Threats Threat Mmentioning

confidence: 99%

See 3 more Smart Citations

Comparative Analysis of Threat Modeling Methods for Cloud Computing towards Healthcare Security Practice

Yeng¹,

Wolthusen²,

Yang³

2020

IJACSA

View full text Add to dashboard Cite

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Data security techniques in cloud computing based on machine learning algorithms and cryptographic algorithms: Lightweight algorithms and genetics algorithms

Thabit

Can

Wani

et al. 2023

Concurrency and Computation

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SummaryCloud computing (CC) refers to the on‐demand availability of network resources, particularly data storage and processing power, without requiring special or direct administration by users. CC, which just made its debut as a collection of public and private data centers, provides clients with a unified platform throughout the Internet. Cloud computing has revolutionized the world, opening up new horizons with bright potential due to its performance, accessibility, low cost, and many other benefits. Due to the exponential rise of cloud computing, systems based on cloud computing now require an effective data security mechanism. Comprehensive security policies, corporate security culture, and cloud security solutions are used to ensure the level of cloud data security. Many techniques exist to protect data communication in the cloud environment, including encryption. Encryption algorithms play an important role in information security systems and various cloud computing‐based systems. Current researchers have focused on lightweight cryptography, genetics‐based cryptography, and machine learning (ML) algorithms for security in CC. This review study analyses CC security threats, problems, and solutions that use one or more algorithms. The work discusses several lightweight cryptographies, genetics‐based cryptography and different ML algorithms that are used to overcome cloud security issues, including supervised, unsupervised, semi‐supervised, and reinforcement learning. Moreover, we enlist future research directions to secure CC models.

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Modeling and Mitigating Security Threats in Network Functions Virtualization (NFV)

Alhebaishi¹,

Wang²,

Jajodia³

2020

Lecture Notes in Computer Science

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Threat Modeling for Cloud Infrastructures

Cited by 7 publications

References 35 publications

Comparative Analysis of Threat Modeling Methods for Cloud Computing towards Healthcare Security Practice

Comparative Analysis of Threat Modeling Methods for Cloud Computing towards Healthcare Security Practice

Data security techniques in cloud computing based on machine learning algorithms and cryptographic algorithms: Lightweight algorithms and genetics algorithms

Modeling and Mitigating Security Threats in Network Functions Virtualization (NFV)

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