Data Security in Mobile Scanning: Why On‑Device Processing Matters

Daniel Albertini of Anyline

The issue

In 2019, a Symantec security report revealed that roughly 75% of all cyber‑attacks targeted point‑of‑access devices such as routers. This fact underscores the high risk that a compromised device can pose to an organization, says Daniel Albertini, CTO of Anyline.

With that in mind, why do many businesses still insist—often unnecessarily—on transmitting data over networks instead of processing it locally on the device?

Consider a modern factory setting. An employee scans a serial number on a new part using OCR on their mobile device to update inventory. The OCR engine sends the image to a remote server for recognition, exposing the data to any attacker who has compromised the network router.

While the exposure of stock information may seem low‑stakes, the same principle applies to far more sensitive data. Imagine border‑control officers equipped with a mobile solution that quickly scans passports and IDs. The software must still transmit raw images over Wi‑Fi or cellular networks, potentially exposing personal data to third‑party processors that offer cheaper, cloud‑based OCR at the cost of security.

The solution

These risks stem from using OCR software that relies on cloud processing. For non‑critical tasks, the trade‑off may be acceptable, but when security is paramount, on‑device processing is essential.

By implementing on‑device OCR, organizations can keep sensitive data within their own devices, eliminate the need for a network connection, and maintain full control over the processing pipeline. This approach not only mitigates the risk of data interception but also ensures compliance with strict data‑protection regulations.

OCR technology delivers undeniable benefits—reducing human error, increasing throughput, and cutting costs—but the value is realized only when the solution is both cutting‑edge and uncompromising in security.

The author is Daniel Albertini, CTO, Anyline.