 First, let me show you our results, and then I'll give you some background on the journalistic. In particular, I clarify the relationship among the five decisions of the journalistic, and I will explain the information of the journalistic to investigate your own compressiveness. And I propose a three-round journalistic protocol and demonstrate its journalistic property. And finally, I conclude. Let me show you our results. I'm going to present a fast construction of three-round journalistic protocol for any type of journalistic. And this is not the approximate amount of journalistic, but the tip of journalistic on income journalistic. This is a bigger notion of journalistic. And in order to demonstrate our journalistic property, I'm going to introduce a new simulation technique. And this is a non-broadcast simulation. And it's based on the computer assumption for strong digital problems. Yeah, I start by reviewing the notion of interactive protocols for journalistic problems. We consider two-party protocols. But the browser and the data, they take a common input text. And the browser tries to convince the browser that x belongs to language app through the interaction. And the interactive protocol requires two conditions. One is the completion and the other is the soundness. The completeness means if x belongs to language app, then the browser always accepts it. And soundness requires if x does not belong to language app, then any cheating program cannot make the browser accept it. So the probability that the browser accepts is very small and it's endless. And the language is a special property for interactive protocols. It requires means that any cheating program contains no information by drafting in the program. And this notion is summarized based on the simulation paradigm. So for any cheating verifier, we have to test the simulator s and such that the two distributions are computationally distributed. The one distribution is the verifier's full conversation. It means the full conversation of verifiers gets by interacting with the program. And the second distribution is the output distribution of the simulator test. So this means the simulator can output the full conversation of the verifier. And that induces the program. And we consider two dimensions in this equation, in this formalization. One dimension is about Algerian life. In some definitions, the verifiers are allowed to take any Algerian. And in other definitions, the verifiers are allowed. And the other dimension is about the computational model of the verifier and the simulator. In the uniform model, they are modeled by probability for non-uniform models. And in the non-uniform model, they are modeled by polynomial size size. So here we have all kinds of distribution of their life. The GNR's life is a horizontal distribution. And the interior of the life, here is the case. And the non-uniform of the life, and in the case, and finally, Algerian, in the case, non-uniform of the life. And our proposal for the program satisfies this notion of distribution. There is another... There is another distribution of the life. It's a graph of distribution of their life. And this is the most formal thing, because all non-uniform life properties have been demonstrated using this notion, using the black box simulation. So all non-uniform life possibilities are near the case. And this distribution requires the existence of a single universal simulator. It uses any cheating verifier in the black box. This notion is formalized as follows. Now we have our five kinds of distributions, so let me show the relationships among them. ESPK is the strongest distribution, so ESPK implies all other definitions. And AIGK is also absolutely... ESPK is the most suitable for practical application, field application. And AIGK is also considered suitable for field graphic application. This is because AIGK is closed under the CK surface. But no, GMRGK is not considered suitable for field graphic application, because GMRGK is not closed under CK surface. And our achieve the definition AIGK is also closed under CK surface. But unfortunately, AIGK does not imply AIGK. And this is because there is a protocol which satisfies AIGK, but not AIGK. So I don't know whether AIGK is suitable for field graphic application. Let me explain our motivation. Our motivation is to investigate the Royal Bounds and the ground complexity. And this table shows the rounds of Royal Bounds regarding 3D definitions. For example, Royal Bounds regarding ESPK is 3D. And this is because the 3D Rounds ESPK protocol is only for PTP language. And the PTP language has 3D at the night. So we can consider 3D Royal Bounds. And in addition to that, this Royal Bound is actually tight. Because it is well known that it is the 4 rounds ESPK protocol for any PTP language. And the Royal Bounds regarding AIGK or AIGK are also known there too. But it is unknown whether these Royal Bounds are actually tight. So in other words, it is an open program with the 3 round AIGK or AIGK protocol or non-TBI language like such as empty language. And in this talk, we solved this program with respect to the AIGK. But our results does not apply to AIGK. So this program is still open with respect to the AIGK. Let me explain how to construct a 3 round AIGK protocol. Our starting protocol, our starting plot point is a 3 round public point. For instance, there is a nice group who has an empty complete language. M1 and M2 are proved as a message. And the Y is a verifier public point. When the verifier receives an M2, it checks if M2 is valid. And it is true that the verifier accepts common text. And the type of example of starting protocol is a carrier composition of ground seronaric group for Hamiltonian static program. And this is an empty complete language. And I want to transform this protocol into another 3 round protocol which satisfies the seronaric property against any shipping verifier. So our approach is simple. We place the verifier's public point via an interruption between the prove-up and the verifier. And we use some standard notation which relates to the speed-provided program. It is a prime such as Q2 times Q plus 3 and Gs and Evans for all the Qs. Unfortunately, we only say this question for water p. I'd like to present the seronaric protocol. As you see, the red message is added to the static protocol. And the Y is generated by an interruption, the group and the verifier. And in the first round, Groober generates an M1 in QG and picks a random number K and the computer, Dr. W, sends them to the verifier, picks a random number B and the computer, Dr. B and Dr. X, and then sends to the Groober. And Groober checks his FC code for P2K. And if it is true, Groober picks a random number C and then computes C and Y and the computer also computes M2 according to the static protocol and sends to the verifier. And the verifier generally checks the Y code C2B and M2 is carried. Because conditions are satisfied, verifier accepts the command to take it. So this check is important for the knowledge property and this check is important for soundness function. I'd like to demonstrate that I'd like to show this protocol satisfies the veronaric property. And to the source, we have to construct a simulator. Before constructing a simulator, let me observe the property of this protocol. This protocol is Noroka's fabric point protocol. Because more B is the secret point of the verifier. And because it is hard to compute more B from the capital V and capital S. So I designed this protocol so that as long as B is secret, the soundness condition is satisfied. And yet, once B is revealed, the soundness condition is no longer satisfied. So our observation is as follows. Once the simulator gets secret point B, the simulation is easy to do. And a question arises here. And the question is how the simulator can get secret point B? And in order to answer this question, I introduced a computational assumption for strong internal assumption. This slide focuses on the first round and the second round. It is easy to see that if verifier holds a specified protocol, the verifier always passes the proof as check. But it seems that verifiers must know the secret point B in order to pass the proof as check. So I assume that any cheating verifier cannot pass the proof as check without knowing the secret point B. I define the strong initial assumption from the non-uniform models. We consider two circuit farming. A circuit C takes a... A circuit C is similar to the verifier's computation. A circuit C takes as input PQG and A. And try to output the keter B and X and satisfy the physical B to A. And this corresponds to a proof as check. And we consider another circuit C prime. C prime takes same input and output, but not only keter B, keter S, but also secret point B. And S D H A 1 says for any circuit C, take this turn, the circuit C prime. And if X is called P to A, then it holds a B for G Q B. So this means that whenever... Whenever a circuit C adds to the BX, satisfying the X equal B to A, the circuit C knows the secret point B. And this assumption is fundamentally different from the standard complex assumption, such as a one-way function. Because there are two quantifiers. In the standard complex assumption, there is only one quantifier. So this assumption seems very strong, but I believe this assumption is crazy. And I can prove that a strongly mechanical assumption 1 implies a mechanical assumption. And this is why we call this assumption a strong digital assumption. Let me explain, let me sketch the proof of your knowledge. Let me stress, you can no longer use this black approximation technique. So we need no black approximation technique. And now I know that under S D H A 1, for any cheating verifier we have, there exists another cheating verifier, we have C prime. And we have C prime under the secret point B. Our idea is very simple, our idea is to use we have C prime as a black force. We don't use we have as a black force. And so that the simulator can get, the simulator can get secret point B. So we have prime and be considered as a secret point instructor. And this is our prime of the simulation process. In the past step, the simulator runs the honest verifier simulator of the starting protocol. So that the simulator gets a conversation of starting protocol M 1, Y and M 2. And step 2 is important study. Simulator uses we have prime as a black force. And as a result, the simulator can get secret point B. And once B is known, it is easy to compute that the system is prime of the white force C B B. And this is, this was on the verifier set. And finally, the simulator can have a bit full conversation. And so this is not a black force simulation because the simulator never use we have prime as a black force. It's easy, we have prime as a black force. So let me explain, let me discuss why our proposed protocol was being AI NGK. Not AI NGK. So former architects and the material life are given no uniformity to the verifier. So therefore, SDHA 1 must be formalized in the non-uniform model. And as a result, our simulator is non-uniform, polytomericized, slagged, and so our protocol only achieved AI NGK, but not AI SCK. Before I conclude, let me introduce a related bug. I was not aware of the Dengar flag when I was writing the setup of our paper. And he introduces SDHA at the fifth conference in 1901. This is the title of his paper. His purpose is to construct a public liquid system against a secure guest to decide the test attack. So his purpose is different from ours. But interestingly, he also pointed out that SDHA implied non-black force simulation technique. However, he didn't present a three-rands-in-narrate or non-trivial values, as I will deal with. In conclusion, I have proposed a three-rands-in-narrate protocol. And I have shown under SDHA 1 our protocol satisfies AI NGK. I did not mention about the soundness, but the soundness function is satisfied under SDHA 2. And this is a severe assumption to SDHA 1. So I conclude with our 7 which says there is just a three-rands-in-nGK argument for any NGK argument under SDHA. That's all. Thank you. We have time for one question. We pronounce Norman Perth's words.