Visible to the public Insider Threats and Cryptographic Techniques in Secure Information Management

TitleInsider Threats and Cryptographic Techniques in Secure Information Management
Publication TypeJournal Article
Year of Publication2017
AuthorsOgiela, L., Ogiela, M. R.
JournalIEEE Systems Journal
Volume11
Pagination405–414
Date Publishedjun
ISSN1932-8184
Keywordsauthorisation, business data processing, cognitive data analysis, cognitive systems, Collaboration, Companies, cryptographic data splitting algorithms, cryptographic protocols, cryptography, Data analysis, data protection, data reconstruction methods, Economics, enterprise management processes, Human Behavior, human factors, Information management, information management security, insider threats, Metrics, policy-based governance, Protocols, pubcrawl, Resiliency, secure information management, semantic analysis, strategic data splitting, unauthorized leakage
Abstract

This publication presents some techniques for insider threats and cryptographic protocols in secure processes. Those processes are dedicated to the information management of strategic data splitting. Strategic data splitting is dedicated to enterprise management processes as well as methods of securely storing and managing this type of data. Because usually strategic data are not enough secure and resistant for unauthorized leakage, we propose a new protocol that allows to protect data in different management structures. The presented data splitting techniques will concern cryptographic information splitting algorithms, as well as data sharing algorithms making use of cognitive data analysis techniques. The insider threats techniques will concern data reconstruction methods and cognitive data analysis techniques. Systems for the semantic analysis and secure information management will be used to conceal strategic information about the condition of the enterprise. Using the new approach, which is based on cognitive systems allow to guarantee the secure features and make the management processes more efficient.

URLhttps://ieeexplore.ieee.org/document/7067420
DOI10.1109/JSYST.2015.2409213
Citation Keyogiela_insider_2017