| Literature DB >> 34456514 |
Ripty Singla1, Navneet Kaur2, Deepika Koundal3, Anuj Bharadwaj1.
Abstract
The rise in life expectancy of humans, COVID-19 pandemic and growing cost of medical services has brought up huge challenges for the government and healthcare industry. Due to unhealthy lifestyle, there is an increased need for continual health monitoring and diagnosis of diseases. Wireless Body Area Network (WBAN) is attracted attention of researchers as various biosensors can be embedded in or worn on the body of human beings for the measurement of health parameters. The patient's health data is then sent wirelessly to the physician for health analysis. The biosensors used to measure physiological parameters have limited power due to its small size and hence smaller form factor. For the longevity of the network, it is imperative to transmit the data in an energy-efficient manner. Moreover, the health information of the patient is stringently private. Hence, the privacy and security of transmitted information needs to be ensured. It necessitates the development of effective, lightweight and secure routing protocols that provides security with minimal use of resources. This paper has identified the numerous security requirements in WBANs and has provided the extensive review on existing secure routing protocols reported in the literature. A comparative analysis of the various existing state-of-the art secure routing protocols and critical analysis based on security techniques along with different performance parameters has been presented.Entities:
Keywords: Cryptosystems; Energy efficient; Routing protocols; Security; WBAN; Wireless body area networks
Year: 2021 PMID: 34456514 PMCID: PMC8380194 DOI: 10.1007/s11277-021-08969-0
Source DB: PubMed Journal: Wirel Pers Commun ISSN: 0929-6212 Impact factor: 1.671
Fig. 1WBAN Architecture [15]
Fig. 2WBAN security requirements
Fig. 3Classification of routing protocols based on different cryptosystems
Fig. 4CTR mode [69]
Fig. 5CBC-MAC mode [69]
Fig. 6Security suite [71]
Fig. 7Conceptual diagram [72]
Fig. 8Block diagram for GA in WBANs [74]
Symmetric key cryptographic protocols
| Author | Saleem et al. [ | Sampangi et al. [ | Baqai et al. [ | Kumar and Sharma [ | Lin et al. [ |
|---|---|---|---|---|---|
| Name of protocol | AES Encryption Framework | Security Suite for WBAN | Protocol with Patient/Node Identification and Interference Rejection | GA Framework in WBAN | Symmetric Cryptography with Chaotic Map and MMLN |
| Year | 2009 | 2012 | 2017 | 2018 | 2021 |
| Goal | To provide security solutions to WBAN in accordance with data traffic | To design a robust key generation and management scheme | To design a secure protocol with energy efficiency and interference rejection | To generate rules for protection of data storage and transmission for achieving data security | To design a secure routing protocol for physiological signals |
| Technique Used | AES and its modes | IAMkeys, KEMESIS | Sony protocol [ | AES and GA optimization | GRNN, MPNN, PSO, MMLN and a chaotic map |
| Security | Low | High | High | High | High |
| Initial key exchange phase | Yes | No | No | No | No |
| Energy efficiency | High | Medium | High | NA | Not considered |
| Computational overhead | Low | Medium | Low | Low | Low |
| Pros | Selects security mode using ACL | Random key generation for each frame | Interference rejection from sources | Unique as GA is used in data security for WBAN | High mean PSNR value |
| Usage of stream cipher | Transmission of new frame with latest values instead of retransmission | Capable of giving indications in abnormalities | Security optimization through key management using GA | Low mean executing time | |
| Low network overhead | Independent key generation at both communication entities | Patient/node identification | Biometrics or any image can be used for key generation | Fast operation time in learning | |
| Prioritize data freshness | Fast computations | Sound frequency or any sensation of body can be used for key generation | PSO algorithm rapidly adjusts the network parameters | ||
| Elimination of key exchange phase | Low storage overhead | Highly Secure | |||
| Ensures sender authentication | No noise interference | ||||
| Cons | If initial key compromised, whole network becomes insecure | The lost data frames should be at least 10 for retransmission | Does not consider non line-of-sight communication | Contribution of GA and AES on energy consumption of the network was not studied | Energy efficiency parameter is not considered |
| Does not meet stringent security requirements | Rely on humans for randomness of initial data frames | No modulation scheme is considered to improve the performance | |||
| Varying complexity | Parameters such as throughput, packet dropping rate and packet delivery ratio were not taken into account | GRNN training with the PSO algorithm is done with fixed learning parameters |
Fig. 9Process of authentication between the controller and user [88]
Fig. 10Authentication process for WBAN [93]
Asymmetric key cryptographic protocols
| Author | He and Zeadly [ | Raja and Kiruthika [ | Li et al. [ | Singla and Kaur [ |
|---|---|---|---|---|
| Name of protocol | Authentication protocol for AAL | Rel-AODV | Enhanced 1-round authentication protocol with user anonymity | CSEER |
| Year | 2015 | 2015 | 2017 | 2018 |
| Goal | To develop a secure and robust authentication protocol for AAL systems | To improve the reliability of AODV protocol | To design secure and lightweight authentication protocol | To achieve energy efficiency and security for medical data transmission |
| Technique Used | Identity based PKC, ECC, Hash Function | RSA, SHA-1 | ECC, SHA-1 | Arithmetic Compression, RSA |
| Security | High | High | High | Medium |
| Results compared with other protocols | Liu et al.’s protocol [ | EPR [ | Liu et al. [ | EPR [ |
| Provides strong forward secrecy | Yes | No | Yes | No |
| Data freshness | Yes | Yes | Yes | No |
| Energy efficiency | NA | Medium | NA | High |
| Computational overhead | NA | High | NA | Medium |
| Pros | More Efficient than [ | Provides reliability | Fixes loopholes of Liu et al. protocol [ | 10–11% more energy savings than Rel-AODV [ |
| Usage of timestamp protocol to resist replay attack | Categorizes traffic of WBAN | Resists to various security attacks | Low congestion in network | |
| Satisfies all security requirements | High throughput (80%) | More secure than [ | High throughput (83%) | |
| Low execution time than [ | Satisfies all security requirements | Same cost as Liu et al. protocol [ | Reduces the number of bits to be transmitted in Network | |
| No verification table required | Classification of nodes for energy savings | Low packet dropping rate with increase in transmission power | ||
| Robust and mitigate various security attacks | ||||
| Cons | Energy consumption of the network is not presented | High routing overhead | Energy consumption of the network is not presented | Path loss parameter is not considered |
| Parameters such as throughput, computational overhead not considered | Path loss parameter is not considered | Parameters such as throughput, computational overhead not considered | Data freshness is not considered | |
| Does not withstand with replay attack |
Fig. 11Key generation from ECG-signal [99]
Fig. 12Biometric-based security system using HMM [102]
Fig. 13Architecture of cloud based mobile healthcare system [103]
Biometric encryption routing protocols
| Author | Mana et al. [ | Wang et al. [ | Khan et al. [ | Chen et al. [ | Sammoud et al. [ |
|---|---|---|---|---|---|
| Name of protocol | SEKEBAN | Framework Using Wavelet-Domain HMM | Cloud-based framework | Cryptography Scheme for E-Health Systems | Biometrics-based key establishment protocol |
| Year | 2009 | 2011 | 2014 | 2020 | 2020 |
| Goal | To design secure and efficient key exchange method | To propose high performance authentication protocol | To evolve a secure, general and easily deployable mobile healthcare using cloud framework | To addresses different security issues for E-Health system at various stages | To design a reliable, secure and energy efficient protocol by using symmetric keys |
| Technique used | Morphing Block, Message Digest 5 (MD5), Handshake Protocol, MAC | Wavelet-Domain HMM, Hash, Selective Encryption approach | Cloud Framework, Discrete Wavelet Transform, MAC | BFAKN and FAAM | BCH, morphing function, Hashing function, Mac function |
| Security | Low | High | High | High | High |
| Results compared with other protocols | SSL protocol [ | None | EKG-based key agreement [ | None | SEKEBAN [ |
| Biometric used in protocol | ECG | ECG | ECG, EEG (electroencephalogram) | Fingerprints, ECG, EEG | ECG |
| Key Update period | Fixed by the administrator | Short period of time as statistics of ECG remains same for short period | Short | Not Applicable | Short |
| Energy efficiency | Low | High | Not considered | Not considered | High |
| Key Recoverability | Yes | No | No | Yes | Yes |
| Ubiquitous access for patient data | No | No | Yes | Yes | Yes |
| Entropy of key | Low | Low | High | High | High |
| Computational overhead | Not considered | Low | Low | Low | Low |
| Pros | Generates session key securely | Tolerate signal distortion | Provides privacy to patient data | False Acceptance Rate (FAR) is only 0.4% when error tolerance is 5 | Low energy consumption than SEKEBAN [ |
| Distributes session key securely | High authentication performance | Unique as cloud framework used for the first time | False Rejection Rate (FRR) can reach 6.5% | Highly Secure | |
| Secure end to end transmission | Time efficient model for data authentication | Highly secure | Highly secure | 100% Key retrieval Rate | |
| Secure communication links between nodes | Elimination of initial key distribution phase | EMRs are securely stored | 99.6% impersonation attack identification rate | FAR is 0.0% | |
| High recoverability of key loss | Low complexity | High entropy | Biometrics can hide a secret key with the help of fuzzy vault | FRR is 0.0% | |
| Energy efficient than [ | Low cost encryption method | Unauthorized users cant access patient data | Optimal resource consumption | ||
| Other biometric signal can be used | Reliable scheme for E-Health system | ||||
| Cons | Unique device Identifier (UId) acts as an initial shared secret key can be compromised | Limited to tier-1 communication only | Tier 2 communication can compromise the security | Energy efficiency parameter is not considered | High energy consumption than ELPA scheme [ |
| Device tampering compromised the security | Does not consider security of beyond WBAN communication |
Fig. 14Hybrid algorithm structure [124]
Hybrid key cryptographic protocols
| Author | Liu and Kwak [ | Barua et al. [ | Drira et al. [ | Irum et al. [ | He et al. [ | Basnet et al. [ |
|---|---|---|---|---|---|---|
| Name of protocol | Hybrid security framework | Secure and quality of service assurance scheduling scheme | Hybrid authentication and key establishment scheme | Security mechanism for intra-WBAN and inter-WBAN communications | Secure anonymous authentication (AA) for WBAN | Secure health telemonitoring |
| Year | 2010 | 2011 | 2012 | 2013 | 2016 | 2019 |
| Goal | To develop efficient and secure WBAN systems | To lower the waiting time of medical data packets | To propose a hybrid authentication and key establishment scheme | To strengthen security of tier-1 and tier-2 of WBAN | To propose a secure AA scheme having low cost | To improve security for real-time data communication in telemedicine |
| Technique used | AES, ID based ECC, and Diffie hellman | Bilinear pairing, Queue and digital signature | IBC, ECDH and Diffie–Hellman | Preloading of keys, biometric key generation, HMAC-MD5 | ECC, Diffie Hellman, bilinear pairing | AES, ECC and HMAC |
| Security | Medium | Medium | High | High | High | High |
| Technique for initial key exchange phase | ID-based ECDH key exchange protocol | Bilinear Pairing | Identity-based signature | None | None | ECC |
| Energy efficiency | Not considered | Not considered | Not considered | Medium | Not considered | High |
| Data Freshness | Yes | Not considered | Yes | Yes | Yes | Not considered |
| Prioritization of data traffic | No | Yes | No | No | No | No |
| Computational overhead | Low | Low | Medium | Lowest | Low | Low |
| Pros | Usage of ECC rather than RSA | Minimize key storage space | Resilient to attacks such as DoS, replay and MITM | High entropy of EKG signal | Reduces computational cost at client side | Provides high data encryption level |
Fast cryptographic operation time | Need less computation | Efficient resource utilisation | Elimination of key exchange mechanism | Resilient to various attacks | Shorter encryption time | |
| Different modes of AES can be used for different security requirements | User centric scheme | Categorises nodes for trade-off between security and resource constraints | Easy Node Eviction | Stores patient's data in database of highly secure NM | More challenging to break down ECC than RSA | |
| Shows good trade-off between resource constraints and security | Consider priority based traffic | High authentication performance | Low Storage overhead than BARI + [ | Lower computational cost than Liu et al. [ | Increases network lifetime | |
| Fast computations | Ensures QoS for real time traffic | Low computational load on sensor nodes | Low communication overhead than [ | Highly secure than previous AA schemes | Highly secure | |
| Cons | Stringent Security requirements not met by AES | Bilinear Diffie-Hellman Problem (BDHP) | No security for data storage | Security of tier-3 not considered | Slightly higher communication cost than [ | Size of encrypted file increases by 19% |
| QoS parameters are not considered | QoS in group and peer to peer communication is not ensured | Usage of time consuming multiplication operation | More energy consumption in the key refreshment phase than [ | No consideration of criticality of patient data and throughput |