Security Testing of Internet of Things for Smart City Applications: A Formal Approach

Krichen, Moez; Lahami, Mariam; Cheikhrouhou, Omar; Alroobaea, Roobaea; Maâlej, Afef Jmal

doi:10.1007/978-3-030-13705-2_26

Cited by 39 publications

(26 citation statements)

References 28 publications

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“…Formal methods can be used to calculate whether a system description (specification) is inherently consistent, whether certain properties can be guaranteed, and whether the requirements have been properly designed and implemented (currently only theoretical). Furthermore, the specification can be used for simulation / animation, for code generation, for test generation and test evaluation [15]. The extra effort to describe something formally must have a justification.…”

Section: Formal Methodsmentioning

confidence: 99%

A Formal Approach To Validate Block-Chains

Alroobaea¹

2020

Preprint

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Our goal is to propose a suitable approach for validating blockchains. For this purpose, we intend to adopt formal methods which are based on strong mathematical foundations. More precisely, we follow a model-based testing approach. The latter consists in describing the behavior of the system using a speciﬁc formalism, deriving test cases from the obtained model and then executing the obtained tests on the implementation to check whether it is correct or not. The adopted formalism corresponds to the timed automaton Model. The generated tests may be either digital or analog. Moreover, we propose several techniques which allow to solve the state explosion which may be encountered during the veriﬁcation and test generation phases.

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Section: Formal Methodsmentioning

confidence: 99%

A Formal Approach To Validate Block-Chains

Alroobaea¹

2020

Preprint

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“…Every attribute of a network is given a weight (0 < wj < 1) which indicates its priority or importance. Si is the measure of group utility [20] i.e., the sum of weighted normalizations of entire attributes in a certain network.…”

Section: Steps Involvedmentioning

confidence: 99%

Multi-Criteria Fuzzy-Based Decision Making Algorithm to Optimize the VHO Performance in Hetnets

Prithiviraj¹,

Maheswari²,

Balamurugan³

et al. 2022

Computers, Materials &Amp; Continua

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Despite the seemingly exponential growth of mobile and wireless communication, this same technology aims to offer uninterrupted access to different wireless systems like Radio Communication, Bluetooth, and Wi-Fi to achieve better network connection which in turn gives the best quality of service (QoS). Many analysts have established many handover decision systems (HDS) to enable assured continuous mobility between various radio access technologies. Unbroken mobility is one of the most significant problems considered in wireless communication networks. Each application needs a distinct QoS, so the network choice may shift appropriately. To achieve this objective and to choose the finest networks, it is important to select a best decision making algorithm that chooses the most effective network for every application that the user requires, dependent on QoS measures. Therefore, the main goal of the proposed system is to provide an enhanced vertical handover (VHO) decision making program by using a Multi-Criteria Fuzzy-Based algorithm to choose the best network. Enhanced Multi-Criteria algorithms and a Fuzzy-Based algorithm is implemented successfully for optimal network selection and also to minimize the probability of false handover. Furthermore, a double packet buffer is utilized to decrease the packet loss by 1.5% and to reduce the number of handovers up to 50% compared to the existing systems. In addition, the network setup has an optimized mobility management system to supervise the movement of the mobile nodes.

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“…Researchers are trying to come across different approaches, techniques, and mechanisms for overcoming various perspectives of smart cities' security. Krichen et al [13] followed an approach of the model based on consisting of modelling the system with suitable formalism, derivation of suites from the model, applied criteria of convergence for selection of appropriate tests, execution of the tests, and lastly collection of verdicts and their analysis for detection of errors and debug them. e formalism adopted was based on the model of extended timed automata with inputs and outputs.…”

Section: Related Workmentioning

confidence: 99%

Acquiring Data Traffic for Sustainable IoT and Smart Devices Using Machine Learning Algorithm

Nazir

et al. 2021

Security and Communication Networks

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Billions of devices are connected via the Internet which has produced various challenges and opportunities. The increase in the number of devices connected to the Internet of things (IoT) is nearly beyond imagination. These devices are communicating with each other and facilitating human life. The connection of these devices has provided opening directions for the smart applications which are one of the growing areas of research. Among these opportunities, security and privacy are considered to be one of the major issues for researchers to tackle. Proper security measures can prevent attackers from interrupting the security of IoT network inside the smart city for secure data traffic. Keeping in view the security consideration of data traffic for smart devices and IoT, the proposed study presented machine learning algorithms for securing the data traffic based on a firewall for smart devices and IoT network. The study has used the dataset of “Firewall” for validation purposes. The experimental results of the approach show that the hybrid deep learning model (based on convolution neural network and support vector machine) outperforms than decision1 rules and random forest by generating a recognition rate of 95.5% for the hybrid model, 68.5% for decision rules, and 78.3% accuracy for random forest. The validity of the proposed model is also tested based on other performance metrics such as f score, error rate, recall, and precision. This high accuracy rate and other performance values show the applicability of the proposed hybrid model to secure data traffic purposes in smart devices. This can be used in many research areas of the smart city for security purposes.

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Security Testing of Internet of Things for Smart City Applications: A Formal Approach

Cited by 39 publications

References 28 publications

A Formal Approach To Validate Block-Chains

A Formal Approach To Validate Block-Chains

Multi-Criteria Fuzzy-Based Decision Making Algorithm to Optimize the VHO Performance in Hetnets

Acquiring Data Traffic for Sustainable IoT and Smart Devices Using Machine Learning Algorithm

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