Tag: maxmind

拿 Cloudflare Workers 跑 Geolocation API

在 Hacker News Daily 上看到拿 Cloudflare Workers 跑 Geolocation API：「How to make simple Geolocation service」。

作者想要做一個很簡單的 Geolocation API，一開始的想法是在 AWS Lambda 上用 MaxMind 的資料，但 latency 偏高：

However, I quickly realized that the response time isn't what I've expected - on average the response took somewhere between from 200ms to 500ms. So I started looking for other options.

所以作者就想到是不是有有機會丟到 Cloudflare Workers 上，但發現 license 看起來是個問題，另外因為把 MaxMind 的資料庫丟進去，會超過 worker 的時間限制：

And for this case MaxMind offers GeoLite2 database, however you'll be in charge of hosting this database on your server and making regular updates of the database. You also need to make sure your project is compliant with MaxMind's License.

However, this solution had one really big caveat - MaxMind GeoLite2 database does not work on Cloudflare Workers due to some runtime limitations.

結果作者後來發現 Cloudflare Workers 上本身就會帶 Geoloation 資訊了，不需要另外拉 MaxMind 的資料查：

And after exploring their documentation, I realized that the Request object in function have an access to cf object, which contains some useful information about the visitor, including visitor's country!

另外我翻了一下價錢，主要是算次數的，看起來 Free Plan 就可以 100K/day (執行時間限制是 10ms)，而如果是付費方案的話則是 USD$0.5/M (50ms)，這樣對一些小專案來說，Free Plan 似乎是夠用了...

Humble Bundle 對抗信用卡盜刷的方法

Humble Bundle 說明他們如何對抗信用卡盜刷的方法，主要是不斷的降低風險，然後讓人介入的機會降低 (因為人事成本很高)：「How Humble Bundle stops online fraud」。

其中第一點是特別想提的：

Our first line of defense is a machine-learning-based anti-abuse startup called Sift Science, which we’ve been training for years across 55,000,000 transactions. Given how many orders we process, Sift Science has a really good idea when someone is up to no good. The model adapts daily as we get more data.

Sift Science 在 2014 的時候提過：「偵測信用卡交易是否為盜刷的服務」。做的事情很簡單，你把大量的資料傳給 Sift Science，包括了各種使用者身份資訊，以及信用卡資料，Sift Science 可以透過 Machine Learning 的方法告訴你這筆交易的風險，讓你進一步的判斷。

其實不少家都有做類似的服務，像是 MaxMind 的 minFraud (就是做 GeoIP database 很有名的那家公司的另外一個產品)。當交易量很大的時候是個很有趣的應用，降低處理盜刷後續處理的成本。