The constant battle to secure data such as intellectual property or financial information can be won using big data analysis.
With the development of technology, there are newer areas with security risks. For example, it is important to analyze the security of private data on the cloud, and the ability to distinguish valuable information from useless data. With this analysis, it would be easier to raise an alarm in real time if something exceptional happens, indicating a security breach.
There are patterns in the large volumes of data that cannot be extracted by humans. Big data analysis can extract the required data, abstract it, and find good patterns and anomalies. Although big data analysis can be costly, it can save a lot of money as cyber crime costs billions of dollars to businesses and governments each year.
Interpol estimates say that the cost of cyber crimes in the global economy is running to several billions of dollars each year. The 2012 Cyber Crime Report by Norton calculated the global costs of cybercrime, which came out to almost $110 billion. When these costs are considered, big data analysis seems like a viable option.
Studies suggest that companies that capture and use big data for decision making purposes have a higher ROI than their competitors. The McKinsey Global Institute says that big data has the potential to generate large productivity growth for public and healthcare sectors. It can also increase the margins for retailers, thus creating better employment opportunities in the data analysis industry.
Big Data to Manage Threats
Malware generally attacks using the element of surprise. With big data analytics, a connection can be established between the generation of malware and the change in traffic. With this connection, similar patterns can be noted and a malware attack can be stopped before it occurs.
For supply chain and logistics, big data can profile the suppliers by scanning the contracts, agreements, invoices, connectivity logs, shipping notes, and expense and payment records. By keeping a track of this data, high risk suppliers can be easily identified, thus reducing the risk of a loss.
In terms of internal threats, companies can use big data to identify some patterns of staff behavior. This data can include web activity, email content, and access logs. By identifying patterns, any deceitful behavior can be recognized and curbed.
The major advantage of big data would be to predict and prevent IT mishaps. However, it can also help in reviewing an incident once it has occurred. It can assess the impact, root causes, and possible indicators that could warn the organization of future events.
Microsoft’s Big Data Center
To address the problem of cyber crime, Microsoft has created a Cybercrime Center that combines technical and legal expertise. The center has all the latest resources and tools to make crime fighting easier. It was unveiled in November 2013, and was set up to aid the Microsoft Digital Crime Unit in their online battle against cyber crooks.
Big data analysis can help experts win the war against cyber crime. When cyber criminals try to access highly confidential data, it requires high level systems and partnerships to catch them. If the experts could take massive amounts of data and got meaningful information out of it, it can revolutionize the world of IT security.
Big data analysis is not yet mastered, and it needs more talent to completely realize the potential that it holds. Although big data is crucial for fighting cyber crime, it also poses many security risks. There is a lot of data that is generated by workstations, servers, PCs, laptops, and smartphones. When such a huge amount of data is not handled efficiently, there can be huge risks as cyber crooks can attempt to steal a part of this data. Companies that rely on big data analytics need to understand the security concerns, as privacy becomes even more important for the servers that are processing big data.
How Big Data Can Affect Businesses
The need to find insights into corporate data isn’t something new. However, what’s new is the rate at which this data is expanding. With the ever increasing data, there are new threats and risks that come from various sources. When it comes to big data security, many things need to be considered, like the source of data, how much data is collected, how it is being used, and who has the access to all this data. There should be clear guidelines and standards defining all the stakeholders and the methods and processes for storage and use of big data.
Since technology changes rapidly and the legal process is slow, new technical solutions are often unregulated because of the old legislation. This lag can affect the security and privacy of big data. Big data companies need to make sure that their processes are always compliant with the regulations and laws, while making sure that they follow the latest technologies. If the raw data is sensitive in nature, it might not be legal to use it. Companies have to make sure they are not using private raw data for their processes.