When you hear the phrase “Swiss cheese and spam,” you might think of a quirky sandwich. But together they’re the perfect metaphor for messaging security. As mobile messaging becomes more valuable for businesses, the industry has seen a surge in spam — ranging from simple annoyances to serious threats such as smishing and fraud.
So, what does Swiss cheese have to do with it? In security, the “Swiss cheese model” illustrates how multiple imperfect layers of defense can work together to block threats. Each layer — like a slice of Swiss cheese — has holes. But when stacked, the gaps rarely align, making it much harder for threats to slip through.
At Syniverse, we believe true protection is multi-layered. Here’s how we help keep spam out:
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Network filtering — Our SMS firewalls act as the first line of defense, blocking suspicious traffic at the network level.
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Content filtering — Our Messaging Trust solution analyses message content to spot and stop malicious or unwanted messages before they reach users.
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Human feedback and expertise — We incorporate real-time reports from end users and customers, with supervision by experienced data analysts who continuously refine our systems.
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Regulatory and policy controls — We enforce strict campaign vetting and policy compliance to ensure only legitimate traffic is allowed.
What makes Syniverse unique is our ability to align every layer of protection —covering both A2P and P2P traffic, and supporting multiple channels such as SMS, RCS, and WhatsApp. Because we provide all these layers, we can ensure there are no gaps in your defenses.
The result? Reduced risk, regulatory compliance, and peace of mind for your business and your customers.
Want to learn more about how multi-layered protection can keep your messaging channels secure? Contact Syniverse today for a security assessment.
Or visit our website to check out our Mobile Identity and Authentication products.
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Learn more about maximizing the ROI of Identity and Authentication solutions in our whitepaper, Cracking the Security Trilemma.
