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Balancing the Yin and Yang of Big Data

Author: Mark Micallef, Vice President, Asia Pacific & Japan, Cloudera
Data is the oil of the 21st century – crude, unrefined and tremendously valuable when tapped. Gleaned insights from the growing volumes of data collected become strategic assets for businesses, improving customer experiences and providing a competitive edge. On the flip side, data is also increasingly becoming a vulnerability that can be held ransom by cyber criminals or used for malicious means.
 
The majority of cybercriminals in today’s age are motivated by monetary gain, and therefore, go where the money is. A recent finding by Kaspersky Lab highlighted that cybercriminals operating in Asia Pacific were initially data-hungry but have taken a step further and added ‘money-stealing on their attack menu’ as they target banks across the region. The masterminds behind these cyber attacks hunt for sensitive and valuable information such as credit card details and national identification numbers, allowing them to manipulate and use the data for illegal purposes, just as we have seen with the recent Equifax breach. Business leaders face increasing pressures to secure company data in the midst of today’s volatile cyber threat landscape and the issue is often exacerbated in a poorly controlled big data environment, where cyber risks are heightened. This makes it easier for criminals to penetrate through the organizations’ cybersecurity defenses.
 
Governments across the globe have taken initiatives to battle these attacks by introducing new compliance regulations, such as the General Data Protection Regulation (GDPR). The new regulation, scheduled to be in effect from May 2018, aims to govern the collection and management of personally identifiable information (PII) garnered from consumers. As a result, this has a monumental effect on how organizations will leverage data for business decisions, making it necessary for business leaders to take a different approach for data management.  Today’s big data platform must have several key factors – automation, analytics, and a centralized data hub to manage the consistently growing volumes of data while maintaining compliance and security.
 
While the first step of defense is creating awareness across an organization, chief information officers (CIOs) must be able to take education a step further by driving proactive and efficient initiatives to better protect their organizations. By integrating a big data platform onto an existing cybersecurity infrastructure, businesses can identify valuable and sensitive data for encryption, building an additional wall of defense and making it tougher for attacks to break through.

Having a big data platform powered by Machine Learning (ML) and Artificial Intelligence (AI) enables organizations to anticipate and defend against breaches while radically reducing the time to detect and respond attacks. A fitting example is Apache Spot, an open source cyber security project that uses ML to empower organizations with the ability to analyze large data sets quickly, leading to better and faster threat detection. ML and AI can also help to offload tasks from CIOs, a powerful advantage to have with the lack of cybersecurity resources available today.
 
One of our Indonesian customers, Bank Mandiri, was able to do just this. With the adoption of Cloudera’s data management platform, Bank Mandiri leveraged machine learning models to better predict cybercrime, money laundering, and insider threats, all while ensuring that customer data was still easily accessible, secure and compliant with the latest industry regulations.
 
Despite all the advantages that big data has proven to bring to a cybersecurity strategy, organizations are faced with high barriers of entry when deploying an initial big data use case for cybersecurity. As such, Cloudera has partnered with Arcadia Data, Centrify, and StreamSets to make it easier for security teams to take the first step and deploy basic use cases, such as cyber vulnerability and events analytics, leveraging data sources common to many environments.
 
Cyber attacks are inevitable today, and there is no one-size-fits-all solution for cybersecurity. While challenges and opportunities co-exist in the big data space, businesses must first be able to tackle the challenges before being able to fully leverage the opportunities. Therefore, it is imperative that businesses build upon and modernize their existing cybersecurity infrastructures through the adoption of a machine learning and analytics platform as a fundamental and durable part of a data strategy. The best cybersecurity strategies are ones that integrate effort, with the latest technological innovations, keeping organizations safeguarded against present and future threats. 

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