Digital watermarking of ECG data for secure wireless communication

Suneet Kaur Dept. of electronics

ZHCET, AMU. Aligarh (UP), India

suneet_2788@yahoo.com

Riya Singhal Dept. name of electronics

ZHCET, AMU. Aligarh (UP), India

rs20.riya@gmail.com

Dr. Omar Farooq Dept. name of electronics

ZHCET, AMU. Aligarh (UP), India

omarfarooq70@gmail.com

Bhavneet Singh Ahuja Dept. name of electronics

ZHCET, AMU. Aligarh (UP), India

bhavneetsingh@zhcet.ac.in

Abstract— Use of wireless technology has made the bio-medical data vulnerable to attacks like tampering, hacking etc. This paper proposes the use of digital watermarking to increase the security of an ECG signal transmitted through a wireless network. A low frequency chirp signal is used to embed watermark which is patient’s identification taken as 15 digit code. The characteristic of the proposed watermarking scheme is that the blind recovery of the watermark is possible at the receiver and the embedded watermark can be fully removed. Hence, ECG can be viewed by a clinician with zero distortion which is an essential requirement for bio-medical data. Further, tampering such as noise addition and filtering attack can also be detected at the receiver.

Index Terms—Blind Recovery, Chirp, Digital Watermarking, ECG, Tampering.

Introduction Watermarking is a process by which a discrete data stream called a watermark is hidden within a host signal by imposing imperceptible changes on the signal. Although current information hiding techniques were primarily developed for applications such as multimedia copyright protection, they may be quite suitable for bio-medical signal authentication as well. Throughout these techniques the embedded data will be ‘invisible’ to maintain the quality of the host data. Due to the recent explosion of identity theft cases, the safeguarding of private data has been the focus of many scientific efforts. In the years to come, healthcare systems are expected to experience a drastic change in its structure and organization as indicated, for example, in the Healthcare 2015 report showing that governments, health regions, hospitals are allotting billions of dollars into multiple medical initiatives [1]. As the volume of health care data increases, more complex, storage and accessibility of medical information is not only invaluable but also necessary. One of the major technological and ethical issues governing electronic records is the issue of data privacy. Protection from unauthorized access on medical history data and personal patient data is something that can not only

protect a patient's private data from identity theft schemes but can also can safeguard the healthcare and insurance system from fraudulent claims. Watermarking has been implemented both on audio, images as well as video by using various methods like Fourier transform, wavelet transform and scheme based on independent component analysis [2,3,4].

I. DIGITAL WATERMARKING Digital watermarking is an adaptation of the commonly used and well-known paper watermarks to the digital world. Digital watermarking describes methods and technologies that allow hiding of information in digital media. The hiding process is to be such that the modifications of the media are imperceptible. There are several properties that a watermarking scheme (or a watermark) should have are as:

A. Imperceptibility

A watermark that is embedded into a certain kind of media should not be perceptible as far as possible because if it is perceptible then it will degrade the features of the original content which is undesirable.

B. Readability The watermark should not be readable so that statistical methods to detect the watermark can’t be used. Good unread ability also ensures the good copyright protection.

C. Low Complexity

The watermarking scheme should be as low complex as possible so that it can be applied over the real time applications. Also low complexity makes the watermarking scheme economical, which also one of our big requirement.

D. Security

A watermark should be secret and must be undetectable by an unauthorized user in general. A watermark should only be

2010 International Conference on Recent Trends in Information, Telecommunication and Computing

978-0-7695-3975-1/10 $25.00 © 2010 IEEE

DOI 10.1109/ITC.2010.96

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accessible by authorized parties. This requirement is regarded as security and the watermark is usually achieved by the use of cryptographic keys [2]. As information security techniques, the details of a digital watermark algorithm must be published to everyone. The owner of the intellectual property media is the only one who holds the private secret keys. Digital watermarking allows to mutually link information on the documents. That means that some information is written twice on the document: for instance, the name of a passport owner is normally printed in clear text and is also hidden as an invisible watermark in the photo of the owner. If anyone would intend to counterfeit the passport by replacing the photo, it would be possible to detect the change by scanning the passport and verifying the name hidden in the photo does not match any more the name printed on the passport. In our case, we have also embedded patient’s identification by two different ways. Both can be obtained at receiver's side and compared to find tampering.

The watermark used for watermarking purpose has to be robust or fragile, depending on the application [5,6,7]. With robustness we refer to the capability of the watermark to resist to manipulations of the media, such as lossy compression, scaling, and cropping, just to enumerate some. Fragility means that the watermark should not resist tampering, or only up to a certain extent in case of semi fragile watermarks [6]. Robust watermarks are generally used for copyright and ownership verification. In comparison, fragile watermarks are useful for purposes of authentication and integrity attestation as in case of biomedical signals. It is also desirable to have a watermark extraction process that is ‘blind’, implying that the original ‘host signal’ is not required to extract the watermark. In this paper we propose a simple watermark embedding algorithm using chirp signal which has a capability of blind recovery. The watermark extraction can be carried out under high noise background environment. The proposed water marking scheme gives dual benefits, first, it carries patient's identification and second, it detects the attacks if any alteration is done.

II. PROPOSED WATERMARKING SCHEME The concept involves watermarking of the ECG signal using the 8-bit chirp signal. In the proposed scheme, chirp used is ‘quadratic’, where instantaneous frequency sweep ( )tfi is given by

( ) 20 tftfi β+= (1)

Where ( ) 2101−−= tffβ

Fig. 1: The chirp sequence to be embedded for a given

Watermark sequence of ‘0110010 Each sample of ECG is quantized using 10 bits. The ECG signal is divided into frames using a rectangular window of size equal to length of chirp signal[8]. To each bin of ECG signal modulated chirp signal is added. The chirp signal is modulated according to the ‘patient ID.’, which is exclusive for each individual

( )jchirpchirp bfyy *mod, = (2)

where jb =jth bit of the patient ID in binary format

( )⎩⎨⎧

=−=

=0 where11 where1

xx

xf (3)

chirpy is the chirp signal and mod,chirpy is modulated chirp

according to jb . For a bit ‘1’ to be embedded the chirp added will be in phase and for ‘0’ it will be out of phase to the ECG signal. A chirp signal for a watermark sequence ‘0110010’ is shown in Figure 1. In order to make the system less vulnerable to errors, the ‘patient ID’ is spread to a certain factor. Spreading factor (u) is defined as the number of times each bit of watermark is embedded (for e.g.- if u=3 then three in phase chirps will be embedded for bit ‘1’ and three out of phase chirps will be embedded for bit ‘0’). Spreading factor is chosen to exploit the maximum payload capacity. The watermark sequence is a binary stream, dependent on patient’s personal data which is unique. Now, to balance between the recovery capability of the watermark and its perceptibility, a ‘k factor’ is included which is dependent on the required signal to chirp ratio (SCR) (4). The modulated chirp is multiplied with window-dependent ‘k’ and then added to the ECG signal, resulting in the watermarked ECG signal with each sample of 11-bits.

⎟⎟⎠

⎞⎜⎜⎝

⎛=

chirpi

idesired Pk

PSCR*

log10 (4)

where, iP is ECG signal power of ith window and chirpP is the power of the chirp signal.

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Fig. 2: Watermark embedding scheme for ECG signal.

Fig. 3: Watermark extraction scheme from the ECG signal. Each sample of final signal is of 16-bit with first 11-bits as watermarked signal and in the remaining 5-bits ‘k’ and ID are embedded. This makes it a zero distortion watermark embedding scheme i.e. at the receiver one can separate the watermark, hence the patient’s ID and the original ECG signal. From the received signal the bits of 'k' and 'ID' are extracted. The extracted ‘ID’ facilitates in the detection of any alteration in the received ECG signal. The extracted ‘k’ is used to get the replica of original signal at the receiver side. These bits are removed to get the 'watermarked signal'. It is then correlated with the chirp signal of same specifications as in encryption to find the ID. This ID is used to modulate the chirp signal using the same procedure as in encryption. It is then multiplied by extracted 'k' factor. To recover the original undistorted ECG signal, it is then subtracted from the obtained watermarked signal. The ID obtained from correlation is compared with extracted ID. This comparison enables the receiver for verification of the ECG signal. If they are not equal then it indicates that some tampering has been done.

III. RESULTS AND DISCUSSIONS

A. In this paper we have analyzed an ECG signal, sampled at a frequency of 256 Hz. A chirp signal of a quadratic swept-frequency cosine signal with the frequency sweep, 0 to 100 Hz, generated for 0.5 second duration. A 15 digit patient ID is used for modulation, say 012345678901234.Blind Recovery of ECG

One of the prerequisite as far as biomedical signals are concerned is that the signal does not undergo any change in

the process of encryption, watermarking, and decryption. The algorithm proposed in this paper satisfies this criterion. We have successfully done the BLIND RECOVERY of the ECG signal for SCR<=10 (SCR=signal to chirp ratio) dB for the specified spreading factor.

B. Attacks 1) Noise: During transmission over a channel or due to

interference, any undesirable noise added can be efficiently detected using the proposed algorithm. Also, the watermark embedded can be successfully recovered. The algorithm works proficiently even under high noise conditions. This is due to the inherent advantages associated with the chirp signal used for watermarking the ECG. Any change in ECG is undesirable. Even at low noise, any such distortion in the ECG signal can be detected. For SNR= 1dB, status displayed: ‘tampered’; erroneous bits per second i.e. bit error rate (BER) =0. At noise power comparable to the ECG signal power, the watermark can be successfully recovered. For SNR=80dB, status displayed: ‘tampered’; BER =0. The proposed algorithm can detect the injection of very low noise (i.e. tampering detection) into the watermarked signal; also the patient’s ID can be successfully recovered.

2) Filtering Distortion arising in the watermarked ECG signals because of low pass filtering or high pass filtering can be detected .It results in erroneous recovery of id which indicates ‘tampering’. In fig.6 LPF characteristics and signals obtained are shown.

C. ID Authentication With the proposed watermarking scheme, ID in most of cases can be detected successfully. The significance of ID retrieval is that, at the receiver side, we can find from the ECG itself to which patient it belongs. Hence any chance of fraudulent ECG or fault in this respect can be minimized.

IV. CONCLUSIONS In this paper, a simple technique for watermarking of biomedical signals (ECG) is presented. The scheme highlights on “Blind Recovery” of the original signal from the watermarked signal. Through this method one can also conceal the information about the patient’s ID which can further be used for detection of any corruption of the original signal. Another novelty of the proposed scheme is its ability to remove the watermark completely from the recovered ECG signal and display it to the clinicians without distortion.

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Fig.5: for LPF (normalized cut off freq= 60Hz): status displayed: ‘tampered’; BER =24

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1-10

-5

0

5x 10

4

Normalized Frequency (×π rad/sample)

Pha

se (

degr

ees)

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 150

100

150

Normalized Frequency (×π rad/sample)

Mag

nitu

de (

dB)

0 50 100 150 200 250 300 350 400 450 500-1000

0

1000ORIGINAL ECG SIGNAL

0 50 100 150 200 250 300 350 400 450 500-1000

0

1000WATERMARKED SIGNAL

0 50 100 150 200 250 300 350 400 450 500-5

0

5x 10

4 RECOVERED SIGNAL

0 50 100 150 200 250 300 350 400 450 500-5

0

5x 10

4 ERROR

Fig. 4 : for SCR=9dB

Fig.6 performance for noise of SNR=80dB

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V. REFERENCES 1. Vlachos, Michail, Yu, S. Philip, “Systems and Methods

for Metadata Embedding in Streaming Medical Data” 9August 2009

2. B. S. Ko, R. Nishimura and Y. Suzuki, “Time-spread Echo Method for Digital Audio Watermarking”, IEEE Transactions on Multimedia, 7(2), 2005,pp. 212-221.

3. H. O. Oh, J. W. Seok, J. W. Hong and D. H. Youn, “New Echo Embedding Technique for Robust and Imperceptible Audio Watermarking”, Proc. ICASSP 2001,pp.1341-1344.

4. Bao P, Xiaohu M. ‘‘Image adaptive watermarking using wavelet domain singular value decomposition’’, IEEE Trans. Circuits Syst. Video Technol 2005; Vol 15(1),pp. 96---102.

5. Y. W. Liu and J. O. Smith, “Watermarking Sinusoidal Audio Representations by Quantization Index Modulation in Multiple Frequencies”, Proc. of ICASSP 2004, Vol. 5, pp.373-376.

6. D. Kirovski and H. S. Malvar, “Spread-Spectrum Watermarking of Audio Signals, IEEE Transactions on Signal Processing”, Vol. 51(4), 2003,pp. 1020-1033.

7. Zou D, Shi YQ, ZN, Su W. ‘‘A semi-fragile lossless digital watermarking scheme based on integer wavelet transform’’, IEEE Trans Circuits System Video Technology 2006, Vol. 16(10),pp. 1294---300.

8. O. Farooq, S. Datta and J. M. Blackledge, “Blind Tamper Detection in Audio using Chirp based Robust Watermarking”, WSEAS Transactions on Signal Processing, 4(4), April 2008, 190-200.

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