Decentralized Security Bounty Management on Blockchain and IPFS

Hoffman, Alex; Becerril-Blas, Eric; Moreno, Kevin; Kim, Yoohwan

doi:10.1109/ccwc47524.2020.9031109

Cited by 10 publications

(7 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Figure 1 shows the knowledge engineering-based proposed system. The proposed knowledge system consists of four components: users, domain experts, knowledge engineers, inference agents, or intelligent agents [26][27][28]. Knowledge engineering phases are considered to design and deploy the proposed blockchain-based distributed application (DApp) for official health documents generation and maintenance.…”

Section: Proposed Methodsmentioning

confidence: 99%

Knowledge engineering–based DApp using blockchain technology for protract medical certificates privacy

et al. 2022

View full text Add to dashboard Cite

In the Industry 4.0 era, an inherited featured technology, blockchain, plays a vital role in knowledge engineering applications. Blockchain provides privacy to sensitive data as an intelligent agent, so its adoption rate increases in all the advanced domains. Especially in the health care department, blockchain technology usage helps avoid attacks like the Wannacry ransomware attack during 2017. Therefore, this paper described a decentralised application (DApp) expert system using public blockchain to create and maintain official health documents, especially medical certificates. Current existing systems, either paper‐based or database or clouds to save the medical certificates, have more scope to do attacks. Hence, proposed a blockchain‐based DApp that acts as an interface between intelligent agents, blockchains, and system related to the medical certificates. The main strength of this paper is implementation results, which are not among the maximum literary works currently available. The associate cost for conducting distributed application operations on the blockchain in terms of Gas comprehensively presented here. Furthermore, it consists of comparing the system's non‐functional functions by considering blockchain and non‐blockchain environments. Also, presented the simulation results with the performance results compared with the existed systems.

show abstract

Section: Proposed Methodsmentioning

confidence: 99%

Knowledge engineering–based DApp using blockchain technology for protract medical certificates privacy

et al. 2022

View full text Add to dashboard Cite

show abstract

“…IPFS was further used to enable a variety of other applications and use cases, which we cannot discuss in detail for the sake of brevity. Instead, we provide a brief list of other use cases/studies (in no particular order) which have built on top of IPFS: alternative storage schemes for IPFS [8], verifiable voting systems [44], collaborative document editing with version control [38], land record management [36], digital right management [1,37,46], content retrieval marketplaces [3], training of federated learning models [31], exchange of decentralised transfer learning models [54], software integrity and delivery frameworks [48], bug bounty system [19], biological data migration [58], among others.…”

Section: Research Studiesmentioning

confidence: 99%

Towards Decentralised Cloud Storage with IPFS: Opportunities, Challenges, and Future Directions

Doan¹,

Psaras²,

Ott³

et al. 2022

Preprint

View full text Add to dashboard Cite

Recent data ownership initiatives such as GAIA-X attempt to shift from currently common centralised cloud storage solutions to decentralised alternatives, which gives users more control over their data. The InterPlanetary File System (IPFS) is a storage architecture which attempts to provide decentralised cloud storage by building on founding principles of P2P networking and content addressing. It combines approaches from previous research, such as Kademliabased Distributed Hash Tables (DHTs), git's versioning model with cryptographic hashing, Merkle Trees, and content-based addressing in order to compose a protocol stack that supports both forward and backward compatibility of components. IPFS is used by more than 250k peers per month and serves tens of millions of requests per day, which makes it an interesting large-scale operational network to study. In this editorial, we provide an overview of the IPFS design and its core features, along with the opportunities that it opens as well as the challenges that it faces because of its properties. IPFS provides persistence of names, censorship circumvention, built-in file deduplication with integrity verification, and file delivery to external users via an HTTP gateway, among other properties.

show abstract

“…An independent hash value is generated by the file content to identify the file, and only one file with the same content exists in IPFS to save storage space. IPFS is widely used in electronic medical records, 48,49 IoT architecture, 50 data backup, 51 and reward management 52 . Here, we store the training data and model parameters of the deep learning model in IPFS.…”

Section: Distributed Deep Learning Based On Blockchainmentioning

confidence: 99%

“…IPFS is widely used in electronic medical records, 48,49 IoT architecture, 50 data backup, 51 and reward management. 52 Here, we store the training data and model parameters of the deep learning model in IPFS. The data are scattered in IPFS, and distributed storage is used to generate the corresponding IPFS hash.…”

Section: Framework Designmentioning

confidence: 99%

A blockchain‐enabled learning model based on distributed deep learning architecture

Zhang

Liang

Jia

et al. 2022

Int J of Intelligent Sys

View full text Add to dashboard Cite

Aiming to address the unsatisfactory performance of existing distributed deep learning architectures, such as poor accuracy, slow network communication, low arithmetic speed, and insufficient security, we propose and design a learning model based on a distributed deep learning and blockchain architecture. We use a hybrid parallel algorithm based on blockchain (HP‐B) to build a distributed deep consensus learning model. The HP‐B algorithm is grouped according to the performance of computing nodes participating in training, network links and training samples, and the grouped computing equipment performs optimal distributed computing. The purpose of this approach is to solve the security and scalability concerns and improve the convergence speed and accuracy of deep learning. The proposed method achieves good results on the CIFAR‐100, CIFAR‐10, and IMAGENET data sets. Finally, the distributed deep learning model based on blockchain is combined with the generative adversarial network to solve the segmentation problem of medical imaging data, and the experimental results are superior to those of other networks.

show abstract

Decentralized Security Bounty Management on Blockchain and IPFS

Cited by 10 publications

References 8 publications

Knowledge engineering–based DApp using blockchain technology for protract medical certificates privacy

Knowledge engineering–based DApp using blockchain technology for protract medical certificates privacy

Towards Decentralised Cloud Storage with IPFS: Opportunities, Challenges, and Future Directions

A blockchain‐enabled learning model based on distributed deep learning architecture

Contact Info

Product

Resources

About