Security Evaluation for Wireless Network Based on Fuzzy-AHP with Variable Weight

Zhang, Runfu; Huang, Lianfen; Xiao, M.

doi:10.1109/nswctc.2010.122

Cited by 9 publications

(4 citation statements)

References 2 publications

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“…The parameter

α

is essential for the emphasizing weighting amplifier and directly affects the amplification intensity. According to a previous study [44], positive, negative and constant

α

values represent encouraging, punishing and constant amplification, respectively. In our implementation, we retain the

S C

s with a low score value and disregard those with a high score value; then,

α

becomes negative.…”

Section: Methodsmentioning

confidence: 99%

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HiRAM: A hierarchical risk assessment model and its implementation for an industrial Internet of Things in the cloud

Sun

Tang

Huang

2023

Software Testing Verif & Rel

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The trend towards intelligent control processes has introduced the Internet of Things (IoT) and cloud computing technologies to factories. IoT devices can sense data and send it to a cloud for further analysis in a factory. Consequently, the quantity of such valuable data flowing in an industrial cyber‐physical system has gradually increased. Tailoring a risk assessment system for Industrial IoT (IIoT) is essential, particularly for a cloud platform that handles the IIoT data flow. In this study, we leverage analytic hierarchy processes (AHPs) and propose Hierarchical Risk Assessment Model (HiRAM) for an IIoT cloud platform. The proposed model allows the platform to self‐evaluate its security status. Furthermore, a modular and responsive Risk Assessment System based on HiRAM, called HiRAM‐RAS, is realized and evaluated in a real‐world IIoT cloud platform. We deploy HiRAM‐RAS to a sample application and introduce the practical deployment procedures. We then estimate the practicality of the HiRAM‐RAS by injecting different degrees of errors and launching Distributed denial‐of‐service (DDoS) attacks. The results demonstrate the changes in integrity and availability scores evaluated by HiRAM.

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“…The parameter

α

is essential for the emphasizing weighting amplifier and directly affects the amplification intensity. According to a previous study [44], positive, negative and constant

α

values represent encouraging, punishing and constant amplification, respectively. In our implementation, we retain the

S C

s with a low score value and disregard those with a high score value; then,

α

becomes negative.…”

Section: Methodsmentioning

confidence: 99%

“…Hence, we revise the aforementioned variable weighting calculation [44] and propose an emphasizing weighting amplifier to resolve the weighting‐dilution problem. A new weighting vector, called variable weighting vector

\overset{bold-italicω}{true} false(X false)

, is calculated with Equation (14).…”

Section: In‐practice Revisionsmentioning

confidence: 99%

HiRAM: A hierarchical risk assessment model and its implementation for an industrial Internet of Things in the cloud

Sun

Tang

Huang

2023

Software Testing Verif & Rel

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“…Expert opinion using the Delphi technique was used for pairwise comparisons. Finally, Zhang et al [58] used a combination of FAHP and variable weight Cyber Security Attacks, vulnerabilities, and penetration testing [30] Cyber Security Vulnerabilities, threats, users, protection mechanisms. encounters [31] Cyber Security Skills Soft skills, technical skills, certifications [32] System Security Controls Effectiveness, risk, budgetary constraints, exploitation, maintenance, mitigation time Information Security [33] Information Loss Security Human dependent, technical, random [34] Security Investments Confidentiality, data integrity, availability…”

Section: A Using Ahp To Assess Securitymentioning

confidence: 99%

“…[54] Security Level Agreements Compliance, data governance, information security Network Security [55] Network Security Assets, access control, communication [56] Smart Grid Security Smart terminal, wireless channel, password security, app. code, embedded system [57] Network Security Software, hardware, information, communication, organization, physical environment [58] Wireless Security Authenticity, availability, confidentiality, integrity, non-repudiation theory to assess wireless network security using the top-level criteria of authenticity, availability, confidentiality, and integrity. A case study suggested that the FAHP variableweight technique for assessing wireless network security was both efficient and practical.…”

Section: A Using Ahp To Assess Securitymentioning

confidence: 99%

Ranking Security of IoT-Based Smart Home Consumer Devices

AlLifah

Zualkernan

2022

IEEE Access

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Smart home consumer devices like home theatres, music players, voice-based assistants, smart lighting, and security cameras have widely adopted the Internet of Things (IoT). These devices pose a significant security risk to consumers because the devices are exposed to mobile applications and cloud-based services with known security vulnerabilities. IoT technologies also introduce additional vulnerabilities specific to smart home architectures. Most current home consumer devices provide little or no information about the level of security they afford. Since most consumers are not tech-savvy, it is currently difficult for a consumer to make an informed decision about which consumer device model (e.g., which smart television model?) has the best security. Hence, consumers need an objective security ranking of each type (e.g., security cameras) of home consumer devices. This paper proposes a novel methodology to systematically build such security rankings for home consumer devices. The proposed methodology can be applied by utilizing data from any security assessment study. The paper discusses previous efforts in applying Analytic Hierarchy Process (AHP) to rank security risks in general. The paper also presents a systematic survey of security vulnerabilities of smart home consumer devices when viewed from an IoT lens. Using the proposed methodology, a case study where an AHP model for ranking commonly used home consumer devices including home theatres, security cameras, smart lighting, smart speakers, video surveillance, smart switches, home automation systems, home security systems, smart routers, wireless doorbell cameras, and home audio systems, was developed. Relative security rankings for each type of consumer device were derived from the AHP model. According to the AHP model, network security was the primary driver of smart home device security with a priority of 0.6893 while application security had the least priority of 0.0591. Critical Vulnerabilities were the most important for device security (priority=0.4397), Man-in-The-Middle attacks for network security (priority=0.2019), exploitable services for cloud security (priority=0.26), and sensitive data for application security (0.7626). The AHP model was internally consistent (Consistency Ratio < 0.1). Sensitivity analysis showed that the AHP model was robust against pairing assumptions.INDEX TERMS AHP, consumer applications, cloud computing, home consumer devices, Internet of Things, network security, smart home.

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Security Evaluation for Wireless Sensor Networks Based on Attack Test and Fuzzy Comprehensive Judgement

Zhang

et al. 2014

Advanced Technologies in Ad Hoc and Sensor Networks

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Security Evaluation for Wireless Network Based on Fuzzy-AHP with Variable Weight

Cited by 9 publications

References 2 publications

HiRAM: A hierarchical risk assessment model and its implementation for an industrial Internet of Things in the cloud

HiRAM: A hierarchical risk assessment model and its implementation for an industrial Internet of Things in the cloud

Ranking Security of IoT-Based Smart Home Consumer Devices

Security Evaluation for Wireless Sensor Networks Based on Attack Test and Fuzzy Comprehensive Judgement

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