Data Encryption for Internet of Things Applications Based on Catalan Objects and Two Combinatorial Structures

Saračević, Muzafer; Adamović, Saša; Miškovic, Vladislav; Elhoseny, Mohamed; Maček, Nemanja; Selim, Mahmoud M.; Shankar, K.

doi:10.1109/tr.2020.3010973

Cited by 54 publications

(44 citation statements)

References 40 publications

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“…However, they did not tell the reasons in detail. (2) Some other factors also affect the RSUD problem. In [15], curve-shaped roads, a number of lanes, and nonuniform traffic statistics were taken into consideration by Gao et al They also considered some different RSUs with different radii in the RSUD problem [16].…”

Section: Related Workmentioning

confidence: 99%

“…The communication link between car A and R 2 1 is short such that the propagation delay is not taken into consideration. When the car A runs into the communication range of R 2 1 , it will transmit the message to R 2 1 . The transmission time t is:…”

Section: One Rsu In C 2mentioning

confidence: 99%

“…Car B running in the same direction as car A in C 1 1 , whether there is a RSU or not in C 1 1 . As shown in Figure 2, R 2 1 can't relay the packet to car B, because car B is not in the communication range of R 2 1 . There are no vehicles in C 2 1 , but we hope that the data packet can be transmitted from A before car A runs into C 1 1 ; the data packet needs to be sent to car B during the time t 1 :…”

Section: No Vehicles In C 2mentioning

confidence: 99%

“…As shown in Figure 3, there is no car in the same direction as Car A in the first half of C 1 1 in the driving direction. If car B arrives before time t 1 , it can receive the message from R 2 1 . Then the packet can be relayed by car B to R 0 1 on the premise that continuous vehicles are heading in the same direction as B, or there is a car D that runs in the same direction as A on the road ahead.…”

Section: No Vehicles In C 2mentioning

confidence: 99%

“…Specifically, V2V communication technology is based on a Vehicular Ad Hoc Network (VANET). VANET, which is a vital part of the intelligent transportation system (ITS), can improve road safety and traffic efficiency using wireless communication technology, meanwhile providing various entertainment service information to enhance drivers' and passengers' experience while ensure data confidentiality, reliability, and integrity by the data encryption technique [2,3]. VANET, created by applying the principles of mobile ad hoc…”

Section: Introductionmentioning

confidence: 99%

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A Center-Rule-Based Neighborhood Search Algorithm for Roadside Units Deployment in Emergency Scenarios

Shi

et al. 2020

Mathematics

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Roadside Units Deployment (RSUD) is of great importance to smart transportation with the Internet of Things (IoT). It is believed to be not feasible for RSUD to cover and perceive the whole area due to the high installation and maintenance costs. The candidate locations set of RSUD may be huge for a future urban area with vehicle-to-everything (V2X) networks. Most of the previous studies tried to maximize the Roadside Units (RSU) coverage only and made few reports on emergency scenarios, such as accidents happening. We tried to find better candidate locations of RSUD in some grid road networks with equal length streets, and then chose some of these locations for final installation with a given budget to minimize the average reporting time of emergency messages in V2X networks. Firstly, we analyzed candidate locations of RSUD for different cases of RSUs and vehicles. Then we proposed a message dissemination model for RSUD with the V2X network, and a center-rule-based neighborhood search algorithm (CNSA for short). In this algorithm, we generated initial solutions with the center rule and then obtained better neighbor solutions. Numerical simulation results from small-scale urban streets showed that the proposed algorithm performs well on execution time. Simulation results with Veins and Simulation of Urban Mobility) (SUMO) verified the proposed model and CNSA for evaluating the RSUD scheme by distance instead of accident reporting time in urban areas with large-scale traffic flow.

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Section: Related Workmentioning

confidence: 99%

Section: One Rsu In C 2mentioning

confidence: 99%

Section: No Vehicles In C 2mentioning

confidence: 99%

Section: No Vehicles In C 2mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Center-Rule-Based Neighborhood Search Algorithm for Roadside Units Deployment in Emergency Scenarios

Shi

et al. 2020

Mathematics

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Internet of Things data management: A systematic literature review, vision, and future trends

Shirvanian

Shams

Rahmani

2022

Int J Communication

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The Internet of Things (IoT) is expected to connect devices with unique identifiers over a network to create an equilibrium system with high speeds and volumes of data while presenting an interoperability challenge. The IoT data management system is indispensable for attaining effective and efficient performance because IoT sensors generate and collect large amounts of data used to express large data sets. IoT data management has been analyzed from various perspectives in numerous studies. In this study, a Systematic Literature Review (SLR) method was used to investigate the various topics and key areas that have recently emerged in IoT data management. This study aims to classify and evaluate studies published between 2015 and 2021 in IoT data management. Therefore, the classification of studies includes five categories, data processing, data smartness application, data collection, data security, and data storage. Then, studies in each field are compared based on the proposed classification. Each study investigates novel findings, simulation/implementation, data set, application domain, experimental results, advantages, and disadvantages. In addition, the criteria for evaluating selected articles for each domain of IoT data management are examined. Big data accounts for the highest percentage of data processing fields in IoT data management, at 34%. In addition, fast data processing, distributed data, artificial intelligence data with 22%, and data uncertainty analysis account for 11% of the data processing field. Finally, studies highlight the challenges of IoT data management and its future directions.

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Defending co‐resident attack using reputation‐based virtual machine deployment policy in cloud computing

Xiao

Liang

et al. 2021

Trans Emerging Tel Tech

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Cloud computing enables users to utilize IT resources conveniently with low‐level cost, but it also brings some new threats. The co‐resident attack is one of the typical examples, where malicious users steal information from legal users by starting a virtual machine (VM) and building a side‐channel between VMs on the same server. Most of current studies focus mainly on defending the side‐channel attack, which requires modifications to the existing underlying architecture of cloud platforms. Some studies focus on security‐aware VMs deployment policies that can defeat co‐resident attacks through reduction of co‐residences. However, most of these studies ignore workload‐balance and energy‐efficiency. In addition, they neglect that data held in different VMs should have different security levels. Motivated by these issues, in this article, we first formalize the multi‐attackers co‐resident attack problem. The co‐located VMs rate (CVR) metric is proposed to evaluate the security level in cloud and a security‐aware policy named least‐danger‐based‐on‐reputation (LDBR) is presented to minimize the metric. Also, we propose extensional LDBR (E‐LDBR) policy to balance security, workload‐balance and energy consumption, and weighted‐LDBR (W‐LDBR) policy that considers users' different security levels. Experimental results indicate that LDBR outperforms PSSF (previous‐selected‐server‐first) by 15.02%‐22.07% in security, E‐LDBR is more balanced in workload and consumes less energy consumption, and W‐LDBR can reduce security threats by 13.3% compared with PSSF.

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Data Encryption for Internet of Things Applications Based on Catalan Objects and Two Combinatorial Structures

Cited by 54 publications

References 40 publications

A Center-Rule-Based Neighborhood Search Algorithm for Roadside Units Deployment in Emergency Scenarios

A Center-Rule-Based Neighborhood Search Algorithm for Roadside Units Deployment in Emergency Scenarios

Internet of Things data management: A systematic literature review, vision, and future trends

Defending co‐resident attack using reputation‐based virtual machine deployment policy in cloud computing

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