• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3852-3864
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• 2016

Patients' health data is very sensitive and the access to individual's health data should be strictly restricted. However, many data consumers may need to use the aggregated health data. For example, the insurance companies needs to use this data to setup the premium level for health insurances. Therefore, privacy-preserving data aggregation solutions for health data have both theoretical importance and application potentials. In this paper, we propose a privacy-preserving health data aggregation scheme using differential privacy. In our scheme, patients' health data are aggregated by the local healthcare center before it is used by data comsumers, and this prevents individual's data from being leaked. Moreover, compared with the existing schemes in the literature, our work enjoys two additional benefits: 1) it not only resists many well known attacks in the open wireless networks, but also achieves the resilience against the human-factor-aware differential aggregation attack; 2) no trusted third party is employed in our proposed scheme, hence it achieves the robustness property and it does not suffer the single point failure problem.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.83-95
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• 2020

Because sensor nodes have limited resources in wireless sensor networks, data aggregation can efficiently reduce communication overhead and extend the network lifetime. Although many existing methods are particularly useful for data aggregation applications, they incur unbalanced communication cost and waste lots of sensors' energy. In this paper, we propose a privacy-preserving, energy-saving data aggregation scheme (EBPP). Our method can efficiently reduce the communication cost and provide privacy preservation to protect useful information. Meanwhile, the balanced energy of the nodes can extend the network lifetime in our scheme. Through many simulation experiments, we use several performance criteria to evaluate the method. According to the simulation and analysis results, this method can more effectively balance energy dissipation and provide privacy preservation compared to the existing schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4442-4466
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• 2016

This paper proposes a privacy-preserving aggregation scheme based on the designed P-Gene (PAPG) for sensor networks. The P-Gene is constructed using the designed erasable data-hiding technique. In this P-Gene, each sensory data item may be hidden by the collecting sensor node, thereby protecting the privacy of this data item. Thereafter, the hidden data can be directly reported to the cluster head that aggregates the data. The aggregation result can then be recovered from the hidden data in the cluster head. The designed P-Genes can protect the privacy of each data item without additional data exchange or encryption. Given the flexible generation of the P-Genes, the proposed PAPG scheme adapts to dynamically changing reporting nodes. Apart from its favorable resistance to data loss, the extensive analyses and simulations demonstrate how the PAPG scheme efficiently preserves privacy while consuming less communication and computational overheads.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.3
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• pp.685-692
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• 2019

Smart grid enables efficient power management by allowing real-time awareness of electricity flows through two-way communication. Despite its various advantages, threats to user privacy caused by frequent meter reading hinder prosperous deployment of smart grid. In this paper, we propose a privacy-preserving aggregation method exploiting fully homomorphic encryption (FHE). Specifically, it achieves privacy-preserving fine-grained aggregation of electricity usage for smart grid customers in multiple electrical source environments, while further enhancing efficiency through SIMD-style operations simultaneously. Analysis of our scheme demonstrates the suitability in next-generation smart grid environment where the customers select and use a variety of power sources and systematic metering and control are enabled.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.5189-5208
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• 2015

To address the contradiction between data aggregation and data security in wireless sensor networks, a Recoverable Privacy-preserving Integrity-assured Data Aggregation (RPIDA) scheme is proposed based on privacy homomorphism and aggregate message authentication code. The proposed scheme provides both end-to-end privacy and data integrity for data aggregation in WSNs. In our scheme, the base station can recover each sensing data collected by all sensors even if these data have been aggregated by aggregators, thus can verify the integrity of all sensing data. Besides, with these individual sensing data, base station is able to perform any further operations on them, which means RPIDA is not limited in types of aggregation functions. The security analysis indicates that our proposal is resilient against typical security attacks; besides, it can detect and locate the malicious nodes in a certain range. The performance analysis shows that the proposed scheme has remarkable advantage over other asymmetric schemes in terms of computation and communication overhead. In order to evaluate the performance and the feasibility of our proposal, the prototype implementation is presented based on the TinyOS platform. The experiment results demonstrate that RPIDA is feasible and efficient for resource-constrained sensor nodes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.617-636
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• 2021

This paper presents a privacy-preserving data aggregation scheme deals with the multidimensional data. It is essential that the multidimensional data is rarely mentioned in all researches on smart grid. We use the Paillier Cryptosystem and blinding factor technique to encrypt the multidimensional data as a whole and take advantage of the homomorphic property of the Paillier Cryptosystem to achieve data aggregation. Signature and efficient batch verification have also been applied into our scheme for data integrity and quick verification. And the efficient batch verification only requires 2 pairing operations. Our scheme also supports fault tolerance which means that even some smart meters don't work, our scheme can still work well. In addition, we give two extensions of our scheme. One is that our scheme can be used to compute a fixed user's time-of-use electricity bill. The other is that our scheme is able to effectively and quickly deal with the dynamic user situation. In security analysis, we prove the detailed unforgeability and security of batch verification, and briefly introduce other security features. Performance analysis shows that our scheme has lower computational complexity and communication overhead than existing schemes.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.49-59
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• 2018

Smart grid system has been deployed fast despite of legal, business and technology problems in many countries. One important problem in deploying the smart grid system is to protect private smart meter readings from the unbelievable parties while the major smart meter functions are untouched. Privacy-preserving involves some challenges such as hardware limitations, secure cryptographic schemes and secure signal processing. In this paper, we focused particularly on the smart meter reading aggregation,which is the major research field in the smart meter privacy-preserving. We suggest a noisy weighted aggregation scheme to guarantee differential privacy. The noisy weighted values are generated in such a way that their product is one and are used for making the veiled measurements. In case that a Diffie-Hellman generator is applied to obtain the noisy weighted values, the noisy values are transformed in such a way that their sum is zero. The advantage of Diffie and Hellman group is usually to use 512 bits. Thus, compared to Paillier cryptosystem series which relies on very large key sizes, a significant performance can be obtained.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.65-72
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• 2020

Today, the Internet of Things is used in many places, including homes, industrial sites, and hospitals, to give us convenience. Many services generate new value through real-time data collection, storage and analysis as devices are connected to the network. Many of these fields are creating services and applications that utilize sensors and communication functions within IoT devices. However, since everything can be hacked, it causes a huge privacy threat to users who provide data. For example, a variety of sensitive information, such as personal information, lifestyle patters and the existence of diseases, will be leaked if data generated by smarwatches are abused. Development of IoT must be accompanied by the development of security. Recently, Differential Privacy(DP) was adopted to privacy-preserving data processing. So we propose the method that can aggregate health data safely on smartwatch platform, based on DP.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1553-1571
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• 2018

Currently, many of schemes for smart grid data aggregation are based on a one-level gateway (GW) topology. Since the data aggregation granularity in this topology is too single, the control center (CC) is unable to obtain more fine-grained data aggregation results for better monitoring smart grid. To improve this issue, Shen et al. propose an efficient privacy-preserving cube-data aggregation scheme in which the system model consists of two-level GW. However, a risk exists in their scheme that attacker could forge the signature by using leaked signing keys. In this paper, we propose a secure and fine-grained electricity consumption aggregation scheme for smart grid, which employs the homomorphic encryption to implement privacy-preserving aggregation of users' electricity consumption in the two-level GW smart grid. In our scheme, CC can achieve a flexible electricity regulation by obtaining data aggregation results of various granularities. In addition, our scheme uses the forward-secure signature with backward-secure detection (FSBD) technique to ensure the forward-backward secrecy of the signing keys. Security analysis and experimental results demonstrate that the proposed scheme can achieve forward-backward security of user's electricity consumption signature. Compared with related schemes, our scheme is more secure and efficient.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06a
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• pp.160-161
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• 2010