Can graphs mitigate against coronavirus-related cybercrime?. Issue 11 (November 2020)

• Record Type: Journal Article
• Authors: Hodler, Amy
• Is Part Of: Network security. Volume 2020:Issue 11(2020)
• Page Start: 6
• Page End: 8
• Publication Date: 2020-11
• Subjects: Computer security -- Periodicals; Computer networks -- Security measures -- Periodicals; Electronic data processing departments -- Security measures -- Periodicals; Computers -- Access control -- Periodicals; 005.805
• DOI: 10.1016/S1353-4858(20)30127-6
• Languages: English
• ISSNs: 1353-4858

Abstract

Abstract : Cyber criminals are exploiting the spread of Covid-19 in order to carry out fraud and cybercrime, pinpointing aid programmes as easy targets. With the pandemic spreading apace, funds are being issued hastily to provide service and support to local communities. Trust is being exploited by these malevolent actors. Fraud is evolving continuously and the pandemic has given cyber criminals unique opportunitiesto leverage existing attack techniques. Traditional fraud detection solutions are not powerful enough because they are built on relational databases that provide no context for the data. By comparison, graphs not only explain individual data points but also their relationships with one another. This enables even the most complex relationships to be shown in a meaningful way, explains Amy Hodler of Neo4j.