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Commentary Speculations on the Negative Side of Big Data

"If subsequent technological advancement and business processing models development make it possible for Big Data processing in becoming commonplace, it would be fair to speculate that corresponding technologies may also emerge that could have the capacity to poison big data for malicious purposes." -Loloy D

Commentary Speculations on the Negative Side of Big Data
Prepared by Loloy D, April 2013

Much like how spam has been plaguing the internet since it was "invented" and "further developed" to elude intelligent and advanced security validation, Big Data can also be subjected to similar poisoning especially when malicious gains can be made from short-term market speculations, and influencing CPIs and other relevant statistical indicators. Far from being a vehicle for spreading FUDs (fear, uncertainty and doubt), my thesis proposes for a more careful approach on implementing and adopting Big Data on industrial, national and international scales. Automatic data validation on voluminous ultra-large amounts of complex data sources with a high degree of confidence on reliability may not exist yet, even when the biggest names in the commercial arena of enterprise solutions providers claim otherwise. The "backdoor hackers" who control millions of botNets and who initiate DDoS attacks may eventually design systems, mechanisms and supporting scripts that could manipulate the very data sources that encompass the domain comprising Big Data. Note that both structured and non-structured data are fair game to multi-vectored attacks that "backdoor hackers" normally employ. It is thus crucial for Big Data analytics and tools to become more robust and comprehensively prepared in the validation and filtration of "junk" or "malicious material" that would adversely influence the veracity of all those data representations. Note further, that even the biggest names in the internet arena, such as Google, Yahoo, Oracle and IBM, may also push for their own agenda and their own ends as they release reports that allegedly comes from clean and reliable Big Data analytics.

Under Big Data, how can we represent true reliability? This may never be practically achieved; there is just too much commercial interest and intervention in the entire process.

About Loloy D

Loloy D wrote this thesis after attending an international conference that discussed Big Data in Bangkok, Thailand on April 2013 under the guise of his alter ego :-). He runs the domains loloyd.net and the more-than-a-decade running loloyd.com, and has been pursuing an Internet Age International Arms Race world record.