Threat modeling in smart firefighting systems: Aligning MITRE ATT&amp;CK matrix and NIST security controls

Zahid, Shahzaib; Mazhar, Muhammad Shoaib; Hanif, Zahid; Hina, Sadaf; Shah, Ghalib A.

doi:10.1016/j.iot.2023.100766

Cited by 17 publications

(8 citation statements)

References 27 publications

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“…As part of the complete assessment of the threat model analysis, it prioritises threats and mitigation based on probabilities, impacts, and countermeasure costs. It evaluates all possible risks throughout the system rather than focusing only on the parts of the system that are expected to exhibit flaws [30].…”

Section: Threat Analysismentioning

confidence: 99%

Pixel Tampering Detection in Encrypted Surveillance Videos on Resource-Constrained Devices

Aribilola,

Lee,

Asghar

2024

Preprint

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Encryption (naïve/selective) is recommended to secure the recorded visual content; however, intruders can still manipulate encrypted data. Visually, tampering attacks on encrypted video pixels in selectively encrypted videos are difficult to identify. Thus, this paper presents a tampering detection system that performs vulnerability analysis for Regions-of-Interest (ROI) in encrypted videos. To detect the tampering attacks, we explored the pixels' intensities and proposed a new TampDetect algorithm. The TampDetect applies the Hue, Saturation, and Value (HSV) colour model to detect the encrypted areas in the video. These encrypted pixels are then segmented and selected from the non-encrypted pixels using a minimum and maximum HSV value and a global threshold. The mean intensity of the encrypted pixels is thus calculated and stored. The integrity of the video frame is then validated by comparing the stored mean intensity with the newly calculated mean intensity to validate tampering/attack. The experiments were conducted on an Intel NUC, and its low computational cost demonstrates the lightweight nature of the proposed TampDetect algorithm for detecting tampering in ROI encrypted videos. The developed dataset for experiments, i.e., original, ROI encrypted, and tampered videos (encrypted/decrypted) is made available on kaggle-repository for future researchers.

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Section: Threat Analysismentioning

confidence: 99%

Pixel Tampering Detection in Encrypted Surveillance Videos on Resource-Constrained Devices

Aribilola,

Lee,

Asghar

2024

Preprint

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“…It not only safeguards against denial-of-service attacks but also contributes to energy conservation and extends the network's lifespan [122]. Several measures must be implemented to maintain the availability of M2M systems in the face of potential security threats and vulnerabilities [123].…”

Section: ) Availabilitymentioning

confidence: 99%

Investigations in Security Challenges and Solutions for M2M Communications—A Review

Manikandan

2024

IJEETC

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The Internet of Things (IoT) is becoming increasingly popular, and machine-to-machine (M2M) technology is one of its major components. Reducing human interaction and tasks is one of the most important justifications for research in M2M communication. Also, M2M technology decreases network traffic, improving network effectiveness. In contrast, multiple networks are combined into M2M networks, which leads to security-related design concerns. However, a significant barrier to its growth is security. According to statistics, new gadgets may come under attack five minutes after they connect to the Internet. If these issues are resolved, it will be easier for people to trust this worldview. Security issues with possible solutions have gotten little attention despite extensive M2M studies. This article provides a comprehensive security analysis of M2M communication technologies, exploring the risks and solutions to better comprehend M2M communication and its security implications.

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“…We have only included studies (including technical articles and excluding review-type articles) focused on both areas. Table 7 summarizes the methodologies and results of the applications [115][116][117][118][119][120][121][122][123][124][125][126][127].…”

Section: Recent Cps and Iot Applicationsmentioning

confidence: 99%

“…The network traffic load was increased by seven times [116] Attack detection and mitigation using a threat modeling framework…”

Section: Applicationsmentioning

confidence: 99%

A Survey of Internet of Things and Cyber-Physical Systems: Standards, Algorithms, Applications, Security, Challenges, and Future Directions

Chui¹,

Gupta

Liu³

et al. 2023

Information

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The smart city vision has driven the rapid development and advancement of interconnected technologies using the Internet of Things (IoT) and cyber-physical systems (CPS). In this paper, various aspects of IoT and CPS in recent years (from 2013 to May 2023) are surveyed. It first begins with industry standards which ensure cost-effective solutions and interoperability. With ever-growing big data, tremendous undiscovered knowledge can be mined to be transformed into useful applications. Machine learning algorithms are taking the lead to achieve various target applications with formulations such as classification, clustering, regression, prediction, and anomaly detection. Notably, attention has shifted from traditional machine learning algorithms to advanced algorithms, including deep learning, transfer learning, and data generation algorithms, to provide more accurate models. In recent years, there has been an increasing need for advanced security techniques and defense strategies to detect and prevent the IoT and CPS from being attacked. Research challenges and future directions are summarized. We hope that more researchers can conduct more studies on the IoT and on CPS.

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Threat modeling in smart firefighting systems: Aligning MITRE ATT&CK matrix and NIST security controls

Cited by 17 publications

References 27 publications

Pixel Tampering Detection in Encrypted Surveillance Videos on Resource-Constrained Devices

Pixel Tampering Detection in Encrypted Surveillance Videos on Resource-Constrained Devices

Investigations in Security Challenges and Solutions for M2M Communications—A Review

A Survey of Internet of Things and Cyber-Physical Systems: Standards, Algorithms, Applications, Security, Challenges, and Future Directions

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