Table 3.

Application layer attacks with preventive techniques.

Hardware/Physical Attacks	Relevant refereneces with proper description of authentication schemes
Non-repudiation Attacks	Reference Kremer et al. (2002), demonstrate the existing classical non-repudiation authentication procedures by highlighting that most of them are befalling within the class of a trusted third party (TTP) authentication model, which is comprehensively discussed in references Coffey et al. (2003); Yaga et al. (2018). Classical non-repudiation security explications are maturing and antiquated in the H-IoT application employed in connections of COVID-19, due to the certification of trustworthiness and third-party interruption in the network. In this context, blockchain-based authentication played a major role to address the possible malicious attacks on H-IoT deployed networks. To address the non-repudiation security threat in H-IoT application, the on-chain and off-chain channels scheme was suggested in reference Xu et al. (2019).
Repudiation Attacks	Reference Awan et al. (2020), suggested a NeuroTrust mutual authentication model that leverages trust parameters to assure dependability, adaptability, and packet authenticity with low network cost to detect rogue devices in the H-IoT network. In Ahanger and Aljumah (2018); Algarni (2019); Sahi et al. (2017), the writers give a thorough sketch of the security and privacy predicaments that must be addressed for the prosperous implementation of H-IoT applications on a viable large scale. Despite that, they also examined the security interests amalgamated with H-IoT applications by analyzing the present literature to get an insight into these security obligations.
Malicious code injection attacks	Reference Ahmed and Ullah (2017), presents the false data injection attack (FDIA) solution by launching an awareness campaign followed by some cryptographic techniques to prevent the foretasted attacks in the healthcare domain. In Aggarwal et al. (2021), the author designs a three-layered blockchain-based Unmanned Aerial Vehicles (UAV) approach to enable privacy protection in the H-IoT applications. The recommended model offers a distributed policies for UAVs that assures the integrity and confidentiality of data during transmission of H-IoT applications from one site to another practicing the proof of work (PoW) consensus technique.
Data corruption attacks	In Alazeb and Panda (2019), the authors present two model-based data preservation scheme for the H-IoT applications by utilizing separate fog modules for heterogeneous, and homogeneous data respectively to assure the legitimacy of transmitted data. The current literature in Abouzakhar et al. (2017); Chaudhry et al. (2021); Roy et al. (2018) fully describes data corruption removal strategies.