Elsevier

Future Generation Computer Systems

Volume 115, February 2021, Pages 304-313
Future Generation Computer Systems

Multiple cloud storage mechanism based on blockchain in smart homes

https://doi.org/10.1016/j.future.2020.09.019Get rights and content

Highlights

  • ā€¢

    The data storage model in smart home based on blockchain under multiple cloud providers is proposed.

  • ā€¢

    An identity-based proxy aggregate signature is proposed to improve the efficiency of signature verification.

  • ā€¢

    Besides, the signature can compress transaction storage space and reduce communication bandwidth.

Abstract

The emergence of the smart home has fundamentally changed the quality of human living owing to its usefulness and convenience. However, it still has some serious problems that mainly lie in its relational database security. The data storage of a smart home cannot meet the security requirements of its residents. To strengthen its security, blockchain technology is applied to the data storage and data connection, being embodied in the data storage model in smart homes based on blockchains under multiple cloud providers. However, the model still has weaknesses due to its limited blockchain transaction storage space and the current speed of addressing blockchain storage transactions. To solve these problems, this paper proposes an identity-based proxy aggregate signature (IBPAS) scheme to improve the efficiency of signature verification, as well as compress the storage space and reduce the communication bandwidth. According to our experiments, although the communication cost of our IBPAS scheme accounts for only 12% to 39% of that of an ordinary signature scheme, its storage performance in a blockchain is better than that of the blockchain itself by 20%.

Introduction

Since the Internet of Things (IoT) was formally put forward by the International Telecommunication Union in 2005, the development of sensor networks, cloud computing, microchips and other relevant technologies has greatly contributed to the rapid growth of the IoT industry. As a typical representative application of IoT technology, the smart home integrates household facilities based on technology to provide a comfortable, convenient, safe and entertaining living environment to its residentsĀ [1], [2], [3].

Since a variety of smart devices are used in the smart home system, a large amount of data is generated, and data exchanges are dispensable during its operation. The storage of video information in the home camera, for example, usually requires a very large storage space. Therefore, traditional information systems face difficulty in maintaining and managing a large amount of collected smart home dataĀ [4], [5], [6], [7]. Fortunately, cloud storage has played a revolutionary role in the field of data storage. Under the new storage mode, users do not need to care about the specific structure, management mode and maintenance mode of the storage system and do not need to worry about technical issues such as expansion and fault tolerance. They simply purchase storage services from a cloud storage provider (CSP), who will not only meet the diverse requirements of its users (such as storage capacity, access speed, and security) but also reduce the storage cost and bring greater economic benefits to the data owners. Therefore, cloud storage technology is widely used in the field of smart homesĀ [8], [9].

Despite all these conveniences, smart homes also face serious security problems. The security loopholes of the smart home system may not only bring the risk of privacy leakage to its users but also cause the loss of its usersā€™ property and even threaten their personal securityĀ [10], [11]. In general, the following challenges exist for the smart home system.

(1) Unauthorized access: Attackers may invade smart homes without authorization and steal usersā€™ data. In this case, they may hack into the system by learning usersā€™ behavioral patterns and steal their data, thus removing their privacy.

(2) Tampering with data: Attackers may modify data stored in the smart home system without authorization, making authorized data collectors obtain fake user data. For example, attackers may deliberately adjust the temperature settings, which will put the userā€™s property and life security at risk.

Since the smart home system is based on cloud storage, the data owner may physically lose control of their data, making the data stored on the server easy to modify and delete.

To address the above threats, this paper constructs ablockchain for data storage in a multiple-cloud-storage-provider environment and proposes an aggregate digital signature to address security problems. Here are our contributions:

  • ā€¢

    Blockchain in multiple CSPs: We build a blockchain for data storage in a multicloud environment for the smart home system. As each CSP has a copy of the blockchain for a smart home userā€™s data, it prevents data from being tampered with.

  • ā€¢

    The identity-based proxy aggregate signature (IBPAS)scheme: This scheme is an identity-based proxy aggregation signature one that can compress the blockchain storage space and reduce the communication bandwidth.

We have organized the existing papers below. On the basis of a literature review, SectionĀ 2 introduces the basics of smart homes and blockchains. SectionĀ 3 describes the security requirements of smart homes. SectionĀ 4 presents our multiple-cloud-storage model. SectionĀ 5 describes the identity-based proxy aggregation signature scheme. SectionĀ 6 gives an assessment of the energy consumption of the message calculation and transmission of the IBPAS scheme.

Section snippets

Smart home

The concept of smart homes has undergone nearly 40Ā years of development and innovation since the 1980s. Currently, with its diversified forms, the smart home system has richer technology implementation. It involves the application of advanced computer technology, network communication technology, and sensing and control technology to meet our needs in a personalized manner, thus unifying our home life associated with each subsystem organically and implementing a ā€œpeople-orientedā€ smart home

Problem statement

With the rapid development of information and intelligence today, the smart home industry has become more prosperous, with a wider range of applications. Although intelligent households bring convenience to peopleā€™s lives, they also have security problems that become more prominent with the rapid development of this industry. These security problems, such as personal information disclosure, illegal user intrusion, and equipment failure, may cause property loss and even personal injury to users

Multiple-cloud-storage-provider models in smart homes

Our information system of the smart home model is shown in Fig.Ā 2. Different from the traditional smart home information system, we build a multi-CSP environment to replace the single CSP in smart homes. In the model, the following entities exist.

  • (1)

    Smart devices/devices in the edge network: In our smart home system, a large number of smart devices are deployed in each home, which can be constructed into an edge network. Most of these devices are sensors, monitoring the indoor temperature,

Identity-based proxy aggregate signatures

SectionĀ 5.1 describes the basic IBPAS model, SectionĀ 5.2 describes our scheme, and SectionĀ 5.3 proves the security of our scheme under the oracle modelĀ [46].

Experiment

To assess the energy consumption of the proposed scheme, we use the method presented inĀ [50], [51] to analyze the energy consumed mainly by the Chipcon CC1000 transceiverĀ [45]. The energy consumption of receiving and transmitting one byte is 28.6 Ī¼J and 59.2 Ī¼J, respectively, in Crossbow MICA2DOT motes.

In the IBPAS scheme, the message size is 50 bytes. The energy consumption of those that contain sent and received messages is (6|p|+5)Ɨ(28.6+59.2) mJ = (0.526|p|+0.439) mJ. For W users, the

Conclusions

In this paper, we proposed a multiple-cloud-storage mechanism in smart homes, where the data blockchain is constructed in multiple-cloud-storage providers. We designed an IBPAS scheme to ensure that user data are viewed only by managers and that the blockchain storage space is compressed. We employed blockchain technology to store data in the blockchain. Through the untamable nature of a blockchain in multiple-cloud-storage providers, the integrity, reliability, and availability of data are

CRediT authorship contribution statement

Yongjun Ren: Conceptualization, Methodology, Writing - original draft. Yan Leng: Software, Implementation. Jian Qi: Data curation, Analysis. Pradip Kumar Sharma: Methodology, Modelling, Proofread. Jin Wang: Methodology, Modelling, Analysis. Zafer Almakhadmeh: Investigation, Proofreading. Amr Tolba: Methodology, Data curation, Validation.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This work is supported by the NSFC (61772280, 61772454, 61811530332, 61811540410), and the PAPD fund from NUIST, China. The authors extend their appreciation to the Deanship of Scientific Research at King Saud University for funding this work through research group No. RG-1439-088. Prof.Ā Jin Wang is the corresponding author.

Yongjun Ren obtained the Ph.D. degree in the computer and science Department at the Nanjing University of Aeronautics and Astronautics, China, in 2008. Now he is serving as a full time faculty in the Nanjing University of Information science and Technology. His research interests include network security and applied cryptography.

References (52)

  • ZhaoW. et al.

    Etc-iot: Edge-node-assisted transmitting for the cloud-centric internet of things

    IEEE Network

    (2018)
  • HanD.M. et al.

    Design and implementation of smart home energy management systems based on zigbee

    IEEE Trans. Consum. Electron.

    (2010)
  • DemirisG. et al.

    Technologies for an aging society: a systematic review of smart home applications

    Yearb. Med. Inf.

    (2008)
  • WangJ. et al.

    Optimal coverage multi-path scheduling scheme with multiple mobile sinks for WSNs

    Comput. Mater. Contin.

    (2020)
  • GargS. et al.

    HyClass: Hybrid classification model for anomaly detection in cloud environment

  • SinghA. et al.

    Fuzzy-folded bloom filter-as-a-service for big data storage in the cloud

    IEEE Trans. Ind. Inf.

    (2018)
  • RoblesR.J. et al.

    Applications, systems and methods in smart home technology

    Int. J. Adv. Sci. Technol.

    (2010)
  • N. Noury, T. HervĆ©, V. Rialle, G. Virone, E. Mercier, G. Morey, T. Porcheron, Monitoring behavior in home using a smart...
  • GargS. et al.

    Towards secure and provable authentication for internet of things: realizing industry 4.0

    IEEE Internet Things J.

    (2019)
  • WangJ. et al.

    An energy-efficient offloading scheme for low latency in collaborative edge computing

    IEEE Access

    (2019)
  • C. Lee, L. Zappaterra, K. Choi, H.A. Choi, Securing smart home: Technologies, security challenges, and security...
  • ZhangJ. et al.

    Spatial and semantic convolutional features for robust visual object tracking

    Multimedia Tools Appl.

    (2018)
  • SunR. et al.

    An improved method in deep packet inspection based on regular expression

    J. Supercomput.

    (2019)
  • JoseA.C. et al.

    Improving smart home security: Integrating logical sensing into smart home

    IEEE Sens. J.

    (2017)
  • Y.P. Tsou, J.W. Hsieh, C.T. Lin, C.Y. Chen, Building a remote supervisory control network system for smart home...
  • ZengD. et al.

    Distant supervised relation extraction with cost-sensitive loss

    Comput. Mater. Contin.

    (2019)
  • Cited by (143)

    • Selection of node with editing rights and privacy protection mechanisms based on dual-blockchain

      2023, Journal of King Saud University - Computer and Information Sciences
    View all citing articles on Scopus

    Yongjun Ren obtained the Ph.D. degree in the computer and science Department at the Nanjing University of Aeronautics and Astronautics, China, in 2008. Now he is serving as a full time faculty in the Nanjing University of Information science and Technology. His research interests include network security and applied cryptography.

    Yan Leng was born in Jiangsu Province, China. He is pursuing a masterā€™s degree at Nanjing University of Information Science and Technology. His research includes cloud storage integrity verification, blockchain system structure and its applications.

    Jian Qi was born in Jianhu, Jiangsu Province, China. He received his B.S. degree in IoT from Binjiang College of Nanjing University of Information Science & Technology in 2017. Currently, he is enrolled in the Masterā€˜s Degree of the School of Computer and Software, Nanjing University of Information Science & Technology. His research interests include cloud storage integrity verification, blockchain architecture and applications and cryptographic accumulator.

    Pradip Kumar Sharma is the researcher and leader at UCS Lab in Seoul National University of Science & Technology. He is presently working on many ongoing research projects with industry and research institutes. The research projects focus on the study and development of innovative software solutions on ubiquitous computing, cloud computing, IoT, computer & network security using cutting edge technology such as blockchain, software defined networking, machine learning, and artificial intelligence, etc.

    Jin Wang received the B.S. and M.S. degree in the Electronical Engineering from Nanjing University of Posts and Telecommunications, China in 2002 and 2005, respectively. He received Ph.D. degree from Kyung Hee University Korea in 2010. Now, he is a professor in the Nanjing University of Information Science and technology. His research interests mainly include sensor networks. He is a member of the IEEE and ACM.

    Zafer Almakhadmeh received the M.Sc. and Ph.D. degrees from the Department of Computer Engineering, Faculty of Information and Computer Engineering, Kharkov National Technical University of Ukraine, in 1998 and 2001, respectively. He is currently an Associate Professor with the Department of Computer Science, Community College, King Saud University, Saudi Arabia. His main research interests include cloud computing, image processing, computer vision, and intelligent systems.

    Amr Tolba received the M.Sc. and Ph.D. degrees from Mathematics and Computer Science Department, faculty of science, Menoufia University, Egypt, in 2002 and 2006, respectively. He is currently an Associate Professor at the Faculty of Science, Menoufia University, Egypt. He is currently on leave from Menoufia University to the Computer Science Department, Community College, King Saud University (KSU), Saudi Arabia. Dr Tolba serves as a technical program committee (TPC) member in several conferences. He has authored/coauthored over 65 scientific papers in top ranked (ISI) international journals and conference proceedings. His main research interests include socially aware networks, vehicular ad-hoc networks, Internet of Things, intelligent systems, Big Data, recommender systems, and cloud computing.

    View full text