X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/prng_gpu.git/blobdiff_plain/725505ba2683a3f4a5a00955d99b175d2a141d69..fbd01ece23dac6b48c01009d7cdb8dd98dd647ce:/reponse.tex?ds=sidebyside

diff --git a/reponse.tex b/reponse.tex
index a0d3da6..afa4a2d 100644
--- a/reponse.tex
+++ b/reponse.tex
@@ -27,7 +27,7 @@ In section 1, we have added a small summary of test measurements performed with
 \textit{Section 9:
 The authors say they replace the xor-like PRNG with a cryptographically secure one, BBS, but then proceed to use extremely small values, as far as a cryptographer is concerned (modulus of $2^{16}$), in the computation  due  to the need to use 32 bit integers in the GPU and combine bits from multiple BBS generated values, but they never prove (or even discuss) how this  can be considered cryptographically secure due to the small  individual values. At the end of 9.1, the authors say $S^n$ is secure because it is formed from bits from the BBS generator, but do not consider if the use of such small values will lead to exhaust searches to determine individual bits. The authors either need to remove all of section 9 and or prove the resulting PRNG is cryptographically secure.}
 
-A new section (namely, Section 8.2) and a discussion at the end of Section 9.1 have been added to measure practically the security of the generator.
+A section in the Annex document (namely, Section~3) and a discussion at the end of Section 9.1 have been added to measure practically the security of the generator.
 
 \bigskip
 \textit{In the conclusion:
@@ -102,7 +102,7 @@ generator  is  not cryptographically  secure  in  the  example disputed  by  the
 reviewer, we  cannot apply this  result. Indeed the  first part of  the document
 does  not  deal  with  security,  but  it investigates  the  speed,  chaos,  and
 statistical quality of  PRNGs.  A sentence has been added  to clarify this point
-at the end of Section 5.4.
+at the end of Section 5.
 
 
 \bigskip
@@ -142,11 +142,11 @@ ideas are the same: a cryptographically secured PRNG can be broken
 
 Nevertheless, new arguments have been added in several places of the revision of
 our paper, concerning more concrete  and practical aspects of security, like the
-$(T,\varepsilon)-$security notion  of Section  8.2. Such a  practical evaluation
+$(T,\varepsilon)-$security notion  of Section  3 of the Annex document. Such a  practical evaluation
 has not yet been performed for the  GPU version of our PRNG, and the reviewer is
 right  to think  that these  aspects are  fundamental to  determine  whether the
 proposed PRNG can or cannot face the attacks. A similar formula to what has been
-computed  for the  BBS (as  in Section  8.2) must  be found  in future  work, to
+computed  for the  BBS (as  in Section  3 of the Annexe document) must  be found  in future  work, to
 measure the amount of time need by an attacker to break the proposed generator when
 considering  the parameters  we have  chosen  (this computation  is a  difficult
 task).  Sentences have been added in  several places (like at the end of Section
@@ -156,7 +156,8 @@ task).  Sentences have been added in  several places (like at the end of Section
 \textit{To sum it up, while the theoretical part of the paper is interesting, the practical results leave much to be desired, and do not back the thesis that chaos improves some quality metric of the generators.} 
 
 
-We hope now that, with the new sections added to the document (like Section 5), we have convinced the reviewers that adding chaotic properties in 
+We hope now that, with the new pieces of information added to the documents
+(like Section 3 of the Annex document), we have convinced the reviewers that adding chaotic properties in 
 existing generators can be of interest.
 
 \bigskip