cryptography - How decrypt keccak algorithm -


i preparing presentation keccak (http://keccak.noekeon.org/).

in presentation, encrypt plain-text – brings following questions:

  1. what exact role of padding function (how obtain cube of 1600 bits 64 bit)?
  2. after encrypting text, how can decrypt again?

you cannot "decrypt" output of keccak, since isn't encryption algorithm, 1 way hash function. instead, use verifying hash value indeed hash output of particular text (which must know already), calculating hash of text, , comparing output first hash value.


Comments

Post a Comment

Popular posts from this blog

python - How to create a legend for 3D bar in matplotlib? -

Image
given ax = plt.subplot() : ax.bar()[0] can passed plt.legend() . however, ax.bar3d() returns none . how create legend displayed bars? update: passing legend="stuff" ax.bar3d() , calling ax.legend() raises /usr/lib/python2.6/site-packages/matplotlib/axes.py:4368: userwarning: no labeled objects found. use label='...' kwarg on individual plots. warnings.warn("no labeled objects found. " you need use proxy artist legends not supported. this code: from mpl_toolkits.mplot3d import axes3d import matplotlib.pyplot plt import numpy np fig = plt.figure() ax = fig.add_subplot(111, projection='3d') x, y = np.random.rand(2, 100) * 4 hist, xedges, yedges = np.histogram2d(x, y, bins=4) elements = (len(xedges) - 1) * (len(yedges) - 1) xpos, ypos = np.meshgrid(xedges[:-1]+0.25, yedges[:-1]+0.25) xpos = xpos.flatten() ypos = ypos.flatten() zpos = np.zeros(elements) dx = 0.5 * np.ones_like(zpos) dy = dx.copy() dz = hist.flatten() ax...
Read more

java - Multi-Label Document Classification -

i have database in store data based upon following 3 fields: id, text, {labels}. note each text has been assigned more 1 label \ tag \ class. want build model (weka \ rapidminer \ mahout) able recommend \ classify bunch of labels \ tags \ classes given text. i have heard svm , naive bayes classifier, not sure whether support multi-label classification or not. guides me right direction more welcome! the basic multilabel classification method one-vs.-the-rest (ovr), called binary relevance (br). basic idea take off-the-shelf binary classifier, such naive bayes or svm, create k instances of solve k independent classification problems. in python-like pseudocode: for each class k: learner = svm(settings) # example labels = [class_of(x) == k x in samples] learner.learn(samples, labels) then @ prediction time, run each of binary classifiers on sample , collect labels predict positive. (both training , prediction can done in parallel, since problems assumed ...
Read more

php - Dynamic url re-writing using htaccess -

how can rewrite http://mydomain.com/test/master.php?catid=2&subcatid=8 http://mydomain.com/test/master.php/catname/subcat using .htaccess file. once rewritten, how can access these parameters in master.php? note: untested, let me know if doesn't work. rewriterule ^master.php/([a-za-z0-9_-]+)/([a-za-z0-9_-]+)$ /master.php?catid$1&subcatid=$2 [l]
Read more