Efficient and Privacy-Preserving Spatial Keyword Similarity Query Over Encrypted Data

Zhang, Songnian; Ray, Suprio; Lu, Rongxing; Guan, Yunguo; Zheng, Yandong; Shao, Jun

doi:10.1109/tdsc.2022.3227141

Cited by 18 publications

(6 citation statements)

References 31 publications

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“…Contact Tracing. There are two mainstream contact tracing technologies, namely proximity-based solutions [3], [4], [5], [6], [7], [8], [9], [25], [26], [27], [28], [29] and location-based solutions [10], [11], [12], [13], [14], [15], [16], [17], [21].…”

Section: Related Workmentioning

confidence: 99%

“…Different from our work on efficient contact tracing over historical data, many works focus on developing the contact tracer as an administrative web-based system [11], a privacy-enhanced mobile application [10], [12], [15], or a decentralized Blockchain-based system [16]. Several works [13], [14], [17] consider the efficiency of close contact search. In particular, Chao et al [14] devise an iterative algorithm and a grid-based time interval tree to find contacted trajectories along the transmission chains.…”

Section: Related Workmentioning

confidence: 99%

“…Li et al [17] develop group processing algorithms for online continuous monitoring of the contacts with the given objects. Zhang et al [13] resolve contact similarity search on uncertain trajectories based on an uncertain trajectory M-tree applied to necklace-based trajectories. However, all these aforementioned studies apply to GPS data and determine the contact based on free-space distances.…”

Section: Related Workmentioning

confidence: 99%

“…However, these methods need to install apps on devices, and they do not consider spatial information and thus fail to customize close contact criteria. There also exist location-based contact tracing methods [10], [11], [12], [13], [14], [15], [16], [17] that find spatially close people based on their spatial distances in the historical times. However, these methods mainly focus on outdoor spaces and neglect the indoor topology in our problem setting.…”

Section: Introductionmentioning

confidence: 99%

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Contact Tracing Over Uncertain Indoor Positioning Data

Liu

et al. 2023

IEEE Trans. Knowl. Data Eng.

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Pandemics often cause dramatic losses of human lives and impact our societies in many aspects such as public health, tourism, and economy. To contain the spread of an epidemic like COVID-19, efficient and effective contact tracing is important, especially in indoor venues where the risk of infection is higher. In this work, we formulate and study a novel query called Indoor Contact Query (ICQ) over raw, uncertain indoor positioning data that digitalizes people's movements indoors. Given a query object o, e.g., a person confirmed to be a virus carrier, an ICQ analyzes uncertain indoor positioning data to find objects that most likely had close contact with o for a long period of time. To process ICQ, we propose a set of techniques. First, we design an enhanced indoor graph model to organize different types of data necessary for ICQ. Second, for indoor moving objects, we devise methods to determine uncertain regions and to derive positioning samples missing in the raw data. Third, we propose a query processing framework with a close contact determination method, a search algorithm, and the acceleration strategies. We conduct extensive experiments on synthetic and real datasets to evaluate our proposals. The results demonstrate the efficiency and effectiveness of our proposals.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Contact Tracing Over Uncertain Indoor Positioning Data

Liu

et al. 2023

IEEE Trans. Knowl. Data Eng.

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“…However, existing schemes [9,10] only support single or limited geometric ranges, such as circular, rectangular, or triangular ranges. While homomorphic encryption offers a viable approach for secure geometric range queries [11], the computational overhead associated with it is often unacceptable in practical scenarios. To achieve a fast search, Searchable Symmetric Encryption (SSE) [12][13][14] is commonly employed to enable secure and efficient retrieval of ciphertexts.…”

Section: Introductionmentioning

confidence: 99%

Enabling Efficient and Privacy-Preserving Task Allocation with Temporal Access Control for Mobile Crowdsensing

Song

Liu²,

et al. 2023

Electronics

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The increasing proliferation of GPS-enabled mobile devices, including Unmanned Aerial Vehicles (UAVs), smartphones, and laptops, has resulted in a significant upsurge in the outsourcing of spatial data to cloud servers for storage and computation purposes, such as task allocation and location-based services. However, the reliance on untrusted cloud servers introduces the risk of privacy breaches, as these servers possess the ability to deduce and access users’ private information based on task content and query requirements. Existing privacy-preserving task-allocation schemes offer only coarse-grained and non-temporal access control, which restricts their applicability in scenarios involving multiple users and time-series data, such as trajectory and time-related routes. To overcome these challenges, this paper proposes an Efficient and Privacy-Preserving Task Allocation with Temporal Access Control (EPTA-T) scheme for mobile crowdsensing. By leveraging the techniques of Gray code and randomizable matrix multiplication, EPTA-T achieves efficient and privacy-preserving task allocation in mobile crowdsensing. Specifically, EPTA-T supports fine-grained and temporal access control through the utilization of an attribute-based access tree and function integration. The formal security analysis demonstrated that EPTA-T effectively guarantees data privacy and query privacy throughout the task allocation process. Extensive experiments conducted using a real-world dataset indicated that the EPTA-T scheme surpassed the performance of the state-of-the-art scheme.

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