The growing popularity of OTT services, led by Netflix and Amazon Prime, is attracting more players who are ready to leverage 5G speeds that could democratize real-time streaming. Advanced OTT streaming capabilities with improved quality of service (QoS) and quality of experience (QoE) are becoming a reality as 5G is capable of supporting up to one million devices per square kilometer.
Breakthroughs in the radio access network (RAN) layer and core mobile network subsystems will enable further proliferation of 5G streaming applications. Emerging technologies such as mmWave, MIMO, mobile edge computing (MEC), and Cloud-RAN (C-RAN) are paving the way for next-gen streaming applications for 5G-powered use cases across industries for immersive learning, augmented and virtual reality, next-gen remote healthcare and more. However, 5G-enabled machine-to-machine (M2M) and device-to-device (D2D) communications running on millions of devices and low-powered sensors mean a significant expansion of the cyber security threat landscape across the content streaming value chain, from upstream content origin servers to the last mile streaming devices.
Relaying, off-loading and sharing of content, besides proximity-based applications such as vehicular communications, real-time video surveillance, and video analytics on the edge, are all facing a higher risk of breach and exploitation by cybercriminals.
Studying the overall OTT and content streaming architecture to evaluate susceptibility to attack, attack patterns, and modes in deference to the expanding cyber threat landscape is pivotal in developing appropriate cyber resilience strategies to mitigate risks and protect vulnerable assets.
Understanding five critical attack vectors
The streaming applications landscape is vulnerable to cyber-attacks such as:
- Content spoofing, content poisoning
- Stream ripping and MITM attacks
- Malware and ransomware attacks
- DRM hijacking, HDCP bypassing
- IoT botnet attacks, zero-day vulnerability attacks, etc.
Leveraging machine-first automation to enable a combination of prediction, prevention, and protection layers across the streaming ecosystem can significantly mitigate cyber-attacks targeting next-gen streaming platforms and applications. Proactive, predictive monitoring for potential attack vectors across the streaming value chain is crucial to secure the trust boundaries against cyber-attacks.
Elevate your security posture
The integrated security triad approach, built on three dedicated layers for prediction, prevention, and protection, can elevate organizational cyber defense and resiliency against attacks against streaming platforms.
Huge volumes of streaming content consumed over millions of devices and applications worldwide render it impossible to use conventional techniques to predict cybercrime hotspots. Analytics-driven solution accelerators can help overcome this challenge. The prediction layer will leverage realistic threat models to predict security hotspots in the 5G streaming ecosystem level and appraise a gamut of 5G streaming vulnerabilities across smart CCTVs, autonomous cars, advanced set-top boxes, AR and VR systems. Machine learning-based algorithms will enable real-time prediction of hotspots, identify high-risk items, and categorize them. Early flagging of potential vulnerabilities will empower organizations to provide disruption-free streaming services.
Prediction of zones prone to potential cyber risk drives the development of prevention models. Prevention against cyber-attacks requires strict adherence and compliance of 5G streaming systems to domain-specific and regulatory security standards. A combination of streaming specific qualitative assessment (SQA) and quantitative automated control testing (QACT) methods can be used to design a hybrid prevention model with capabilities to add new controls in the future. Leveraging the hybrid prevention model will help industries adopt proactive risk mitigation and thrive in the internet of things era.
The protection layer is meant to deliver enhanced cyber resilience for streaming applications. This layer is built to accommodate comprehensive, automated SAST (static application security testing), DAST (dynamic application security testing), and component verification tests at the content aggregation level, in place of conventional last mile tests. This breakthrough approach will not only enhance the efficiency of security tests for streaming content but also cull vulnerabilities from reaching downstream systems such as user devices. Designed to enhance end-to-end security of assets in the streaming life cycle, including new streaming devices such as next-gen set-top-boxes and GPU-enabled playback devices, this final layer offers aggregation level protection and completes the proposed security-triad methodology.
With capabilities to roll out bespoke automated security tests at the content aggregation level, the protection layer will bring organizations the competitive edge of validated DRM (digital rights management) capabilities, early on in the streaming value chain.
The integrated security triad advantage
A deep-dive, strategic approach powered by automation and context-driven analytics leveraging the integrated dynamic security-triad model will help next-gen media companies and industries pre-empt cyber-attacks targeting 5G streaming applications. This in turn widens the scope for enterprises to focus more on ideating, creating and delivering high-quality offerings backed by uninterrupted streaming services and realize accelerated business growth through customer delight. The security-triad approach helps enterprises to adopt a ‘security by design’ principle to protect streaming applications and ensure disruption-free, high-quality streaming services in real-time and monetize from the 5G economy.