A security gateway application for End-to-End M2M communications

Chen, Hsing‐Chung; You, Ilsun; Weng, Chien-Erh; Cheng, Chia-Hsin; Huang, Yung-Fa

doi:10.1016/j.csi.2015.09.001

Cited by 27 publications

(19 citation statements)

References 3 publications

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“…(i) Vehicle communication systems. Machine-to-Machine (M2M) communication for the IoT system was considered to be a key technology in future networks as introduced by Chen et al [24]. Park et al proposed a transmission strategy for use with a capillary M2M system under wireless personal area networks based on a series of performance analysis for contention adaptation of M2M devices with directional antennas [25,26] [28].…”

Section: Data Analysis For Automaticmentioning

confidence: 99%

Vehicle Movement Analyses Considering Altitude Based on Modified Digital Elevation Model and Spherical Bilinear Interpolation Model: Evidence from GPS-Equipped Taxi Data in Sanya, Zhengzhou, and Liaoyang

Gui

2020

Journal of Advanced Transportation

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Aggravating energy shortages and increasing labor costs have become global problems and have garnered special importance in recent years in the transportation sector, especially in taxi markets. Automatic vehicles have a bright future, however, there is an equal amount of skepticism and concern about safety for all the optimism. To unlock the potential of automatic vehicles in intelligent transportation systems, a lot more data and testing are required to promote safety level as far as possible and achieve the organizational aim of reducing accidents to zero tolerance. And it is vital to provide accurate models for vehicle movement analyses. In this study, Modified Digital Elevation (MDE) model and Spherical Bilinear Interpolation (SBI) model were proposed for vehicle movement analyses considering altitude. And the experimental data of 9,990 GPS-enabled taxis in Sanya, Zhengzhou, and Liaoyang were adopted to support comparisons. Measurement results showed that MDE model had over 99% less disparity with direct solution than original model and SBI model could further improve the effects. It indicated that the application of MDE model and SBI model could improve both accuracy and efficiency of vehicle movement analyses and it had a bright future in the field of automatic vehicles. Future directions could be improving models and expanding data.

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Section: Data Analysis For Automaticmentioning

confidence: 99%

Vehicle Movement Analyses Considering Altitude Based on Modified Digital Elevation Model and Spherical Bilinear Interpolation Model: Evidence from GPS-Equipped Taxi Data in Sanya, Zhengzhou, and Liaoyang

Gui

2020

Journal of Advanced Transportation

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“…A randomization process occurs within the EEIRI design for each search query denoted by q. This is conducted through inclusion of (d+2)-dimensions random items that are demonstrated in equation 4as well as encrypted as demonstrated in equation (5). Therefore, there is a difference in terms of encrypted search vectors q′ for each search query.…”

Section: Search Unlinkabilitymentioning

confidence: 99%

“…In any case, the administration and maintenance of these images makes noteworthy requests as far as storage and computational cost. These capabilities might be inaccessible for all smart cellphone clients, especially the individuals who are utilizing lightweight smart cellphone, for example, iPhones [5].…”

Section: Introductionmentioning

confidence: 99%

EEIRI: Efficient Encrypted Image Retrieval in IoT-Cloud

2019

KSII TIIS

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One of the best means to safeguard the confidentiality, security, and privacy of an image within the IoT-Cloud is through encryption. However, looking through encrypted data is a difficult process. Several techniques for searching encrypted data have been devised, but certain security solutions may not be used in IoT-Cloud because such solutions are not lightweight. We propose a lightweight scheme that can perform a content-based search of encrypted images, namely EEIRI. In this scheme, the images are represented using local features. We develop and validate a secure scheme for measuring the Euclidean distance between two descriptor sets. To improve the search efficiency, we employ the k-means clustering technique to construct a searchable tree-based index. Our index construction process ensures the privacy of the stored data and search requests. When compared with more familiar techniques of searching images over plaintexts, EEIRI is considered to be more efficient, demonstrating a higher search cost of 7% and a decrease in search accuracy of 1.7%. Numerous empirical investigations are carried out in relation to real image collections so as to evidence our work.

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“…1 Authorized smart device users initially generate the feature vector v from q after being provided with the image query q and the secret keys. 1 Subsequently, the resulting vector is extended and expanded using equations (2) and 4, respectively, to obtain the QSV (refining vector). 1 Finally, authorized smart device users execute the trapdoor algorithm ST q TrpdrGen(SK, q) to hash q into L bucket identifiers using the same settings as those of the index setup.…”

Section: Secure Retrieval Stagementioning

confidence: 99%

Efficient encrypted image retrieval in IoT-cloud with multi-user authentication

Sibahee

Abduljabbar

et al. 2018

International Journal of Distributed Sensor Networks

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Encryption is one of the best methods to safeguard the security and privacy of an image. However, looking through encrypted data is difficult. A number of techniques for searching encrypted data have been devised. However, certain security solutions may not be used in smart devices in IoT-cloud because such solutions are not lightweight. In this article, we present a lightweight scheme that can enable a content-based search through encrypted images. In particular, images are represented using local features. We develop and validate a secure scheme for measuring the Euclidean distance between two feature vectors. In addition, we use a hashing method, namely, locality-sensitive hashing, to devise the searchable index. The use of an locality-sensitive hashing index increases the proficiency and effectiveness of a system, thereby allowing the retrieval of only relevant images with a minimum number of distance evaluations. Refining vector techniques are used to refine relevant results efficiently and securely. Our index construction process ensures that stored data and trapdoors are kept private. Our system also efficiently supports multiuser authentication by avoiding the expensive traditional method, which enables data owners to define who can search for a specific image. Compared with other similarity-based encryption methods predicated upon searchability, the option presented in this study offers superior search speed and storage efficiency.

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A security gateway application for End-to-End M2M communications

Cited by 27 publications

References 3 publications

Vehicle Movement Analyses Considering Altitude Based on Modified Digital Elevation Model and Spherical Bilinear Interpolation Model: Evidence from GPS-Equipped Taxi Data in Sanya, Zhengzhou, and Liaoyang

Vehicle Movement Analyses Considering Altitude Based on Modified Digital Elevation Model and Spherical Bilinear Interpolation Model: Evidence from GPS-Equipped Taxi Data in Sanya, Zhengzhou, and Liaoyang

EEIRI: Efficient Encrypted Image Retrieval in IoT-Cloud

Efficient encrypted image retrieval in IoT-cloud with multi-user authentication

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