Security Attacks in Internet of Things

Nair, Rajit; Sharma, Preeti; Singh, Dileep Kumar

doi:10.1002/9781119670087.ch14

Cited by 6 publications

(2 citation statements)

References 37 publications

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“…To mitigate these attacks, the devices should be designed such that they are physically secure in nature [37]. This includes the secure design of the data acquisition unit, radio frequency circuits, and chip selection.…”

Section: A Physical Layermentioning

confidence: 99%

Security Analysis of a Digital Twin Framework Using Probabilistic Model Checking

et al. 2023

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Digital Twins (DTs) have been gaining popularity in various applications, such as smart manufacturing, smart energy, smart mobility, and smart healthcare. In simple terms, DT is described as a virtual replica of a given physical product, system, or process. It consists of three major segments: the physical entity, its virtual counterpart, and the connections between them. While the data is collected from a physical entity, processed at the virtual layer, and accessed in the form of a DT at the application layer, it is exposed to several security risks. To ensure the applicability of a DT system, it is imperative to understand these security risks and their implications. However, there is a lack of a framework that can be used to assess the security of a DT. This paper presents a framework in which the security of a DT can be analyzed with the help of a formal verification technique. The framework captures the defense of the system at different layers and considers various attacks at each layer. The security of the DT system is represented as a statetransition system and the security properties are captured in temporal logic. Probabilistic model checking (PMC) is used to verify the systems against these properties. In particular, the framework is used to analyze the probability of success and the cost of various potential attacks that can occur at each layer in a DT system. The applicability of the proposed framework is demonstrated with the help of a detailed case study in the healthcare domain.INDEX TERMS Digital twin security, security analysis, probabilistic model checking, Markov decision process, discrete time Markov chain.

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Section: A Physical Layermentioning

confidence: 99%

Security Analysis of a Digital Twin Framework Using Probabilistic Model Checking

et al. 2023

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“…As a result, the authentication must be contained within the devices, with the ability to change the credentials as needed. Cryptography primitives: The IoT systems involve crucial phenomena such as encrypting data that is shared with a private key among users and unlocking the data using advanced computer techniques. The data transmitted by IoT devices is subject to assaults, which might occur between devices, via the internet, or in the cloud 23 . To guarantee safe and secure data transport, IoT devices must include industry compliant standard encryption libraries.…”

Section: Challenges Of Iot Device Securitymentioning

confidence: 99%

An optimum security enabled System‐on‐Chip selection for Internet of Things applications using genetic algorithm modeling

Krishnamoorthy

Kalimuthu

2021

Concurrency and Computation

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Summary The System‐on‐Chip (SoC) is the core component in embedded systems that push toward the evolution of the Internet of Things. The quick growth of embedded SoC devices has a substantial influence to overcome security issues in embedded system design. Since microcontroller‐based systems are security and safety‐critical, this article focuses on security aspects of state‐of‐the‐art microcontrollers through performing design space analysis of several crypto‐core algorithms. These crypto functions are analyzed and compared to identify and implement the appropriate algorithm for on‐chip security. The genetic algorithm (GA) optimization model is utilized for the optimal selection of secured SoC from the commercial devices that are stored in the database. In this work, the fitness function is proposed with various levels such as performance‐centric, security enabled, low operating power, and application‐specific SoC selection. We also validate the GA results by implementing the security benchmarks on resultant devices by analyzing the execution time and performance. The accuracy of the GA‐based optimum SoC selection is estimated using confusion matrix method that produces the accuracy of 89.66%.

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Autonomic computing system: Threats, security issues and an efficient approach for self protection

Jain

Chitra

Batra

et al. 2023

Materials Today: Proceedings

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Security Attacks in Internet of Things

Cited by 6 publications

References 37 publications

Security Analysis of a Digital Twin Framework Using Probabilistic Model Checking

Security Analysis of a Digital Twin Framework Using Probabilistic Model Checking

An optimum security enabled System‐on‐Chip selection for Internet of Things applications using genetic algorithm modeling

Autonomic computing system: Threats, security issues and an efficient approach for self protection

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