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IoT Database Forensics

An Investigation on HarperDB Security
Authors: Marsh, R; Belguith, S; Dargahi, T;

IoT Database Forensics

Abstract

The data that are generated by several devices in the IoT realmrequire careful and real time processing. Recently, researchers haveconcentrated on the usage of cloud databases for storing such datato improve efficiency. HarperDB aims at producing a DBMS that isrelational and non-relational simultaneously, to help journeymendevelopers creating products and servers in the IoT space. Much ofwhat the HarperDB team has talked about has been achieved, butfrom a security perspective, a lot of improvements need to be made.The team has clearly focused on the problems that exist from adatabase and data point of view, creating a structure that is unique,fast, easy to use and has great potential to grow with a startup.The functionality and ease of use of this DBMS is not in question,however as the trade-off triangle to the right suggests, this doesentail an impact to security. In this paper, using multiple forensicmethodologies, we performed an in-depth forensic analysis onHarperDB and found several areas of extreme concern, such as lackof logging functionalities, basic level of authorisation, exposure ofusers’ access rights to any party using the database, There had to bea focus on preventative advice instead of reactive workarounds dueto the nature of the flaws found in HarperDB. As such, we providea number of recommendations for the users and developers.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Average
Average
Green