Efficient privacy-preserving fault tolerance aggregation for people-centric sensing system

Jansi, K. R.; Raja, S. V. Kasmir; Sandhia, G. K.

doi:10.1007/s11761-018-0241-5

Cited by 8 publications

(3 citation statements)

References 15 publications

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“…Moreover, the results are evaluated based on secure communications, transmission delay and communication overhead. The obtained results are compared with the existing models such as Anonysense [5] and EPPFTA [15]. Further, the model is evaluated using the Network Simulation Tool called NS-2, with the initial simulation settings, mentioned in Table III, since, the real-time evaluations are complicated to process.…”

Section: Experiments and Resultsmentioning

confidence: 99%

“…The model designed in terms of false data an injection attack that also supports data integrity. Fault tolerance based aggregation with the security enforcement has been done by the authors of [15]. And, the model has been named as Efficient Privacy Preserving Fault Tolerance Aggregation (EPPFTA) and the results are evaluated based on the performance factors such as packet delivery rate and transmission delay.…”

Section: Related Workmentioning

confidence: 99%

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Towards Developing Secure Data Aggregation with Integrity Verification Model (SDA-IV) in People Centric Sensing Systems

2019

IJEAT

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In present scenario of vast developments in wireless communication methods, embedded device based operations and mobile communications, sensor based techniques are widely adopted. Such systems are termed as People Centric Sensing Systems, which become very popular and acquires greater attention of researchers recently. However, security and privacy in transmitting data has been the major issue in People Centric Sensing Network (PCSN). For handling that problem efficiently, this paper presents a model called Security Data Aggregation and Integrity Verification (SDA-IV) model for providing privacy preserved data sharing between devices in PCSN. A new peer-to-peer oriented secure data sharing is achieved with the proposed model by making the user to shares their data randomly with other nodes along with the incorporating of integrity checking conceit. Moreover, the work comprises four phases: Initial Setup, Data Division and Encryption, Data Aggregation and Integrity Verification. Homomorphic Message Authentication Code is user for privacy preserving process and Hashing Functions are incorporated for integrity verification of shared data. Furthermore, the efficiency of the proposed SDA-IC model is evidenced using simulation results and comparative evaluations.

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Section: Experiments and Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Towards Developing Secure Data Aggregation with Integrity Verification Model (SDA-IV) in People Centric Sensing Systems

2019

IJEAT

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“…Further, the model was not attacks resistive. The survey work presented in [7], [8] and [9] discussed about the adversaries and countermeasures for various attacks on urban sensing network. The attack models and mitigation techniques were discussed with effective data distribution strategies [11].…”

Section: Related Workmentioning

confidence: 99%

A Reliable Cloud Based Framework for Large Scale Urban Sensing Systems

Jansi

Sandhia

KasmirRaja

2021

Advances in Parallel Computing

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The rising usage of smartphones and sensing models in today’s life induces the development of large scale urban sensing networks in communication concepts. With the efficient implementation of people centric mobility models, the personal communication devices of people are acting as the sensor nodes that are capable of sensing the human behaviours and participating in framing the smart protocol designs for smart cities. Without the involvement of mobile users or people, the new protocols for mobility management, traffic management, environmental sensing and other applications become futile. The proposed cloud based model improves the reliability and scalability of the system with its multiple cloud servers design. The single point of failure can be resisted since many cloud servers belonging to a provider is used. So the framework remains fault tolerant in the presence of any server attacks. A standard homomorphic based encryption scheme is used for providing data confidentiality and also data is transferred anonymously improving the privacy of the system. The data aggregation process is supported by the model protecting the user’s privacy. The performance analysis for the proposed framework is done in terms of design goal analysis and computation cost analysis.

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Secure Data Aggregation Model for People Centric Sensing Networks

Jansi

2022

Smart Innovation, Systems and Technologies

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Efficient privacy-preserving fault tolerance aggregation for people-centric sensing system

Cited by 8 publications

References 15 publications

Towards Developing Secure Data Aggregation with Integrity Verification Model (SDA-IV) in People Centric Sensing Systems

Towards Developing Secure Data Aggregation with Integrity Verification Model (SDA-IV) in People Centric Sensing Systems

A Reliable Cloud Based Framework for Large Scale Urban Sensing Systems

Secure Data Aggregation Model for People Centric Sensing Networks

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