![]() ![]() Many tools are hybrids of these types of mobile security models, and they aren't purely signature-, AI- behavior- or cloud intermediary-based. How vendors employ different types of mobile security This approach uses crowd sourcing to obtain and test files, but it is more behavior-based than the simple penetration testing associated with a traditional signature file antivirus approach. Mobile behavioral analysis is the best way to find zero-day exploits. There is still a cloud-based component to this approach the agent occasionally downloads new suspicious behaviors to flag on the device, but most of the work is done locally. ![]() With this approach, an AI-based preloaded app prevents malicious activity by flagging suspicious behavior. The following type of mobile security monitors the behavior of the apps or files on the device. Fortunately, the general availability of fast 4G, 5G and LTE makes this less of an issue.įor mobile security vendors, this approach means they can run very fast and extensive processes on high-powered cloud servers, eliminating the restrictions of on-device resources. This intermediary approach also works well for mobile devices, but it can sometimes cause a lag in performance if the mobile devices are on a slow network. The files are loaded to the device only if these files are approved. Under this model, any files a user receives or downloads to the device are automatically uploaded to the cloud service for testing and comparison to determine if they're malware or security threats. The next type of security model also uses the cloud and essentially acts as an intermediary service. However, this type of mobile security approach isn't great at finding zero-day attacks due to the time lag inherent with gathering data, testing and returning intelligence to the on-device agent. With relatively fast connections, the lag in checking a file type against the files on a cloud server is minimal. This cloud-based analysis approach works very well for mobile devices because it doesn't require large amounts of local processing. The tools enforce these policies through a local app that updates with the latest information about the safety of files. Once AI identifies any malicious files, it prevents users from downloading and opening them. No mobile security tool is 100% effective, but they are an important step given how much sensitive corporate data is available on mobile devices these days.Īnalyzing these files and applications in the cloud helps security tools identify the warning signs of malicious intent. It's a similar model to search engines where the community contributes samples that improve the overall experience. This type of mobile security tool studies the files users download and install on their devices. Today, many organizations employ the hybrid-AI approach noted below. This doesn't work very well for mobile devices, however. ![]() The traditional signature file antivirus model creates a signature file on the device that all apps and documents are compared to. Traditional signature file antivirus approach There are four different types of mobile security models used by vendors. No mobile security tool is 100% effective, but they are an important step given how much sensitive corporate data is available on mobile devices these days.
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