I have seen on some sites which say ,for-example, multiple votes/views from same computer will be neglected/penalized etc. For-example liking a facebook page, or youtube video from same computer(different accounts) will not increase its worth(according to my knowledge).How do these sites identify bogus votes? I just need a direction.
How web-servers identify a client
web development;web applications
Without requiring user accounts (I'm assuming that your use case precludes them), there's no foolproof method to identify end users. But some common methods include:CookiesSet a cookie on the client machine to identify the user.Pros: Definitely unique per sessionCons: Easy to remove or prevent (even for people with limited technical knowledge), only apply to one browser, easy for a script to bypassIP addressUse the user's IP address to identify the user.Pros: Changes infrequently, works across browsers, requires technical knowledge to spoof or use a proxy serverCons: Not necessarily unique: one IP address can easily apply to entire homes/buildings/offices behind a network, and for some ISPs end user IP addresses might be reassignedBrowser fingerprintingUse all browser data passed to the server (not just user agent, but also OS, screen resolution, and a number of other things) to generate a unique browser fingerprint.Pros: High probability of being unique, opaque to the end user (changing IP addresses or clearing cookies won't bypass it)Cons: Probably too unique -- any change in browser condition (or browser) will change the fingerprint (though you can choose only a subset of supplied browser information to balance fingerprint volatility and uniqueness), can be bypassed by scriptsYou can, of course, also use multiple methods. Which method you use really depends on your specific use case. For many cases, just a simple cookie will do. If you want some defense against scripts or other methods of bypassing, add an IP address rate limit. You can also attempt to gather as much information as possible and use some sort of heuristic algorithm to try to find people that are bypassing the system for uniqueness that you have in place.But again, there's no foolproof way to do this.