BC-IoDT: Blockchain-based Framework for Authentication in Internet of Drone Things
October 21, 2022 ยท Declared Dead ยท ๐ DroneCom@MobiCom
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Junaid Akram, Awais Akram, Rutvij H. Jhaveri, Mamoun Alazab, Haoran Chi
arXiv ID
2210.11745
Category
cs.CR: Cryptography & Security
Cross-listed
cs.DC
Citations
21
Venue
DroneCom@MobiCom
Last Checked
3 months ago
Abstract
We leverage blockchain technology for drone node authentication in internet of drone things (IoDT). During the authentication procedure, the credentials of drone nodes are examined to remove malicious nodes from the system. In IoDT, drones are responsible for gathering data and transmitting it to cluster heads (CHs) for further processing. The CH collects and organizes data. Due to computational load, their energy levels rapidly deplete. To overcome this problem, we present a low-energy adaptive clustering hierarchy (R2D) protocol based on distance, degree, and residual energy. R2D is used to replace CHs with normal nodes based on the biggest residual energy, the degree, and the shortest distance from BS. The cost of keeping a big volume of data on the blockchain is high. We employ the Interplanetary File System (IPFS), to address this issue. Moreover, IPFS protects user data using the industry-standard encryption technique AES-128. This standard compares well to other current encryption methods. Using a consensus mechanism based on proof of work requires a high amount of computing resources for transaction verification. The suggested approach leverages a consensus mechanism known as proof of authority (PoA) to address this problem . The results of the simulations indicate that the suggested system model functions effectively and efficiently. A formal security analysis is conducted to assess the smart contract's resistance to attacks.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Cryptography & Security
R.I.P.
๐ป
Ghosted
R.I.P.
๐ป
Ghosted
Membership Inference Attacks against Machine Learning Models
R.I.P.
๐ป
Ghosted
The Limitations of Deep Learning in Adversarial Settings
R.I.P.
๐ป
Ghosted
Practical Black-Box Attacks against Machine Learning
R.I.P.
๐ป
Ghosted
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks
R.I.P.
๐ป
Ghosted
Extracting Training Data from Large Language Models
Died the same way โ ๐ป Ghosted
R.I.P.
๐ป
Ghosted
Language Models are Few-Shot Learners
R.I.P.
๐ป
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
๐ป
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
๐ป
Ghosted