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Nicholas Kolokotronis

Researcher at University of Peloponnese

Publications -  125
Citations -  1131

Nicholas Kolokotronis is an academic researcher from University of Peloponnese. The author has contributed to research in topics: Computer science & Intrusion detection system. The author has an hindex of 14, co-authored 115 publications receiving 689 citations. Previous affiliations of Nicholas Kolokotronis include National and Kapodistrian University of Athens & Athens State University.

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Proceedings ArticleDOI

Blockchain Solutions for Forensic Evidence Preservation in IoT Environments

TL;DR: A blockchain-based solution, designed for the smart home domain, dealing with the collection and preservation of digital forensic evidence, that allows tackling the unique challenges posed by the need for digitally handling forensic evidence collected from IoT networks.
MonographDOI

Digital Crime And Forensic Science in Cyberspace (N/A)

TL;DR: "Digital Crime and Forensic Science in Cyberspace" is unique in putting together a number of contributions from leading experts in digital forensics and associated fields, making information on this new and complex subject available in one source of reference that addresses its multifaceted nature.
Proceedings ArticleDOI

IoT Malware Network Traffic Classification using Visual Representation and Deep Learning

TL;DR: The detection of malicious network traffic in the proposed approach works at the package level, reducing significantly the time of detection with promising results due to the deep learning technologies used.
Proceedings ArticleDOI

WiP: A Novel Blockchain-Based Trust Model for Cloud Identity Management

TL;DR: Wang et al. as mentioned in this paper proposed a trust and identity management model based on the blockchain for cloud identity management with security and privacy improvements, which addressed the issues of poor management of trust in federated identity management systems, which brought with it many security, privacy and interoperability issues.
Journal ArticleDOI

On the Nonlinear Complexity and Lempel–Ziv Complexity of Finite Length Sequences

TL;DR: A new recursive algorithm is presented, which produces the minimal nonlinear feedback shift register of a given binary sequence and it is shown that the eigenvalue profile of a sequence uniquely determines its nonlinear complexity profile, thus establishing a connection between Lempel-Ziv complexity and non linear complexity.