| Literature DB >> 34690480 |
J Vijitha Ananthi1, P Subha Hency Jose1.
Abstract
Body area network (BAN) connects sensors and actuators to the human body in order to collect patient's information and transmitting it to doctors in a confined space with limited users. wireless body area network (WBAN) is derived from wireless sensor networks (WSN) and enables to transfer of the patient's information with a wide range of communication due to the limitations of the wired body area network. It plays a vital role in healthcare monitoring, healthcare systems, medical field, sports field, and multimedia communication. Sensors and actuators lead to high energy consumption due to their tiny size. WBAN facilitates in securely storing patient information and transmitting it to the doctor without data loss at a specific time. This review examines and summarizes methodological approaches in WBAN relating to security, safety, reliability, and the fastest transmission. Flying body area networks (FBAN) utilizing unmanned aerial vehicles for data transmission are recommended to promote rapid and secure communication in WBAN. FBAN improve the security, scalability, and speed in order to transmit patient's information to the doctor due to high mobility.Entities:
Keywords: Body area networks (BAN); Energy consumption; Flying body area networks (FBAN); Remote healthcare monitoring; Security limitations; Wireless body area networks (WBAN)
Year: 2021 PMID: 34690480 PMCID: PMC8522540 DOI: 10.1007/s10776-021-00538-3
Source DB: PubMed Journal: Int J Wirel Inf Netw ISSN: 1068-9605
Fig. 1Wireless body area network architecture
Fig. 2WBAN architecture
Fig. 3WBAN applications
Comparison of security techniques in WBAN
| Author[s] | Technique | Research issues | Methodology | Outcome |
|---|---|---|---|---|
| Bengag et al. [ | Intrusion detection system | Jamming Attacks | Two MAC Protocols involved (ZIGBEE and TMAC) | Successful packet delivery rate |
| Arya et al. [ | IoT based e-health | Data security | Constant monitoring for critical patients | Data authentication and authorization |
| Al Hayajneh et al. [ | Cloud-based WBAN | Lesser users | Increased storage level | More users and network lifetime |
| Thamilarasu et al. [ | Mobile agent-based IDS | Network-level intrusion attacks | Machine learning and regression algorithms | Accurate results and lesser resource overhead |
| Umar at.al [ | Signal propagation-based mutual authentication | Active and passive network attacks | Enables mutual trust and used seed update algorithm | Minimal routing overhead and less computational cost |
| Dharshini et al. [ | DMASK-BAN | Vulnerable attacks | Secret key extraction with movement aided from DoS attacks | Minimum power consumption with high QoS |
| Suchithra et al. [ | Invariant feature-based approach | High-rate attacks | Maintain the bandwidth conditions in cooperative routing | Low-rate attacks |
| Kumar et al. [ | Identity-based anonymous authentication and key agreement | Several security issues | Cloud technology and wireless communication | High storage and low computation cost |
| Rao et al. [ | Trust management | High residual power | Fuzzy logic technique | Secure and stable performance |
| Ali et al. [ | Enhanced authentication and access control protocol | User impersonation attacks | Bilinear pairing and elliptic curve cryptography | High security |
Comparison of different security approaches in different aspects
| Author[s] | Approaches | Network Utilization | Qualities |
|---|---|---|---|
| Tan et al. [ | PUF based Cloud assisted Lightweight Authentication | Multi-hop BAN | Lesser storage overhead Lesser resource loss Fewer conflict rates Less channel utilization rate Less packet drop rate High delivery rate |
| Demir et al. [ | Cyber-physical systems IWSN Smart Grid WBAN V2X | 6G Networks | Security enhancement Multilayer protection High Network lifetime Low latency High reliability Suitable for real-time implementation |
| Mo et al. [ | The wearable health monitoring system Known session special temporary information Two-factor authentications Key agreement scheme | Wireless sensor networks | High-security features High efficiency Lesser computational cost Lesser communication overhead Lesser traffic computation |
| Amel Zendehdel et al. [ | Telehealth monitoring Bluetooth low energy Wearable device Fingerprinting Vulnerability scanning | Internet of Things | High security High reliability Detection of middleware attacks |
| Kong et al. [ | Smart healthcare systems | WBAN | Improves communication security |
| Jithish et al. [ | Cyber-physical system Markov Decision Process | WBAN | High Energy efficiency Network longevity Défense the dos and deception attacks |
| Vyas et al. [ | Remote health monitoring Health care applications Symmetric key generation Cloud assisted Complex encryption | Wireless communication channels | Intruder identification Improves the security |
| Damasevicius et al. [ | Network flow features Different Attack types Cluster Approaches Cybersecurity domain | Wireless sensor network | Network Intrusion detection |
| Alzahrani et al. [ | Cloud-based IoT Authentication protocols Remote patient health monitoring Session key | WBAN | Avoiding smart card attacks High secure efficiency |
| Irshad et al. [ | Energy internet-based vehicle to grid Cyberattacks The smart grid-based authentication protocol | Wireless network | Lesser computational cost Lesser communication cost |
Developments of WBAN
| Year | Techniques involved | Network utilized | Merits |
|---|---|---|---|
| 2020 | Cloud-based IoT Authentication protocols Remote patient health monitoring Session key Key management | WBAN, Wireless sensor networks, Internet of Things, Wireless networks | Detecting intruders High secure efficiency Less computational cost High-Security features High efficiency Less communication overhead Less traffic computation High security High reliability Detection of middleware attacks |
| 2019 | Biometrics Key management Advanced encryption cipher Elliptical curve digital signatory Secured, anonymity preserving and lightweight mutual authentication and key agreement scheme (SALMAKA) | Wireless body area networks, Wireless sensor networks, Internet of things, Cooperative communication | Authenticity Confidentiality Fewer handover delays Less energy consumption Less computational cost |
| 2018 | Biometrics Third-party key exchange protocol Cloud computing Battery replacement | Sensor network, Body area network, GSM, GPRS | Less energy consumption High security |
| 2017 | Cluster-based detection Cloud assisted intrusion Routing protocols Many surveys were involved | Body area networks based on optical and wireless | Less energy consumption Attacker detection |
| 2016 | Clustering algorithm Encryption Attack’s detection Cloud computing Mutual authentication scheme | WBAN, HBC, Star topology | Network efficiency Less energy consumption High secure communication |
Fig. 4WBAN factors focused for the past 5 years
Fig. 5Future focusing factors of WBAN
Cryptographic Techniques based on obtained results from existing techniques
| Different cryptographic techniques based on obtained results | ||
|---|---|---|
| Techniques | Reliability (%) | Accuracy (%) |
| Biometrics techniques [ | 82 | 78 |
| Key management scheme [ | 79 | 81 |
| Mutual authentication scheme [ | 89 | 85 |
| Session key arrangement scheme [ | 83 | 87 |
| Elliptical curve cryptography [ | 87 | 89 |
| Lightweight Scheme [ | 82 | 83 |
| Trust management scheme [ | 70 | 72 |
Attacker Detection Techniques based on obtained results from existing techniques
| Different attacker detection techniques based on obtained results | |
|---|---|
| Techniques | Delivery rate (%) |
| Spoofing attacker [ | 75 |
| Jamming Attack [ | 72 |
| DoS Attacks [ | 82 |
| Vulnerable attacks [ | 84 |
| High and low-rate attacks [ | 89 |
Fig. 6Comparison of cryptographic techniques
Fig. 7Comparison of attacker detection techniques
Fig. 8Comparison of different techniques