Privacy-Preserving Task Assignment in Spatial Crowdsourcing

Liu, An; Li, Zhixu; Liu, Guanfeng; Zheng, Kai; Zhang, Min; Li, Qing; Zhang, Xiangliang

doi:10.1007/s11390-017-1772-5

Cited by 41 publications

(17 citation statements)

References 39 publications

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“…This two-dimensional data is re-coordinate to single shorter string values using the geohash converter. Geohash algorithm provides a hierarchical grid-based model of the earth where locations are presented in Base32 strings [84]. To use more accurate, consistent data for our data processing, the converted geohash data, and other data features are integrated through data fusion.…”

Section: Proposed Risk Inference Approach Based On Geographical mentioning

confidence: 99%

Risk Assessment Inference Approach Based on Geographical Danger Points Using Student Survey Data for Safe Routes to School

2020

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Safe Routes to School is very important for students to have good physical and psychologically healthy in school life. For providing safe routes based on risk analysis, finding out dangerous points and areas can be a target to avoid dangerous locations by pedestrians and drivers. However, analyzing the risk assessment to derive the safe routes requires a large amount of data with a certain time of observation by experts. Deep learning is a solution to provide information regarding safe routes based on expert knowledge. In this paper, we propose a risk assessment inference approach using a Recurrent Neural Network (RNN) model with Long-Short Term Memory (LSTM) cells based on geographical information for safe routes to school. However, geographical information including coordinates is difficult used in learning-based inference models because of the series of float values. For training the RNN model with the geographical data, coordinates of routes and danger points are translated to be geohash through the geohash converter. The geohash data with other data of features are fused and inputted to the one-hot encoder. The one-hot encoded data is used in the inputs of the RNN model to train the LSTMs. The input data of the training model is derived by the risk index model that is proposed to calculate the risk index based on distances of route coordinates and danger points. Therefore, the risk index is correlated with the training dataset. Through the proposed inference approach, the geographical information including multiple coordinates is enabled to be trained by RNN as a geohash-based input string. Moreover, the input string with other features is fused to support the one-hot encoding to get a better result in RNN models.

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Section: Proposed Risk Inference Approach Based On Geographical mentioning

confidence: 99%

Risk Assessment Inference Approach Based on Geographical Danger Points Using Student Survey Data for Safe Routes to School

2020

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“…The elliptic curve discrete logarithm problem (ECDLP) is significantly more difficult and has a larger computational complexity than the integer factorization or discrete logarithm problem. (11) To satisfy security requirements, the ECC needs a comparatively smaller key size than the other cryptosystems. ECC-based access control schemes enjoy high security performance at the expense of bulky mobile agent codes and excessive calculations for encryption/decryption keys.…”

Section: Previous Workmentioning

confidence: 99%

Elliptic Curve Cryptosystems-based Date-constrained Hierarchical Key Management Scheme in Internet of Things

Hsiao¹,

Chen²,

Chen³

et al. 2019

Sensors and Materials

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In this paper, we propose a new mechanism to improve the disadvantage of the security mechanism proposed by a scholar and then fulfill the demands of Internet of Things (IoT) to go through the decentralized environment access control functions. We also propose the date-constrained hierarchical key management scheme for mobile agents. With elliptic curve cryptosystems (ECCs) and discrete logarithms, the proposed scheme is flexible. Moreover, the duration of access for each security class is restricted with a certain authorized discrete time period. We demonstrate the mathematical derivation and arguments for our scheme and further conduct a numerical trial. The constructed scheme could meet security needs and be more space-efficient.

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“…In fact, there are a lot of researches using homomorphic encryption as a commonly used encryption method [9,27,2,24,26,14,54,38,46,45]. Homomorphic encryption [12] which allows computation carried out on ciphertext is a straightforward way to achieve privacy.…”

Section: Related Workmentioning

confidence: 99%

Differential private collaborative Web services QoS prediction

Liu

Shen

et al. 2018

World Wide Web

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Collaborative Web services QoS prediction has proved to be an important tool to estimate accurately personalized QoS experienced by individual users, which is beneficial for a variety of operations in the service ecosystem, such as service selection, composition and recommendation. While a number of achievements have been attained on the study of improving the accuracy of collaborative QoS prediction, little work has been done for protecting user privacy in this process. In this paper, we propose a privacy-preserving collaborative QoS prediction framework which can protect the private data of users while retaining the ability of generating accurate QoS prediction. We introduce differential privacy, a rigorous and provable privacy model, into the process of collaborative QoS prediction. We first present DPS, a method that disguises a user's observed QoS values by applying differential privacy to the user's QoS data directly. We show how to integrate DPS with two representative collaborative QoS prediction approaches. To improve the utility of the disguised QoS data, we present DPA, another QoS disguising method which first aggregates a user's QoS data before adding noise to achieve differential privacy. We evaluate the proposed methods by conducting extensive experiments on a real world Web services QoS dataset. Experimental results show our approach is feasible in practice.

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Privacy-Preserving Task Assignment in Spatial Crowdsourcing

Cited by 41 publications

References 39 publications

Risk Assessment Inference Approach Based on Geographical Danger Points Using Student Survey Data for Safe Routes to School

Risk Assessment Inference Approach Based on Geographical Danger Points Using Student Survey Data for Safe Routes to School

Elliptic Curve Cryptosystems-based Date-constrained Hierarchical Key Management Scheme in Internet of Things

Differential private collaborative Web services QoS prediction

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