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Making IoT Safe Should Be Number One Priority
June 26, 2018 Blog

The Internet of Things (IoT) is rapidly changing the world around us – disrupting and transforming various industries and areas of business. In many instances, that’s a good thing. Unfortunately, in terms of security, we aren’t entirely ready, and the risk of attack is real. IoT is being exploited with increasing frequency, a worrying situation for both enterprises and consumers. They are in desperate need for insights to predict when the products or the technologies they use will end up being attacked. The threat surface has now opened exponentially, revealing numerous vulnerabilities and opportunities for unwelcomed malicious threats and attacks.

recent survey by IT security firm ESET and the National Cyber Security Alliance revealed 40 percent of respondents in the US expressed no confidence in their devices being safe, secure or private. It has become clear from the rising frequency of attacks that security is finding it harder to keep up with the pace of the innovation and the increasingly integrated network connections into critical infrastructure. More defence practices are needed, and clear directions to ways that help fend off attacks on IoT systems are needed.

The severity of the damage a hacker could inflict on a driverless car, or on transport drones, or even in business messages is a reality we can no longer overlook.

The dependency on network-connected technologies is very much outpacing the means to secure them even more so as we increasingly rely on them to improve every-day activities, from self-driving cars to the control systems that deliver water and power to houses. Therefore, securing the Internet of Things needs to be close to, if not the number one priority for both government and businesses at large to mitigate and take charge of before it spirals further out of control or a tragedy occurs.

In terms of businesses, they need to implement cyber operations from a defensive and perhaps even an offensive perspective to protect their clients and data. The threat is global. Nations from first world or third world aren’t spared from being attacked, irrespective of the language barrier.

The enterprise IoT, big data and machine learning initiatives can be delayed, fail, or risk security breach unless the most mature and tightly integrated platform is used. Even so, there’s no single solution that can completely secure the IoT environment. What businesses can do to tackle the issue of IoT security is by taking a wide-angle view and incorporate different security strategies and concepts. For example, IoT security typically requires the monitoring of enormous amounts of physical devices, connections, authentication, and data transfer, thus having the capability to intelligently collect security event data and sift through enormous data sets is crucial.

A recent Forrester report on IoT Security said, “IoT security means watching at least 10 times, if not 100 times, as many physical devices, connections, authentication, and data transfer events as today.  Having strong security event data collection capabilities and the ability to intelligently sift through enormous data sets will be crucial to the security of IoT-enabled systems.”

It has become clear that the boundaries of our security measures have expanded and we need to go beyond what used to be to make sure all these new edge devices are protected. To keep up with the scale that IoT is expanding, will require a combination of machine intelligence with platform scale to detect IoT threats.

Here is where companies like Cloudera are able to assist by providing fast, easy, secure data management and analytics platform that allows organisations to not only analyse and derive value from all of the IoT sensor data that is generated, but also ingest, store, access, and evaluate hundreds of billions of security events through a modern, future-proof architecture. With such capabilities, the enterprise will benefit from increased agility and decreased risk. Their primary goal is in making multi-disciplinary analytics workloads run securely, smoothly and efficiently whether in the cloud or on-premise, backed by their Shared Data Experience. With SDX, it’s easier for enterprises to efficiently deploy and manage their multi-disciplinary IoT, big data and machine learning applications.

By applying machine learning to data at scale, enterprises are able to perform anomaly detection to discover new and advanced attacks, including IoT-based attacks. To protect themselves against risk of future threats, organizations can harness Cloudera’s platform, built on open source innovation and a rich partner ecosystem of applications, to unlock new IoT value.