A Survey Study of the Current Challenges and Opportunities of Deploying the ECG Biometric Authentication Method in IoT and 5G Environments

Ahmed Younes Shdefat, Nour Mostafa, Louai Saker, Ahmet Topcu
2021 Indonesian Journal of Electrical Engineering and Informatics (IJEEI)  
The environment prototype of the Internet of Things (IoT) has opened the horizon for researchers to utilize such environments in deploying useful new techniques and methods in different fields and areas. The deployment process takes place when numerous IoT devices are utilized in the implementation phase for new techniques and methods. With the wide use of IoT devices in our daily lives in many fields, personal identification is becoming increasingly important for our society. This survey aims
more » ... o demonstrate various aspects related to the implementation of biometric authentication in healthcare monitoring systems based on acquiring vital ECG signals via designated wearable devices that are compatible with 5G technology. The nature of ECG signals and current ongoing research related to ECG authentication are investigated in this survey along with the factors that may affect the signal acquisition process. In addition, the survey addresses the psycho-physiological factors that pose a challenge to the usage of ECG signals as a biometric trait in biometric authentication systems along with other challenges that must be addressed and resolved in any future related research. 120 During the COVID-19 pandemic, IoT devices such as smartphones with embedded sensors using machine learning techniques have intelligently helped track COVID-19 patients using real-time data utilization [6] . Lampropoulos et al. [7] presented detailed survey results regarding IoT industrial applications that affect industrial developments and trends. The number of smart factories, for example, is expected to increase dramatically in the upcoming years with new trends of manufacturing that depend on smart IoT devices, inevitably moving in the direction of modeling human-free and robot-controlled factories. Another report [8] indicated that healthcare services will be more vigorous on the heels of the COVID-19 pandemic. Robust services in healthcare systems may be provided by IoT-based solutions such as remote patient control, robots, and others, especially in quarantined hospitals. Data generated from these devices can then be conveyed to medical systems in order to handle situations and obtain accurate results using machine learning [9] . At the same time, the number of smartphone users is increasing massively every year. According to one report [10], recent statistics show that the number of smartphone device users exceeded 3.5 billion in 2020 and is expected to surpass 3.8 billion in 2021. At this rate, the current mobile network infrastructure using fourth generation (4G) or Long-Term Evolution (LTE) technology will not be able to support all of the newly produced devices with IP addresses to be attached to the network to communicate actively due to the limited nature of the currently used communication protocol in the networking field, which is IPV4 [11] . In addition, as more devices are connected to the network and actively communicating, more latency and delay will occur, causing low-quality telecommunication services for users [12] , [13] . Considering the fundamental point of the IoT, which makes everything connected, including heterogeneous things like the future's high volume of smartphone devices, computing devices, appliances, sensors, and objects, a demand is being created for infrastructure with enhanced data rates, more bandwidth, better capacity, minimized latency, and better quality of service [14] . Pervasive interactions between heterogeneous objects such as smart autonomous cars, sensors, appliances, and smartphones within the environments of smart homes, smart cities, and smart grids are triggering the issue of channel access for various heterogeneous objects via different applications, such as medical monitoring applications using vital signs and security applications using biometric authentication methods [15] . The current LTE or 4G infrastructure will be crippled under this load and will not be able to meet the vital IoT demands of making everything within the IoT environment connected through a reliable network, especially while attempting to handle the produced data traffic that will result from the interactions between these connected devices [11], [12]. In order to meet these demands and build a stable and reliable IoT environment, telecommunication companies, researchers, and educational institutions have started to explore alternative advanced technology infrastructures to meet the IoT demands [14] . The fifth generation (5G) of wireless communications technologies supporting cellular data networks has emerged as a proposed solution to resolve 4G limitations in meeting the demands of the IoT environment infrastructure. Therefore, 5G now represents the backbone of the IoT environment. In 5G architecture, there are three frequency spectrums: millimeter waves, mid-band, and low-band. The millimeter wave download speed ranges from 1 to 2 Gbit/s with frequencies above 24 GHz and below 72 GHz; the optimal frequency is 28 GHz. In the mid-band 5G case, download speeds are in the range of 100-400 Mbit/s with frequencies from 2.4 to 4.2 GHz. Finally, the lowband 5G frequency spectrum is identical to the one currently used for 4G [16]. This survey investigates the different biometric authentication methods deployed within the 5G IoT infrastructure in general and the electrocardiogram (ECG) biometric authentication method in particular. Biometrics are defined as biological measurements or recordings of physical characteristics, such as fingerprint mapping, iris scanning, face recognition, behavioral characteristics, and voice recognition, which are used by an authentication system to identify and verify individuals and/or objects [17] . Biometric authentication systems are growing in complexity, as they have to handle ever-greater numbers of wearable devices, which are becoming an extended part of our bodies. Therefore, there is an increasing demand for an automatic and reliable authentication system. In the last decades, the above-mentioned biometric systems have been considered as reliable paradigms [18], [19] . Biometric data types vary, but the most popular types are explained below. The current trends for smart devices, including smartphones, wearable devices, and voice automatic assistant services, involve using voice interactions rather than traditional touch interfaces to perform many tasks including, but not limited to, making phone calls, sending messages, checking emails, performing banking services, and using driver assistant services [20] . In addition, vocal features may be used in voice biometric authentication. However, most of the current applications use this mechanism as a voice assistant, not as an authentication method, because it is difficult to secure, in addition to its vulnerability and exposure to many threats [21], [22] . Fingerprinting is used as a biometric method to identify the unique patterns of ridges and valleys on fingers. Sir William Herschell was the first to note the value of fingerprints for identification [23] , [24] . From the beginning of the twentieth century, the fingerprint was acknowledged as the most permanent biometric trait
doi:10.52549/ijeei.v9i2.2890 fatcat:cvfkcwspvbf2hdcawv4xbxpm34