Trading Private Range Counting over Big IoT Data

Cai, Zhipeng; He, Zaobo

doi:10.1109/icdcs.2019.00023

Cited by 269 publications

(141 citation statements)

References 17 publications

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“…The mean field equation is constructed to analyse the dynamic characteristics of DDSEIR and the factors that influence malware spread, which is used to further derive the malware propagation scale and threshold value of diffusion. (5). This paper uses real dataset Live Journal to build an online social network in NetLogo and verifies the validity of the DDSEIR model.…”

Section: Introductionmentioning

confidence: 64%

Dynamics of Complex Networks: Malware Propagation Modeling and Analysis in Industrial Internet of Things

Cui

Zhang

et al. 2020

IEEE Access

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While cyber physics system (CPS) provides forward-looking and personalized services for users, it also creates conditions for the spread of malware. Therefore, it's critical for us to analyse affecting factors and study the propagation characteristics of malware. On the basis of the difference of intelligent device's dissemination capacity and discriminant ability, a dynamic malware propagation model (Disseminate&Discriminate-Spread-Exposed-Ignorant-Recover, DDSEIR) is proposed. First, intelligent devices are classified into different groups according to the level of dissemination capability by hierarchical mechanism, which takes the networks topology into account. And subsequently, intelligent device's discriminant ability can be evaluated by sender's identity and information attributes. Then, the mean field equation is constructed to analyze the dynamic characteristics of DDSEIR and the factors that influence malware propagation, which is used to further derive the malware propagation scale and threshold value of diffusion. Finally, this paper uses Live Journal dataset to verify the effectiveness of DDSEIR. The experiments illustrate that intelligent device's dissemination capacity and discriminant ability have significant influences on malware propagation.

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Section: Introductionmentioning

confidence: 64%

Dynamics of Complex Networks: Malware Propagation Modeling and Analysis in Industrial Internet of Things

Cui

Zhang

et al. 2020

IEEE Access

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“…Due to the variety and complexity of IoT devices [50], [51], we set the number of nodes n range from 1000 to 8000. In the network generation phase of the simulation experiment, we assume that there is a Data Sharing Platform (i.e., DSP) that could provide data interaction [52], [53].…”

Section: ) Label Generation and Network Configurationmentioning

confidence: 99%

A Novel Community Detection Algorithm Based on Paring, Splitting and Aggregating in Internet of Things

Xia

Zhang

et al. 2020

IEEE Access

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The explosive growth of Internet of Things (i.e., IoT) terminal equipment makes its topology more complex, which leads to the increasing cost of network research. Recently, the implicit community structure is widely used to improve the efficiency of research. However, most of the non-overlapping community detection algorithms have some weakness, such as the large number of community detected and the obvious scale gap between communities. To address these abovementioned problems, we design a novel non-overlapping community detection algorithm, named as Pairing, Splitting and Aggregating algorithm (i.e., PSA). Firstly, in order to improve the accuracy of community division, a new node similarity index is designed to transform the network into a large number of similar node pairs. Secondly, based on the connected branches composed of similar node pairs, the network is further divided into several similar node sets. Thirdly, to balance the scale gap of different communities, the Grasshopper Optimization Algorithm, (i.e., GOA) is introduced to combine the local attribute (i.e., conductance) and global attribute (i.e., modularity) together to aggregate similar node sets into potential (or final) communities. Finally, the experimental results show that PSA not only controls the difference among communities well, but also outperforms the other four popular algorithms in terms of two metrics. Moreover, we propose a community-based resource discovery method (or scheme), named as Community-assisted Short-distancequery Resource Discovery algorithm (i.e., CSRD) to further verify the efficiency of PSA. The results show that the resource discovery efficiency of CSRD using PSA is better compared with other algorithms.

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“…A comprehensive framework for data process is proposed in [28], where the balanced benefits for multiple stakeholders are guaranteed in multiple scenarios. Meanwhile, the study in [29], [30], [31] presents an efficient heuristic method for physical data processing, providing a thorough consideration between the physical and social aspects of CPS.…”

Section: Related Workmentioning

confidence: 99%

Uncertainty Theory Based Reliability-Centric Cyber-Physical System Design

Jiang

Wang

Jiao³

et al. 2019

2019 International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE C

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Cyber-physical systems (CPSs) are built from, and depend upon, the seamless integration of software and hardware components. The most important challenge in CPS design and verification is to design CPS to be reliable in a variety of uncertainties, i.e., unanticipated and rapidly evolving environments and disturbances. The costs, delays and reliability of the designed CPS are highly dependent on software-hardware partitioning in the design. The key challenges in partitioning CPSs is that it is difficult to formalize reliability characterization in the same way as the uncertain cost and time delay. In this paper, we propose a new CPS design paradigm for reliability assurance while coping with uncertainty. To be specific, we develop an uncertain programming model for partitioning based on the uncertainty theory, to support the assured reliability. The uncertainty effect of the cost and delay time of components to be implemented can be modeled by the uncertainty variables with uncertainty distributions, and the reliability characterization is recursively derived. We convert the uncertain programming model and customize an improved heuristic to solve the converted model. Experiment results on some benchmarks and random graphs show that the uncertain method produces the design with higher reliability. Besides, in order to demonstrate the effectiveness of our model for in coping with uncertainty in design stage, we apply this uncertain framework and existing deterministic models in the design process of a subsystem that is used in real world subway control. The system implemented based on the uncertain model works better than the result of deterministic models. The proposed design paradigm has the potential to be generalized to the design of CPSs for greater assurances of safety and security under a variety of uncertainties.

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Trading Private Range Counting over Big IoT Data

Cited by 269 publications

References 17 publications

Dynamics of Complex Networks: Malware Propagation Modeling and Analysis in Industrial Internet of Things

Dynamics of Complex Networks: Malware Propagation Modeling and Analysis in Industrial Internet of Things

A Novel Community Detection Algorithm Based on Paring, Splitting and Aggregating in Internet of Things

Uncertainty Theory Based Reliability-Centric Cyber-Physical System Design

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