The opportunities are also increasingly wide ranging, encompassing personalization and more precise targeting of content as well as ads, coupled with exploitation of behavioral or contextual features such as location and the type of device being used for viewing at the time. All of these aspects require accurate real time information and the ability to analyze data quickly in order to take immediate actions, whether to counter a threat or exploit an opportunity. This all comes under the ambit of Big Data analytics, which is increasingly overlapping with revenue security for pay TV operators and commercial broadcasters.

This trend is bringing together the previously distinct fields of TV analytics and revenue security, which Verimatrix has already taken account of by bringing out our Verspective Intelligence Center. Given our background in CA/DRM along with associated technologies such as forensic watermarking that are coming of age in the multiscreen era, Verspective was conceived particularly in anticipation of evolving threats such as content redistribution over the Internet. From the outset it was clear that Big Data was going to play a crucial role in the enlarged security landscape we now inhabit.

Threats are becoming increasingly hard to define clearly through rules, which means we need to be capable of identifying them as they emerge in real time by analyzing and correlating data from a variety of sources. Sometimes these sources lie beyond the immediate pay TV ecosystem of a given operator, with increased sharing of threat related information for the common good of the whole industry. Such information may derive from monitoring of known piracy networks, which again may give early warning of threats that may be relevant for just one operator or may apply more widely.

One of the most exciting things that became increasingly clear during development of Verspective was that interaction between traditional TV analytics and security would work equally both ways, with mutual benefits on either side. TV revenue security systems have unique access through their “preferred real estate” in the ecosystem to data that will enhance both Quality of Service (QoS) and content related aspects of the user experience by improving recommendations. At the same time the personal data relating to subscriber preferences and behavior feeding Big Data analytics can itself be highly sensitive and therefore benefit from the mechanisms for enforcing privacy already part of revenue security packages. For these reasons, as part of our Verspective Intelligence strategy, we have partnered with a number of major players in the TV analytics, monitoring and audience measurement arenas with which we previously had little overlap.

These partners bring the data collection and analytics expertise that we lack, while we contribute the security technologies needed to ensure privacy of personal data and integrity of the whole system. We also have experience of different jurisdictions, making us well placed to ensure that analytics deployments comply with local regulations over personal data privacy, just as we have done over video content rights which also vary between countries. This was acknowledged by one of our new partners, Genius Digital, the UK based leader in viewer and audience analytics, with which we are involved in a two way collaboration. On the one hand secure data we collect via the Verspective Intelligence Center is enhanced with Genius Digital’s Insight Platform, which provides valuable set top box return path data. Our combined data yields viewer insights that help operators reduce subscriber churn and create new revenue streams. We now offer this capability as part of Verspective Analytics, which is our new product for exploiting our data through these partnerships.

On the other hand our experience is helping Genius Digital take account of differences over governance and data protection between markets, which can have an impact on the way its analytics is implemented. This is an increasing factor as service providers branch out into new areas to exploit their existing subscriber relationships. In one case an operator registered as a financial services company in one of its markets found that the regulations stipulated that credit card data must be stored locally on site rather than in the cloud. This meant analytics integration on that data also had to be performed on the premises.

Experience of different regulatory regimes also comes into play when it comes to data aggregation between multiple operators, which we see playing a growing role both in countering security threats and extracting the full value of data. In both cases the power of data can lie in the ability to correlate multiple instances across different operators. This is something we are encouraging our customers to do by showing them the benefits, but we acknowledge this will take time and involve overcoming the chicken and egg syndrome. This is that the value of aggregated data will only become fully apparent once volumes have built up and many operators are involved, while until then some will be unconvinced that the effort and risks involved make it worthwhile. So we have to convince them that aggregated data will be secure and that where relevant personal data integrity will be ensured through measures such as encryption, obfuscation and anonymization.

Such aggregation on a global scale will also prove valuable and perhaps eventually essential in combating content security threats in a connected online world. For example a malicious activity might first show up locally within a pay TV infrastructure in Latin America and through a connected hub this could be analyzed quickly so that counter measures can be taken before that threatens other service providers around the world.

Aggregation can occur not only between operators but also within them, bringing the potential to turn this into a marketable commodity. This is something we have been looking into with Genius Digital with a view to integrating return path data collected by its Mirimon technology to turn aggregated data into a product our operator customers can sell and make extra revenues from. Such data could be of interest to market research firms, advertising agencies and major brands.

A natural question that comes up repeatedly at this stage when revenue security is still sometimes seen as a niche sector is what data we can provide. The answer is that we have access to data from just about every part of the delivery ecosystem from the head end through the network to the client device. Some of this data can be obtained in other ways, but other data is unique to us, especially within the encrypted domain, as is the case over the network. Our ability to decrypt data on demand during transit of the video is already being exploited by another of our new partners, specialist monitoring vendor IneoQuest, which has addressed the problems operators have ensuring QoS in the multi-screen era arising because video is distributed over the unmanaged Internet, making quality harder to guarantee. The problem is particularly acute for dedicated over-the-top (OTT) operators totally reliant on the Internet for distribution and this is a major focus for specialist monitoring vendor IneoQuest.

As IneoQuest has found, video quality is hard to measure over the Internet, never mind guarantee, since raw data on latency and bandwidth does not equate accurately with the experience delivered to the end device. The issue is compounded by the need for issues affecting QoS to be pinpointed accurately and yet very rapidly in real time for an operator to have any chance of responding to them as they arise in order to sustain a high quality experience. IneoQuest deploys appliances or probes in the network to measure QoS, but found that in order to do that effectively they must be able to detect individual content during transmission. The problem is that the premium content for which QoS is most important is invariably encrypted to protect against piracy and unauthorized access without paying. This is where Verimatrix comes in by decrypting the content that it is protecting, so that IneoQuest can analyze the flows with its probes and provide valuable information about QoS.

Just as importantly, operators also need to see the experience from the end user’s perspective at the client device, enabling adjustments to be made on the fly to parameters such as bit rate in order to optimize QoS. Such ability has a direct bearing on revenue, since both short term engagement with particular content and longer term loyalty to a service are closely correlated with quality as measured on the client in the case of OTT services. This has been confirmed by several consumer surveys, including Parks Associates’ OTT Video Market Tracker, which revealed unexpectedly high churn rates for many OTT video services, as a result of poor experiences coupled with the fact that it is easier to ditch these online offerings than a traditional pay TV service.

This point has been confirmed by yet another of our Big Data partners, Adobe Primetime, which provides a multi-screen platform and sees the role of analytics as being to maximize subscriber engagement time. Adobe has noted that incidence of buffering and dropped frames correlates directly with subscribers turning off. Adobe is also finding that if the operator can get such data, it is then possible to keep such customers engaged by taking appropriate action immediately, which could be to start with a lower bit rate on mobile phones and keep that customer viewing. On this front Verimatrix can provide the key data through its role managing the entitlement process on the client.

It is important to highlight in conclusion that plenty of challenges remain in orchestrating the evolution of revenue security and its convergence with analytics in the multiscreen world, not least in carrying content owners, service providers and their subscribers along with us on this journey. In all cases it is up to us to demonstrate that the data is safe and that we are keeping abreast of the ever changing threat landscape. But there is no doubt that Big Data analytics will be essential in enabling security solutions to notice anomalous and potentially dangerous behavior in as near real time as possible to prevent breaches. Failing that, at the very least the system must be able to direct malicious behavior once a breach has occurred, allowing operators to dynamically update their policies to minimize risk.

At the same time the data we can provide will play a big role in the analytics process both in ensuring QoS and helping operators exploit viewer behavior and preferences effectively. Analytics and security together will be at the heart of next generation pay TV.