Application Level Trust Authority (APPLETA) for Resource-Constrained Edge Devices in IoT and 6G
The rapid growth of the internet and edge devices has greatly increased the risk of cyber-attacks at the edge layer of computer networks. The rise of edge devices has driven extensive research into their cybersecurity challenges. These devices require robust protection to counter possible cyberattacks. Trust is a key security parameter used to determine the level of protection required for a device.. Trustworthiness gives confidence to other devices before they offer or request a service. The trust value indicates the probability of risk that a device may incur while engaging with another device. There are various solutions, but many fail due to the diversity of edge devices in the Internet of Things. In this paper, an efficient trust management framework, APPLETA, has been proposed. It computes the trust value based on routine application transactions and authentication behaviours without additional overhead. Simulation results show that the trust value is computed more efficiently, using only one application transaction trust parameter. APPLETA has demonstrated better results against good and bad-mouthing attacks with two parameters: application transaction and authentication. This scheme can effectively segregate malicious and harmless nodes. This segregation can further assist in the precise detection of malicious nodes.
Authors
- Seok‐Joo Koh (ORCID: https://orcid.org/0000-0003-3429-2040)
- Moneeb Gohar (ORCID: https://orcid.org/0000-0002-7600-1013)
- Shahid Mahmood (ORCID: https://orcid.org/0000-0002-5240-8222)
- Anwar Ghani (ORCID: https://orcid.org/0000-0001-7474-0405)
- Muhammad Usman Tariq (ORCID: https://orcid.org/0000-0002-7605-3040)
Institutions
- Abu Dhabi University (AE)
- International Islamic University, Islamabad (PK)
- Kyungpook National University (KR)
- Bahria University (PK)
- Jeju National University (KR)
Publication Details
- Journal
- IEEE Transactions on Consumer Electronics
- Published
- 2025-05-01
- DOI
- https://doi.org/10.1109/tce.2025.3571817
- Citations
- 3
- Primary Topic
- IoT and Edge/Fog Computing
- Type
- article
- Field-Weighted Citation Impact
- 4.46