Aggregation and perturbation in practice: Case-study of privacy, accuracy &amp;amp; performance

Pöhls, Henrich C.; Mossinger, Max; Petschkuhn, Benedikt; Rückert, Johannes

doi:10.1109/camad.2014.7033231

Cited by 2 publications

(2 citation statements)

References 4 publications

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“…As a case study on real-life energy consumption data notes: "simple presence detection is still feasible on the processed data set, more detailed inferences requiring higher temporal or energy-level details are clearly aggravated." [73]. Thus, a loss of data quality occurring could be a privacy gain whenever it does not harm the intended functionality in the back-end.…”

Section: Minimizing Data Collectionmentioning

confidence: 99%

What it takes to boost Internet of Things privacy beyond encryption with unobservable communication: a survey and lessons learned from the first implementation of DC-net

Staudemeyer

Pöhls

Wójcik

2019

J Reliable Intell Environ

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Privacy requires more than just encryption of data before and during transmission. Privacy would actually demand hiding the sheer fact that communication takes place. This requires to protect meta-data from observation. We motivate the need for strong privacy protection in a smart home use case by highlighting the privacy issues that cannot be solved by confidentiality mechanisms like encryption alone. Our solution is a implementation of DC-net on Re-Mote sensor nodes running Contiki OS. From this, we conclude that the computational and network overheads imposed by these techniques do not make them impractical to use in the IoT. To the best knowledge of the authors, this is the first implementation of DC-net on sensors. Alongside, we provide a survey of the required strong cryptographic security mechanisms, like encryption of communication, to be in place. We describe how the current existing techniques can be facilitated to achieve unobservable communication for the IoT. This includes mechanisms for encrypted IoT communication like DTLS or message authentication like ECDSA signatures on IoT devices. For readers unfamiliar with the concepts of MIXing and DC-net, we explain and analyse how those techniques, formerly used to provide private communication in the Internet, can be applied to the IoT. We briefly survey what complementary features from the IoT architecture are helpful in providing strong protection in this particular use case. Finally, we state some recommendations hoping that following these will enable us to reduce the privacy invasiveness of the IoT on all levels. We think that this will be indispensable if IoT devices shall become a part of our daily lives without rendering us into an Orwellian society.

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Section: Minimizing Data Collectionmentioning

confidence: 99%

What it takes to boost Internet of Things privacy beyond encryption with unobservable communication: a survey and lessons learned from the first implementation of DC-net

Staudemeyer

Pöhls

Wójcik

2019

J Reliable Intell Environ

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“…The algorithms done grouping of likely smart meters that are likely to communicate so that the CRLs will be kept local to that group. Pohls et al (2014) analysed accuracy, privacy, compression-ratio and computational overhead of selected aggregation and perturbation methods in the Internet of Things (IoT) so as to detect possibility of predictions and intelligent reactions with lower quality data. In Lei et al (2007), it was shown that it was possible to effectively and efficiently track the correlation and autocorrelation structure of multi-variant streams and use it to perturb the stream data to preserve privacy.…”

Section: Related Workmentioning

confidence: 99%

Secure and privacy-oriented obfuscation scheme for smart metering in smart grid via dynamic aggregation and lightweight perturbation

Olakanmi

2017

IJIPSI

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Smart metering in smart grid system has raised several condemnations based on its security and privacy invasiveness. The major techniques adopted to mitigate the security and privacy invasions of smart metering are aggregation and perturbation. However, aggregating smart meters' measurements is not enough to secure or preserve the privacy of consumers in either spatial or temporal metering. More so, the existence of perfect perturbation technique which can efficiently reconstruct data during the reconstruction phase has been a major challenge in existing perturbation schemes. In this paper, a scheme that combines aggregation and perturbation to secure smart meters' measurements and preserve consumer privacy is proposed. The scheme dynamically changes the topology and direction of aggregation in neighbourhood area network during spatial and temporal aggregation. It efficiently combines perturbation and aggregation techniques. A novel perturbs generation method was proposed for the perturbation scheme with dynamic constraint-based topology generation method. The simulation results showed that the scheme not only prevented gleaning of the metering but made it difficult for the adversary to perform pre-target attack on any of the smart meters in the network.

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Aggregation and perturbation in practice: Case-study of privacy, accuracy & performance

Cited by 2 publications

References 4 publications

What it takes to boost Internet of Things privacy beyond encryption with unobservable communication: a survey and lessons learned from the first implementation of DC-net

What it takes to boost Internet of Things privacy beyond encryption with unobservable communication: a survey and lessons learned from the first implementation of DC-net

Secure and privacy-oriented obfuscation scheme for smart metering in smart grid via dynamic aggregation and lightweight perturbation

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