An Efficient, Hybrid Authentication Using ECG and Lightweight Cryptographic Scheme for WBAN

Rehman, Zia ur; Altaf, Saud; Ahmad, Shafiq; Huda, Shamsul; Al-Shayea, Adel; Iqbal, Sofia

doi:10.1109/access.2021.3115706

Cited by 18 publications

(3 citation statements)

References 21 publications

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“…Rehman et al 17 proposed a simple WBAN authentication mechanism for safely transmitting sensitive information over a public channel. The approach uses XOR operations and a hash function to improve its performance.…”

Section: Literature Surveymentioning

confidence: 99%

Hash message authentication codes for securing data in wireless body area networks

Nagasundharamoorthi,

Venkatesan,

Velusamy

2023

Concurrency and Computation

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SummaryThere are numerous medical applications for the growing use of wireless body area networks (WBANs), including remote patient health monitoring, early illness detection, and computer‐assisted rehabilitation. WBAN links many sensor nodes implanted or affixed to the human body to monitor physiological data. WBAN technology has the potential to benefit medical healthcare systems tremendously. However, the gathering and transferring sensitive physiological data in an unprotected environment raises severe security and privacy concerns. The limited resources and broadcast transmission of a WBAN pose grave safety issues in biomedical applications. Keeping sensitive patient data safe during broadcasts is critical in the healthcare business. As a result of the massive memory and processing requirements required by traditional public or private key architectures, tiny sensor nodes cannot use them. WBAN sensor nodes can communicate securely using the KHMAC key‐agreement technique proposed in this article. Measurements and confirmations of shared physiological parameters at the transmitter and recipient sensors are key to the proposed protocol KHMAC before communication is established. The proposed KHMAC protocol enables sensors to use their prior session knowledge for secure communication within a predetermined time window. This will shorten the time it takes to establish a shared key, prevent the retransmission of extracted characteristics in the medium and eavesdropping attacks, and preserve the unpredictability of the key. Both the feature extraction and key agreement stages will be shown to have higher precision and lower error rates with KHMAC's proposed key management methodology. The proposed protocol is proven to be more energy and memory efficient than existing key agreement systems.

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Section: Literature Surveymentioning

confidence: 99%

Hash message authentication codes for securing data in wireless body area networks

Nagasundharamoorthi,

Venkatesan,

Velusamy

2023

Concurrency and Computation

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“…The work evaluates the different security attacks and computational overheads. The hybrid authentication using electrocardiogram (ECG) and block cipher for wireless body area network (WBAN) applications is well described in [20]. The RCIA-based RFID authentication with the logic of events theory (LET) is presented in [21].…”

Section: Introductionmentioning

confidence: 99%

Secured Authentication of RFID Devices Using Lightweight Block Ciphers on FPGA Platforms

2023

IEEE Access

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Near Field Communication (NFC) has emerged as a pivotal wireless technology for short-range data exchange between devices, including smartphones and wearables. Leveraging Radio Frequency (RF) signals and robust authentication, NFC ensures secure communication in proximity. Mutual authentication (MA) holds paramount importance for establishing trust between device pairs. A prime example of NFC technology is Radio Frequency Identification (RFID), wherein seamless communication occurs between a reader and a tag. However, security and privacy concerns are critical factors in RFID systems, necessitating effective authentication protocols. This paper introduces an efficient and secure MA mechanism for RFID devices, using lightweight block ciphers (LBCs). Specifically, the extended tiny encryption algorithm (XTEA) and the hummingbird algorithm (HBA) using the cipher block chaining (CBC) mode is designed. These tailored algorithms establish a secure communication channel between RFID tags and readers. Notably, the proposed RFID-MA using XTEA and HBA occupies less than 2% of the chip area, encompassing slices and lookup tables (LUTs), and achieves authentication with execution times of 11.6 µs and 1.34µs, respectively. In comparison to the RFID-MA approach employing the XTEA methodology, the proposed algorithm reduces the chip area overhead by 24.6%, total power consumption by 3.5%, and execution time by 88.36%. The proposed algorithm is implemented using Verilog hardware description language (HDL) within the Xilinx environment and is realized on a Artix-7 field programmable gate array (FPGA) platform, utilizing the ModelSim simulator. The proposed research extensively presents simulation and synthesis results while considering the critical hardware constraints such as time, power, and area. Furthermore, this study has also conducted a comprehensive performance analysis, comparing essential metrics with existing LBC and authentication methodologies, showcasing substantial improvements.

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“…The authentication solutions pertaining to the anonymous lightweight category [17,18] and hybrid approaches, such as [19], along with other cryptographic schemes and RNN based biometrics schemes, [20] also exist in the literature. However, our main focus is, to sum up, authentication schemes based on ML techniques [21,22].…”

Section: Introductionmentioning

confidence: 99%

Advanced Authentication Scheme with Bio-Key Using Artificial Neural Network

et al. 2022

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The improvements in the field of health monitoring have revolutionized our daily lifestyle by developing various applications that did not exist before. However, these applications have serious security concerns; they also can be taken good care of by utilizing the Electrocardiogram (ECG) as potential biometrics. The ECG provides robustness against forgery attacks unlike conventional methods of authentication. Therefore, it has attained the utmost attention and is utilized in several authentication solutions. In this paper, we have presented an efficient architecture for an advanced authentication scheme that utilized a binarized form (bio-key) of ECG signal along with an Artificial Neural Network (ANN) to enhance the authentication process. In order to prove the concept, we have developed the testbed and acquired ECG signals using the AD8232 ECG recording module under a controlled environment. The variable-length bio-keys are extracted using an algorithm after the feature extraction process. The extracted features along with bio-keys are utilized for template formation and also for training/testing of the ANN model to enhance the accuracy of the authentication process. The performance of authentication results depicted high authentication accuracy of 98% and minimized the equal error rate (EER) to 2%. Moreover, our scheme outperformed comparative peers’ work in terms of accuracy and EER.

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An Efficient, Hybrid Authentication Using ECG and Lightweight Cryptographic Scheme for WBAN

Cited by 18 publications

References 21 publications

Hash message authentication codes for securing data in wireless body area networks

Hash message authentication codes for securing data in wireless body area networks

Secured Authentication of RFID Devices Using Lightweight Block Ciphers on FPGA Platforms

Advanced Authentication Scheme with Bio-Key Using Artificial Neural Network

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