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The adversary doesn't care whether it takes 1 sec or 1 hr to test a single password guess, exactly; a serial password-guessing machine that tries passwords in sequence second by second over the course of an hour, vs. The dedicated adversary will use all tools available to them—not just run a password cracker on their laptop, but maybe run it on a GPU, or an FPGA, or even fabricate application-specific integrated circuits on a silicon die.

The adversary will use the smallest password-guessing circuit they can on the die, corresponding to the least energy consumption and heat dissipation, and fit as many of them in parallel as they can. Different cost parameters have different impacts on an adversary's actual costs. So what do the cost parameters do?

The adversary would rather use say double the space to fit twice as many password-guessing circuits on the die; by doubling the memory requirements they can't take advantage of that parallelism. The adversary would rather use say double the space to double the password-guessing throughput; by doubling the parallelism requirements they have to use the parallelism for a single password guess and not two password guesses in parallelism.

Iterations or time. When the user logs in entering their password in via a web client , then set a session cookie that remembers the user for the rest of their session. Make sure to use SSL throughout, and to set the secure flag on all cookies. If you want, you can set a persistent secure cookie once the user authenticates, so they will never need to enter their password again on this browser.

If you want to access the web service from a dedicated mobile client, the same approach works fine. The web server can send a secure persistent cookie which the app can store permanently in its app-local storage, and can use that cookie to authenticate the client. If for some reason the above is not possible, there are some fallback alternatives, but I think they are less preferable and more likely to have security problems.

Here's one plausible fallback method: On the first launch of your mobile client app, it prompts the user for their password, connects to the server over SSL, and sends the password over SSL. The server responds with a random bit authentication key chosen by the server using a crypto-strength PRNG.

The client app stores this auth key permanently in app-local storage. The server remembers the association between this auth key and the user's account permanently. All future requests from the client app are authenticated using this auth key, as follows: you append a parameter to the end of the URL that holds the HMAC under the auth key assigned to this client of the rest of the URL, any POST data, and any other state that the server will taken into account.

As long as all requests are idempotent e. However, it has some security limitations. It does not protect confidentiality. It also does not protect other request headers, response data, and all sorts of other stuff. For this reason, it is not as secure as just using SSL. For instance, a site built using this approach likely will not be secure against man-in-the-middle attacks, due to the amount of other stuff that isn't protected by a HMAC, and thus won't be safe to use on an open Wifi network.

For this reason, I suggest you just use SSL across the board and simplify your life, rather than trying to invent your own cryptographic request authentication format. Security against password guessing.

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C/C++ Math Library - 22 - HMAC/PBKDF2

DK = PBKDF2 (PRF, Password, Salt, c, dkLen) where: PRF is a pseudorandom function of two parameters with output length hLen (e.g., a keyed HMAC) Password is the master password . Feb 08,  · Isomorphic wrapper for the PBKDF2-HMAC key derivation function. - GitHub - fabiospampinato/crypto-pbkdf2-hmac: Isomorphic wrapper for the PBKDF2-HMAC key . Mar 09,  · Python pbkdf2_hmac vs JavaScript casinotop1xbet.website2Sync inconsistent hash. Ask Question Asked 5 years, 6 months ago. Modified 5 years, 6 months ago. Viewed times 1 .