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10. Privacy-preserving and Trusted Threat Intelligence Sharing using Distributed Ledgers

Author

Ali, Hisham, Papadopoulos, Pavlos, Ahmad, Jawad, Pitropakis, Nikolaos, Jaroucheh, Zakwan, and Buchanan, William J.

Subjects
FOS: Computer and information sciences, Computer Science - Cryptography and Security, Cryptography and Security (cs.CR)
Abstract

Threat information sharing is considered as one of the proactive defensive approaches for enhancing the overall security of trusted partners. Trusted partner organizations can provide access to past and current cybersecurity threats for reducing the risk of a potential cyberattack - the requirements for threat information sharing range from simplistic sharing of documents to threat intelligence sharing. Therefore, the storage and sharing of highly sensitive threat information raises considerable concerns regarding constructing a secure, trusted threat information exchange infrastructure. Establishing a trusted ecosystem for threat sharing will promote the validity, security, anonymity, scalability, latency efficiency, and traceability of the stored information that protects it from unauthorized disclosure. This paper proposes a system that ensures the security principles mentioned above by utilizing a distributed ledger technology that provides secure decentralized operations through smart contracts and provides a privacy-preserving ecosystem for threat information storage and sharing regarding the MITRE ATT\&CK framework.

Published
2021

21. A Privacy-Preserving Secure Framework for Electric Vehicles in IoT Using Matching Market and Signcryption.

Author

Kumar, Gulshan, Saha, Rahul, Rai, Mritunjay Kumar, Buchanan, William J., Thomas, Reji, Geetha, G., Hoon-Kim, Tai, and Rodrigues, Joel J. P. C.

Subjects
ELECTRIC vehicles, CRYPTOGRAPHY, KEY performance indicators (Management), MARKETS
Abstract

The present world of vehicle technology is inclined to develop Electric Vehicles (EVs) with various optimized features. These vehicles need frequent charging which takes a longer time to charge up. Therefore, scheduling of vehicles in charging stations is required. Besides, the information of the EVs and its location is also stored by the charging stations and therefore creates a concern of EV privacy. Various researches are going on to solve these problems; however, an efficient privacy-preserving solution is less practiced till date. In this paper, a framework for Electric Vehicle (EV) charging is discussed. The framework uses the concept of Matching Market to identify a charging station and uses the lattice-based cryptography for secure communications. The matching market considers multiple factors to provide the best allocation of charging station and cryptography ensures security and privacy preservation. The use of lattice-based cryptographic hash SWIFFT avoids heavy computation. This usage of matching market and lattice cryptography, more specifically signcryption for EV charging framework are the highlights of the solution and add-ons to the novel features. Overall, the presented framework is efficient in terms of computation and communication cost, satisfaction ratio, slot ratio, charging latency and load balancing index. The performance metrics are compared with recent developments in this field. [ABSTRACT FROM AUTHOR]

Published
2020
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