I am wondering how the disciplines of Information Security and Data Analytics could be synergistic
Are there any other rationale other than the following two reasons:
1. Analytics can be used as a tool for improving security (especially with intrusion detection etc.,)
2. One can use protecting analytical IT systems as a test bed for securing other operational IT systems.
As far as I understand, data analytics or data analysis deals with organsing the data in uch a way that all necessary information/ patterns can be retrieved. If data is important or confidencial then it can be organised by encryption so information security is related to data analysis. Intrusion is nothing to do with data analysis. An unauhorised entry is intrusion. To make more secure, private and confidencial Information security comes in the picture. Encrption is one of the process through which an unauthorised user should not be able to make sense out of data he is receiving.
I think that data analitics must be useful for increasing the all three dimensions of information security: the information confidentiality, the information. Integrity and the information disponibility.
>Intrusion is nothing to do with data analysis
But intrusion detection has definitely to do with data analytics. The huge amount of data generated by IDS and similar systems has to be analyzed.
@Sathish: I also see the second point (if I understood you correctly): There are new security challenges because of the introduction of big data/ data mining/ analytics tools. The solution to these challenges can be used in other systems, too.
For getting an idea of challenges of big data security issues (and maybe getting inspiration to your question) see: https://cloudsecurityalliance.org/download/expanded-top-ten-big-data-security-and-privacy-challenges/
Some examples of these challenges:
- How do we trust the data sources? (Many big data systems use huge amount of distributed sensors. The data of these sensors could be manipulated): How can these sensors/ data be autenticated?
- How can the data be REALLY anonymized: It is (often) possible to correlate data (even personal data) even though the name/address etc. was deleted before data analysis. Data analytics often has to do with sensitive personal data.
Big data analytics is very useful for performing digital forensics, retrospective IDS identifying attacks after the fact as well as for identifying and correlating suspicious patterns in data that otherwise would be impossible to do due to the lack of historic network data. Areas of use goes far beyond traditional IDS. PacketPig is one tool that uses this technique:
https://github.com/packetloop/packetpig
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