Extraction and analysis of non-volatile memory of the ZW0301 module, a Z-Wave transceiver

Badenhop, Christopher W.; Ramsey, Benjamin W.; Mullins, Barry E.; Mailloux, Logan O.

doi:10.1016/j.diin.2016.02.002

Cited by 22 publications

(17 citation statements)

References 4 publications

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“…Due to their proprietary nature, further knowledge of Z-Wave signal characteristics is limited and thus digital forensic analysis, c.f. [36], [37], of ZWave devices remains an emerging area of interest [38]. …”

Section: Rf-dna and Z-wavementioning

confidence: 99%

An Optimization Framework for Generalized Relevance Learning Vector Quantization with Application to Z-Wave Device Fingerprinting

Bihl¹,

Temple²,

Bauer³

2017

Proceedings of the 50th Hawaii International Conference on System Sciences (2017)

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Section: Rf-dna and Z-wavementioning

confidence: 99%

An Optimization Framework for Generalized Relevance Learning Vector Quantization with Application to Z-Wave Device Fingerprinting

Bihl¹,

Temple²,

Bauer³

2017

Proceedings of the 50th Hawaii International Conference on System Sciences (2017)

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“…The study [18] is focusing on the influences, which generally influence the reliability of equipment used in the wireless ISM band. Some studies, for example, the study [19], are focusing on pitfalls of the cyberattacks on the Z-Wave equipment. The study [20] describes in detail the discovered vulnerability of the door locks Z-Wave through interception of communication and subsequently injecting these obtained data to the communication channel.…”

Section: Resultsmentioning

confidence: 99%

Integration of Fibaro system to intruder and hold-up alarm systems

Kadeřábek¹

2017

Engineering for Rural Development

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Abstract. The Fibaro is a system for automation of smart households, which ensures not only the functions of comfort and power saving, but it also offers the security functions. These security functions were checked and examined in this paper from several perspectives. The evaluation of two submitted model realizations of Intruder and Hold-Up Alarm Systems (I&HAS) with using of the Fibaro system was presented: the Proprietary model, which works with manufacturers' detectors, and the Integration model including the standard loop I&HAS to the Fibaro system. These comfort functions were examined in this paper from the point of view of the functional safety and fulfillment of the normative requirements for the I&HAS. The examination of functional reliability consisted of verification of the ability of the control unit to correctly respond to changes in detection conditions inducted through the relevant sensor. The functional tests were conducted in several steps. Thanks to the functional tests the unreliability of the control unit Fibaro HC Lite to register a larger number of detection messages had to be confirmed. The result of this work was the demonstration of inappropriateness of utilisation of installations according to the Proprietary model. Simultaneously the Integration model was evaluated from a point of view of valid norms with assigning of the first security level, however, the conditions unaffected the I&HAS.

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“…Once an NDA is in place, hardware and software to develop Z-Wave devices are provide by Sigma Designs [10]. While Sigma Designs will provide examples to vendors who sign an NDA, without a signed NDA specific characteristics of the protocol are unknown [10]. The protocol describes general physical layer (PHY) and medium access layer characteristics, but the routing and application layer specifications are protected by the NDA enforced by Sigma Designs [10].…”

Section: Z-wave Devicesmentioning

confidence: 99%

“…However, to produce a Z-Wave device, vendors must coordinate with Sigma Designs and sign a Non-Disclosure Agreement (NDA) to gain access to the proprietary details of the Z-Wave standard. Once an NDA is in place, hardware and software to develop Z-Wave devices are provide by Sigma Designs [10]. While Sigma Designs will provide examples to vendors who sign an NDA, without a signed NDA specific characteristics of the protocol are unknown [10].…”

Section: Z-wave Devicesmentioning

confidence: 99%

See 1 more Smart Citation

Multivariate Stochastic Approximation to Tune Neural Network Hyperparameters for Criticial Infrastructure Communication Device Identification

Bihl¹,

Steeneck²

2018

Proceedings of the 51st Hawaii International Conference on System Sciences

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Extraction and analysis of non-volatile memory of the ZW0301 module, a Z-Wave transceiver

Cited by 22 publications

References 4 publications

An Optimization Framework for Generalized Relevance Learning Vector Quantization with Application to Z-Wave Device Fingerprinting

An Optimization Framework for Generalized Relevance Learning Vector Quantization with Application to Z-Wave Device Fingerprinting

Integration of Fibaro system to intruder and hold-up alarm systems

Multivariate Stochastic Approximation to Tune Neural Network Hyperparameters for Criticial Infrastructure Communication Device Identification

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