Titlebook: Network and System Security; 13th International C Joseph K. Liu,Xinyi Huang Conference proceedings 2019 Springer Nature Switzerland AG 2019

協(xié)定

A Blockchain-Based IoT Data Management System for Secure and Scalable Data Sharingulnerability to malicious attacks. Recently, many researchers and security analysts are focusing on the blockchain technology to solve the security and privacy issues of the IoT data management. However, current blockchain technologies are unable to meet the highly concurrent IoT data transactions a

Glycogen

Towards Secure Open Banking Architecture: An Evaluation with OWASP, allowing third party providers and developers access to bank APIs, has emerged, welcoming a myriad of innovative solutions for the financial sector. However, multiple cyber security issues arise from exposing bank data to third party providers through an API. In this work, we propose an architectu

紅潤

Creditee

OVERSCAN: OAuth 2.0 Scanner for Missing Parameters, which results in the security control of accessing sensitive information is necessary. The authorization server as the one security aspect which controls the access permission to the system. Many authentication protocols were proposed to meet these functional requirements. The open-standard author

激怒某人

LaT-Voting: Traceable Anonymous E-Voting on Blockchainystems are excessively dependent on a centralized platform for publishing voting activity and storing ballots, which cannot ensure the security against tampering. Recently, numerous solutions based on blockchain are proposed to eliminate this threat. Nevertheless, these schemes are not applicable fo

修正案

希望

SSHTDNS: A Secure, Scalable and High-Throughput Domain Name System via Blockchain Techniqueerious security threats due to its distributed structure with a center. Blockchain has received extensive attention due to its decentralized, secure and trusted characteristics since the existence of Bitcoin. In this paper, we propose a new domain name system based on blockchain techniques called SS

macular-edema

PLUMP

attenuate

Unsupervised Insider Detection Through Neural Feature Learning and Model Optimisationsity (CMU) CERT Programs insider threat database. Experimental results demonstrate that our proposed approach could achieve an extremely low false-positive rate (FPR) with all malicious events identified.