“With great power comes great responsibility¹.”
As organizations harness the power in data to grow their business through initiatives like IoT, predictive analytics, single view of customers and more, now is the time for them to further exercise their corporate responsibility. This means that organizations need to safeguard data to protect their business continuity, brand name, and most importantly, the people: employees and customers.
Cyberattacks have continuously and severely plagued business entities and global economy over the years, as intelligent consumers are certainly aware. Take one of the critical attacks last year for example, the Equifax Data Breach². The company suffered a 27% decline in earnings in the third quarter compared to the previous year, and reported $87.5 million of pretax expenses in the same period, with an estimated additional expense of $75 million in the subsequent quarter. The leakage of sensitive private information impacted 145.5 million consumers, nearly half of the U.S. population. The aftershock of a data breach can go on and on, from tangible monetary loss to intangible harm, such as loss of credibility and damage to brand equity, from which the company can take years and maybe decades to recover.
Unfortunately, building a sound enterprise-wide cybersecurity mechanism for protection is easier said than done. With the proliferation of connected devices, cloud, and IoT deployments, the expanding exploitation and attack opportunities cause threat levels to rise at an exponential rate, outpacing traditional security tools and defense capabilities. Particularly, in the following three areas:
Because the hyper-connected digital world produces cybersecurity data at a volume and rate that companies can’t keep up using manual process and traditional security tools to safeguard data, they now turn to the most advanced solutions in The Information Age – Big Data and Machine Learning.
The hallmark of big data is the ability to ingest, process, aggregate, and manage vast amount of data coming from variety sources at different speed. This capability provides normalization and analytics of massive security and related data sets for easy detections of anomalies in investigations. Because machine learning models can be trained to recognize patterns and independently adapt to new data, the combination of the two, Big Data and Machine Learning, creates a powerful automated cybersecurity mechanism that shines a light on the dark age of widespread cybercrimes for enterprises.
Sitting at the prime intersection of Big Data and Machine Learning, Hortonworks Cybersecurity Platform (HCP™), powered by Apache Metron, employs a data-science-based approach to visualize diverse, streaming security data at scale to aid Security Operations Centers (SOC) in real-time detection and response to threats. This open source platform is built on top of the unmatched scalability and governance of data in Hortonworks Data Platform (HDP™) and the real-time ingest and processing capability in Hortonworks DataFlow (HDF™). Core features³ of HCP include:
With HCP, users are able to streamline their operational efforts and focus on high-value, urgent items based on alert prioritization. Additionally, the application of advanced analytics and Model as a Service provides a platform for cutting-edge machine learning models using technologies like Spark, GPUs and deep learning. These features bring efficiency and effectiveness to SOC operators, as well as better detection of unknown threats.
The Hortonworks product offering includes support for the Cybersecurity platform as well as our industry-leading professional services to install and harden platforms to build your security data lake. Our delivery teams integrate and implement common data sources such as Active Directory, NetFlow, DNS logs, Proxy logs, Firewall logs, application logs and others and implement alert and anomaly detection. We can provide solutions for use cases like personalized monitoring of user behavior, password attacks, geo-improbably activity, changes in server and client behavior³’ and many others.
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¹Origin, “With Great Power Comes Great Responsibility”:
²Cyberattack Casts a Long Shadow on Equifax’s Earnings, New York Times, 2017: https://www.nytimes.com/2017/11/10/business/dealbook/equifax-cyberattack-earnings.html
³Hortonworks Introduces Real-Time Cybersecurity Threat Detection With Extensible Open Data Models, Press Release, 2017: https://hortonworks.com/press-releases/hortonworks-introduces-real-time-cybersecurity-threat-detection-extensible-open-data-models/
³’Hortonworks Cybersecurity Platform – Big Data Cybersecurity Solution, Simon Elliston Ball, 2017: https://hortonworks.com/blog/hortonworks-cybersecurity-platform-big-data-cybersecurity-solution/