Encryption for Implantable Medical Devices Using Modified One-Time Pads

Zheng, Guanglou; Fang, Gengfa; Shankaran, Rajan; Orgun, Mehmet A.

doi:10.1109/access.2015.2445336

Cited by 55 publications

(30 citation statements)

References 34 publications

(46 reference statements)

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“…There are many ways to extract bits from each feature [3], [5]. In this algorithm, we use the method proposed in our previous paper [7]. It has four steps: Simple Moving Average (SMA) process, Gray coding, removal of the Least Significant Bit(LSB) and parity check.…”

Section: Stage 2: Bs Generation Processmentioning

confidence: 99%

“…Therefore, it cannot be utilized within a WBAN sensor which is constrained by limited resources in terms of memory, battery and computation capability [5]. Nonetheless, it has been proposed that random BSes can be generated from ECG signals and are used for facilitating symmetric key distribution [3], [4], authentication [6], or as symmetric keys directly [5], [7], [11]. This ECG-based security approach benefits WBANs, especially Implantable Medical Devices (IMDs).…”

mentioning

confidence: 99%

“…One ECG-based security mechanism is to generate random binary sequences from ECG signals [3]- [7]. A binary sequence (BS) is a sequence of N bits and each bit has a value of 0 or 1.…”

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confidence: 99%

“…Currently ECG-based BSes are typically randomly generated by processing Inter-pulse Intervals (IPIs) of ECG signals [3]- [7]. IPIs are defined as time intervals between two consecutive heartbeats and are proven to be a random source [4].…”

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confidence: 99%

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Multiple ECG Fiducial Points-Based Random Binary Sequence Generation for Securing Wireless Body Area Networks

Zheng

Fang

Shankaran

et al. 2017

IEEE J. Biomed. Health Inform.

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Generating random binary sequences (BSes) is a fundamental requirement in cryptography. A BS is a sequence of N bits, and each bit has a value of 0 or 1. For securing sensors within wireless body area networks (WBANs), electrocardiogram (ECG)-based BS generation methods have been widely investigated in which interpulse intervals (IPIs) from each heartbeat cycle are processed to produce BSes. Using these IPI-based methods to generate a 128-bit BS in real time normally takes around half a minute. In order to improve the time efficiency of such methods, this paper presents an ECG multiple fiducial-points based binary sequence generation (MFBSG) algorithm. The technique of discrete wavelet transforms is employed to detect arrival time of these fiducial points, such as P, Q, R, S, and T peaks. Time intervals between them, including RR, RQ, RS, RP, and RT intervals, are then calculated based on this arrival time, and are used as ECG features to generate random BSes with low latency. According to our analysis on real ECG data, these ECG feature values exhibit the property of randomness and, thus, can be utilized to generate random BSes. Compared with the schemes that solely rely on IPIs to generate BSes, this MFBSG algorithm uses five feature values from one heart beat cycle, and can be up to five times faster than the solely IPI-based methods. So, it achieves a design goal of low latency. According to our analysis, the complexity of the algorithm is comparable to that of fast Fourier transforms. These randomly generated ECG BSes can be used as security keys for encryption or authentication in a WBAN system.

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Section: Stage 2: Bs Generation Processmentioning

confidence: 99%

mentioning

confidence: 99%

“…One ECG-based security mechanism is to generate random binary sequences from ECG signals [3]- [7]. A binary sequence (BS) is a sequence of N bits and each bit has a value of 0 or 1.…”

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confidence: 99%

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confidence: 99%

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Multiple ECG Fiducial Points-Based Random Binary Sequence Generation for Securing Wireless Body Area Networks

Zheng

Fang

Shankaran

et al. 2017

IEEE J. Biomed. Health Inform.

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“…Related works have studied the expected disparity due to VAR is for different types of cardiac recordings: 1) ECGcPPG: One identifier is generated from an ECG (chest) and another from a cPPG recording (finger) [2], [5]; 2) ECG-BP: One identifier is generated from an ECG (chest) and another from a blood-pressure recording (finger) [2], [5]; and 3) ECG-ECG: Both identifiers are obtained from ECG recordings (on the chest) [3], [25]. We present the average bit-error rate (BER) found in each of these studies in Table I (for the 6 leastsignificant IPI bits).…”

Section: A Trusted-identifier Disparitymentioning

confidence: 99%

Attacks on Heartbeat-Based Security Using Remote Photoplethysmography

Seepers

Wang

Haan

et al. 2018

IEEE J. Biomed. Health Inform.

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Attacks on heartbeat-based security using remote photoplethysmographySeepers, R.M.; Wang, W.; de Haan, G.; Sourdis, I.; Strydis, C. • A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Abstract-The time interval between consecutive heartbeats (interpulse interval, IPI) has previously been suggested for securing mobile-health (mHealth) solutions. This time interval is known to contain a degree of randomness, permitting the generation of a time-and person-specific identifier. It is commonly assumed that only devices trusted by a person can make physical contact with him/her, and that this physical contact allows each device to generate a similar identifier based on its own cardiac recordings. Under these conditions, the identifiers generated by different trusted devices can facilitate secure authentication. Recently, a wide range of techniques have been proposed for measuring heartbeats remotely, a prominent example of which is remote photoplethysmography (rPPG). These techniques may pose a significant threat to heartbeat-based security, as an adversary may pretend being a trusted device by generating a similar identifier without physical contact, thus bypassing one of the core security conditions. In this paper, we assess the feasibility of such remote attacks using state-of-the-art rPPG methods. Our evaluation shows that rPPG has similar accuracy as contact PPG and, thus, forms a substantial threat to heartbeat-based-security systems that permit trusted devices to obtain their identifiers from contact PPG recordings. Conversely, rPPG ca...

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