gateways based on either HTTP ( s ), SMPP or SS7 as the most popular integrations , but are also responsible for safeguarding consumers against abuses and illegal subscriptions , amongst other vices .
A growing concern for MNOs is the increase in grey routes , which are becoming prevalent in the delivery of fraudulent and unwanted traffic . A grey route is one that supports SMS traffic , but doesn ’ t generate revenue for MNOs because they take advantage of legitimate consumer routes to send large quantities of A2P SMS messages for a price point that is under the official carrier rate . The ‘ grey ’ part of the route is usually found at the receiving end where the message terminates on one operator ’ s network . It ’ s often made to look as if it originated locally through manipulation of the sender ID when , in , reality , it will have likely started its journey from abroad . While grey routes are not properly monetised , network operators still pay for signalling and network maintenance for this traffic .
In recent years , there has also been a steady rise in SIM farms that disguise A2P traffic to look like peer-to-peer ( P2P ) traffic to exploit mobile networks . SIM farms are banks of mobile devices that contain SIM cards and connect to networks like mobile phones . They typically use prepaid SIM cards with unlimited SMS deals , and are commonly used by SMS spammers .
A growing concern for MNOs is the increase in grey routes , which are becoming prevalent in the delivery of fraudulent and unwanted traffic .
Two options remain open for MNOs in attempting to curb losses and threats caused by such vulnerabilities , technological intervention or commercial . This is possibly augmented through other strategies including segmentation and segregation of traffic .
Fraud-ridden channels
SIM farms not only violate network fair usage agreements , they also often drive fraudulent traffic to end users with the intention of scamming them through phishing or other means . This poses a threat to both subscribers and network operators , with the latter risking reputational damage and a loss of trust from customers . When channels become fraud-ridden , the highest generators of A2P revenue – enterprises – will often seek alternative networks to protect their customers against potential losses .
To protect themselves , MNOs must primarily implement SMS firewall systems to secure their networks and customers . This should be coupled with continuous learning , as fraud patterns and techniques evolve almost daily . SMS firewalls monitor the type of traffic that is coming onto a mobile network and can track the destination . These solutions scan all SMS traffic coming to a mobile network based on content , the sender and the route via which messages are sent amongst other message parameters as the complexity of curbing some of these vulnerabilities increases .
The criteria for filtering messages initially needs to be pre-set and MNOs should work with a firewall vendor that can implement these rules . Additionally , operators must work with a vendor that continuously updates these rule sets to ensure they filter out all unwanted traffic from a network . Advanced firewall systems feature Artificial Intelligence ( AI ) and Machine Learning ( ML ), which enable the system itself to keep building a database and criteria for filtering messages .
SMS firewalls remain the golden standard for preventing fraud and spam on mobile networks . There are multiple firewall vendors in the market , but the most effective solutions are a managed solution , where MNOs work together with their vendor . This ensures constant upgrading of the firewall to keep up with the latest trends , as well as to create new rules to cover any emerging fraud mechanisms .
Accordingly , and owing to the significant vulnerabilities posed by grey routes , spam , phishing and other SMS based attacks , MNOs are projected to significantly increase their investment of next generation SMS firewalls from 48.3 % in 2018 to 81.3 % in 2023 of all MNO deployments . While majority of the investments were in Europe at 38.8 % of total deployments , Middle East and Africa ( MEA ) accounted for 27.4 %. Going forward , we also anticipate an increased investment by MNOs locally in uniformity with the global trend . •
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