Fromanonymization at the pseudoanonymization; fromhashing al subsamplingpassing through the inoise prevention. The techniques for protecting sensitive information are becoming more advanced every day.
Especially when you move on from the protection of privacy online staff to the need to keep safe databases or larger systems.
The above processes allow you to obtain anonymous or pseudo-anonymous data, but unfortunately they guarantee total unassailability. For this reason it is certainly advisable also intervene from a preventive perspective.
For example, using the differential privacywhich allows you to gain awareness about sensitivity of the single data. And on the information that risks being compromised in the event of unwanted intrusions.
What is hashing and what is it for
When it comes to data anonymization we often end up talking about encryption: a set of techniques designed specifically to hide information or content of various kinds.
L’hashing it’s a cryptographic method which allows you to intervene on data and files. A procedure that transforms the data and converts it in the so-called hash value.
From a cryptography perspective, l’hashing it is anything but a complex operation. Even because it does not involve the creation and exchange of keys public and private.
Nell’hashing encryption is used to reconvert the aforementioned hash values at the previous stage. A necessary step to reconstruct the data and be able to consult it.
I hash values in fact they are simple records that share the length of the original data. But they do not in any way allow us to trace the information contained within the data.
Per return to readable datathe user needs three components: the cryptographic keyl’reference algorithm and finally the given which was originally associated with the hash value.
Hashing is a cryptographic procedure that allows data to be anonymized
Hashing is an ideal formula for proceeding withdata anonymization and to theirs storage. Also because hash values can be associated with pre-established positions within databases.
The fields of hashing application are multiple: from the management of database above to the creation of tabel ad hoc. From the encryption of files al password hashing and the realization of digital signatures and other authentication systems.
Furthermore, hashing is even considered more secure than traditional encryption for at least one order of reasons. The hash value in fact, taken as such, it cannot be decoded in any way.
This assumption allows hashing to resist even tobrute force hacker attacks. But unfortunately there are techniques that also allow us to overcome this limitation.
In fact, some criminals manage to access the so-called rainbow tables: lists of information that they compare hash values, access data and algorithms.
Other anonymization and pseudoanonymization techniques
Hashing and encryption techniques represent only one of the possible fields ofanonymization. Although in some cases it is more correct to talk about pseudoanonymization.
Also there pseudoanonymization it has to do with the data encryption. But it features some structural limits compared to complete anonymization.
In fact, data subjected to pseudo-anonymisation techniques allows for trace it back to a reference person. Provided, however, that you have a more or less complex series of Additional Information.
Furthermore we talk about anonymous data in case you get an output that it cannot be rebuilt: this is the case for example of the hash values described in the previous paragraphs.
Instead we talk about pseudo-anonymous data in case there is the possibility of match groups of information in order to reconstruct the original data.
Subsampling and noise injection make it possible to obtain anonymisation or pseudo-anonymisation of the data
Techniques such as subsampling o l’noise injection allow you to compromise the readability of data, improving the IT security. With the purpose of protect sensitive information contained within it. But they do not necessarily generate 100% anonymous data.
Il subsamplingalso known as decimation or downsamplinginvolves a reduction in the sampling frequency of the electrical signal.
This means intervene on data transmission speed original. Or alternatively, intervene on its dimensions in the original format. A procedure born and spread in the audio sector, which however has found interesting counterparts in the data protection sector.
Lnoise injection it achieves the illegibility of the data by intervening in a diametrically opposite manner compared to subsampling. Indeed, it predicts entering extra variations within the data: random dataor noise, which prevent meaningful data from being identified.
How to use differential privacy to improve cybersecurity
Unfortunately also the techniques of anonymization or pseudoanonymization are notinfallible. And therefore it may happen that someone accesses sensitive data. Or that, more generally, they occur flaws in cybersecurity of a system.
Luckily they exist strategies and methods that allow you to analyze the status ofcrisis in progress e apply any corrective measures. A valid example in this sense is the so-called differential privacy.
When it comes to differential privacy reference is made to a mathematical framework: a set of libraries with specific functions, which act as basis for software development more advanced.
Differential privacy allows you to view how much information has been compromised from any attacks by hacker, but not only. It also allows us to go into the merits of future predictions and scenarios.
This kind of framework allows you to study the files in advancedatabase. Going to locate how much and what sensitive information would be disseminated in case of compromise.
In this sense, differential privacy is excellent first step to plan future interventions of encryption, anonymization or pseudoonymization.
To know more: Computer security: guide to safe browsing on the web