Secure Data Aggregation of Lightweight E-Healthcare IoT Devices With Fair Incentives

Tang, Wenjuan; Ren, Ju; Kun, Deng; Zhang, Yaoxue

doi:10.1109/jiot.2019.2923261

Cited by 96 publications

(43 citation statements)

References 40 publications

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“…With the spread of IoT applications, smart health is becoming an attractive paradigm. As it deals with user information and sensitive medical information, the security and mutual authentication of medical sensor devices for personal information protection, encryption, and real-time monitoring are key elements [125,[170][171][172][173][174][175][176][177][178][179][180][181].…”

Section: Identification Of Topics In Iot Securitymentioning

confidence: 99%

Current Research Trends in IoT Security: A Systematic Mapping Study

Lee

2021

Mobile Information Systems

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The smart mobile Internet-of-things (IoT) network lays the foundation of the fourth industrial revolution, the era of hyperconnectivity, hyperintelligence, and hyperconvergence. As this revolution gains momentum, the security of smart mobile IoT networks becomes an essential research topic. This study aimed to provide comprehensive insights on IoT security. To this end, we conducted a systematic mapping study of the literature to identify evolving trends in IoT security and determine research subjects. We reviewed the literature from January 2009 to August 2020 to identify influential researchers and trends of keywords. We additionally performed structural topic modeling to identify current research topics and the most promising ones via topic trend estimation. We synthesized and interpreted the results of the systematic mapping study to devise future research directions. The results obtained from this study are useful to understand current trends in IoT security and provide insights into research and development of IoT security.

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Section: Identification Of Topics In Iot Securitymentioning

confidence: 99%

Current Research Trends in IoT Security: A Systematic Mapping Study

Lee

2021

Mobile Information Systems

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“…ComptCost(mJ) = cpu 32768 ×1.8mA×3V (13) The total power consumption by the sensor node for EPPDA scheme is estimated with the follow in equation: TotalEnergy(mJ)=EnergyComm+EnergyCompt (14) Figure 12 shows that the energy consumption by EPPDA is lower than that of two other schemes. The reason is that the RESDA and LSDA schemes generate too many unnecessary messages for providing integrity and privacy in data aggregation.…”

Section: Energy Consumptionmentioning

confidence: 99%

“…In addition, it can be extended the life of the network [13]. The data aggregation scheme also faces many security challenges [10][11][12][13][14][15][16][17][18][19][20]. Sensor nodes are often deployed in hostile environments with low bandwidth and unsecured communication channels.…”

Section: Introductionmentioning

confidence: 99%

EPPDA: An Efficient and Privacy-Preserving Data Aggregation Scheme with Authentication and Authorization for IoT-Based Healthcare

Almalki

Soufiene

2021

Preprint

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Internet of Things (IoT) connects various kinds of intelligent objects and devices using the internet to collect and exchange data. Nowadays, The IoT is used in diverse application domains, including the healthcare. In the healthcare domain, the IoT devices can collects patient data, and its forwards the data to the healthcare professionals can view it. The IoT devices are usually resource-constrained in terms of energy consumption, storage capacity, computational capability, and communication range, data aggregation techniques are used to reduce the communication overhead. However, in healthcare system using IoT, the heterogeneity of technologies, the large number of devices and systems, and the different types of users and roles create important challenges in terms of security. For that, the security and privacy aggregation of health data are very important aspects. In this paper, we propose a novel secure data aggregation scheme based on homomorphic primitives in IoT based healthcare systems, called “An Efficient and Privacy-Preserving Data Aggregation Scheme with authentication for IoT-Based Healthcare applications” (EPPDA). EPPDA is based the Verification and Authorization phase to verifying the legitimacy of the nodes wants to join the process of aggregation. EPPDA uses additive homomorphic encryption to protect data privacy and combines it with homomorphic MAC to check the data integrity. The security analysis and experimental results show that our proposed scheme guarantees data privacy, messages authenticity, and integrity, with lightweight communication overhead and computation.

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“…Other issue is that the identity of the user can be impersonated for uploading the malicious data. In [32] mainly focused on the preserving the privacy of health data from the various source by providing the fair incentives, here advanced method of cryptographic schemes were used in order to support the data confidentiality while the data transmission takes place. Moreover to achieve the fair incentive , ID-based signature were used which detects the replay attacks and guarantee the privacy.…”

Section: Literature Surveymentioning

confidence: 99%

ESDAM - Efficient and Secure Data Aggregation against Malicious Nodes in Iot Environment

Veerabadrappa*¹,

Girisha²,

Marikannan³

2019

IJITEE

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Rapid expansion of IoT technologies and their devices has created the considerable convenience in the daily lives of the people. Modernization of technique in IoT has allowed them to perform just more than sensing that directly means the more energy consumption. It is a known fact that most of the IoT devices have the limited power supply and hence it is an obvious need to design the energy efficient model. Despite of IoT devices being so useful in daily life and in other industries, data security is one of the primary concern in the fields of IoT application such as healthcare, agriculture, defense etc., and it is a challenging task to provide the data security in these fields. In past, several methods have been proposed to address this challenge, however, either they failed to provide the security or they lack from the efficiency. In this paper, it introduces a methodology named as ESDAM (Efficient and Secure Data Aggregation against Malicious Nodes) that provides better security with improved efficiency. The proposed methodology is parted into two methods, which helps in discerning the malicious nodes. First method, is through extending coordinates and the second method, is through surveilling the adjacent nodes. Extensive simulation has been performed by applying various constraints through persuading various number of malicious and performance metrics such as energy utilization, number of failed nodes, packet mismatch rate and packet discern rate. The performance evaluation of the simulation results proves that proposed methodology performs better than the existing methods.

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Secure Data Aggregation of Lightweight E-Healthcare IoT Devices With Fair Incentives

Cited by 96 publications

References 40 publications

Current Research Trends in IoT Security: A Systematic Mapping Study

Current Research Trends in IoT Security: A Systematic Mapping Study

EPPDA: An Efficient and Privacy-Preserving Data Aggregation Scheme with Authentication and Authorization for IoT-Based Healthcare

ESDAM - Efficient and Secure Data Aggregation against Malicious Nodes in Iot Environment

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