Game G2 definition

Game G2. In this game, we reject an authenticator that is sent without having been asked to the oracle H1. It makes a di erence if one rejects such an authenticator that is actually valid. But this, of course, happens only with negligible probability: G2 and G1 are statistically indistinguishable.
Sample 1Sample 2
Game G2. The game is transferred from G1 is used to simulate active attacks by adding H1, H2 and Send oracles in which A tries to forge messages. By arbitrarily issuing queries to H1, H2, A attempts q2 q2 to capture collisions. The probability of collisions is at most ( H1 + H2 ) according to the birthday |H1 | |H2 | 2 p paradox. The probability of collisions in the transcripts is at most (qsend +qexe ) . Therefore, we get: q2 q2 (q + q )2 H1 H2 exe send |Pr[Succ1] − Pr[Succ2]| ≤ 2 | H1 | + 2 | H2 | +
Sample 1Sample 2
Game G2. Let Enc be the event when the adversary makes a hash oracle query involving some (IDi, xi) and the same hash query was asked by the a protocol participant (user or U0). This can be checked from the list of hash that is maintained. If such an event occurs it means, adversary has been able to attack the encryption scheme. The probability of success against the encryption scheme after making qs queries is qs ∗ Succenc(A ). The game is identical to G1 except when enc occurs. Thus the total winning probability of the game Pr(Win2) − Pr(Win1) ≤ qs ∗ Succenc(A )) Combining all the results, we obtain Pr(Win0) ≤ N ∗ Succτ(A )+ qs ∗ Succenc(A ) Thus, according to our security assumptions, the probability of the polynomially bound adversary to win the game is negligible.
Sample 1

Examples of Game G2 in a sentence

  • Game G2: The game G2 is identical to G1 except that ∆ aborts if a nonceused in some Send query has already been used in some Execute or Send query before.

  • Game G2 Game G2 is the same as game G1 except that we make the simulation abort if certain conditions are not satisfied.

  • It follows thatPr[GF0 ⇒ 1] ≤ e2(Qs + 1) Pr[GF1 ⇒ 1] .In Game G2 (see Fig.

  • Game G2 is the same as game G1 except that we make the simulation abort if certain conditions are not satisfied.

  • Game G2 is the same as game G1 except that we add the following rule: we choose at random two values i0 in [1, n] and c0 in [1, Q].

  • Game G2: In this game, the challenger changes the way it computes dpk,k when responding to QDKeyGen queries.

  • By the security property of the CHSS, the distribution of (ek, s1—σ) in this game is computationally indistinguishable from the distribution of (ek, s1—σ) in G0,hence we have Pr[b0 b1] = negl(λ).– Game G2.

  • Game G2 sets bad1 only if A has made some ROA query (xkr, mr, nr) beforehand, such that for the Mr and (m0, m1, xk, n) ← Mr, there are some b ∈ {0, 1} and some i ∈ [|n|] satisfying (xk[i], mb[i], n[i]) = (xk , m , n ).

  • Game G2 instantiates exactly the game defining the (S, Φd)-unique-input-prf-rka security of NR∗ when b = 1, so the only difference with game G1 is in the way queries x with x ∈/ S are handled.

  • On principle, the fundamental problem of the social selection of pupils after the fourth year of school remains an issue.


More Definitions of Game G2

Game G2. In this game, we avoid collisions amongst an m or µ value of the current hon- est choice and those of the previous execution, and amongst the hi( ) queries asked by the adversary for i 2, 3, 4 , with probability bounded by the birthday paradox. We can postu- late random oracle queries H0(C, π) and h1(C, π) are respectively free from mutual collisions in the information theoretic sense. Let Collχ be the event that an χ value generated by a Send or Execute query is equal to a value of the previous execution’s corresponding query, or an input to the previous execution’s succeeding Send query. We play the game in a way to abort if the event Collm or Collµ occurs. A new list Coll keeps track of m and µ by saving [Ci, Sj], [in, out], [m, µ] where [χ, ψ] means one of χ and ψ is drawn. The random outputs or inputs must be checked with Coll for a collision in each simulation of send queries. So, this −
Sample 1
Game G2. The game G2 is identical to G1 except that ∆ aborts if a nonce used in some Send query has already been used in some Execute or Send query before. We denote the occurrence of the nonce being repeated in some Send query as event E2. Then: | Pr[W in1] - Pr[W in2]| ≤ Pr[E2]. ∆ can detect event E2 as he can track all nonces generated, via the Sessions table. Calculation of Pr[E2]: Clearly the probability of event E2 happening is . qs(qex+qs) 2k1 Game G3: In game G3, ∆ modifies the way it answers the queries slightly. ∆ chooses a DDH-tuple (g, gra , grb , grarb ). ∆ follows the protocol as before to generate query responses but changes the way it generates the blinded secrets used in the transcript. The change is as follows: − Whenever a blinded secret is to be generated for some session participant Mi, instead of raising the group generator g to a randomly chosen number ri (from [1, q 1], as specified by the protocol), it raises grb (from the given tuple) to ri. Thus, in brief, ∆ uses the value grbri as blinded secret for participant Mi in the transcript. The corresponding blinded response is generated as before by raising the blinded secret to the group leader’s secret rl (which is also randomly chosen from [1, q − 1], as specified by the protocol). Also, ∆ stores the blinded secret so generated and the corresponding ri in table L. In this way, ∆ knows all blinded secrets generated by him during the game and their corresponding secrets. Clearly from the adversary’s point of view there is no change in the game. Thus | Pr[W in2] = Pr[W in3]|.
Sample 1

Related to Game G2

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