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Today's database management systems implement sophisticated access control mechanisms to prevent unauthorized access and modifications. For instance, this is an important basic requirement for SOX (Sarbanes‐Oxley Act) compliance, whereby every past transaction has to be traceable at any time. However, malicious database administrators may still be able to bypass the security mechanisms in order to make hidden modifications to the database. This paper aims to address these issues.

In this paper the authors define a novel signature of a B⁺‐tree, a widely‐used storage structure in database management systems, and propose its utilization for supporting the logging in databases. This additional logging mechanism is especially useful in conjunction with forensic techniques that directly target the underlying tree‐structure of an index. Several techniques for applying this signature in the context of digital forensics on B⁺‐trees are proposed in the course of this paper. Furthermore, the authors' signature can be used to generate exact copies of an index for backup purposes, thereby enabling the owner to completely restore data, even on the structural level.

For database systems in enterprise environments, compliance to regulatory standards such as SOX (Sarbanes‐Oxley Act), whereby every past transaction has to be traceable at any time, is a fundamental requirement. Today's database management systems usually implement sophisticated access control mechanisms to prevent unauthorized access and modifications. Nonetheless malicious database administrators would be able to bypass the security mechanisms in order to make modifications to the database, while covering their tracks.

In this paper, the authors demonstrate how the tree structure of the underlying store engine can be used to enhance forensic logging mechanisms of the database. They define a novel signature for B⁺‐trees, which are used by the InnoDB storage engine. This signature stores the structure of database storage files and can help in reconstructing previous versions of the file for forensic purposes. Furthermore, the authors' signature can be used to generate exact copies of an index for backup purposes, thus enabling the owner to completely restore data, even on the structural level. The authors applied their concept to four real‐life scenarios in order to evaluate its effectiveness.

The purpose of this study is to investigate international trade determinants, paying special attention to variables related to climate change and non-tariff measures (NTMs), as they shape more and more world trade flows, with particular incidence on globalised goods, such as wine.

Based on panel data of Port wine exports to 60 countries, between 2006 and 2018, a gravity model has been estimated through Poisson pseudo-maximum likelihood. Explanatory variables include NTMs, mean temperature, temperature anomaly, gross domestic product (GDP), exchange rate, ad valorem equivalent tariffs and home bias.

The findings show that exports are inversely related to both mean temperature and temperature anomaly in importing countries. Regarding NTMs, it is found that only part of them are trade deterrent. Additionally, purchasing power in importing countries is one of the main determinants of Port wine exports.

The results show that, besides traditional economic variables, policymakers and wineries should include in their exports' decisions the impact of variables related to climate change and NTMs.

The novelty of this paper is to incorporate the impact of climatic variability of importing countries as a determinant of international trade of wine. Most former studies inspired of the gravity model consider explanatory variables such as GDP and exchange rate, and more recent ones started to consider NTMs too, however, this study may be the first paper to include the impact of climate change (quantified by mean temperature and temperature anomaly in importing countries) on exports.