Blockchain Papers

Jean‐Guillaume Dumas, Pascal Lafourcade, Daiki Miyahara, Takaaki Mizuki · 6 authors

No abstract is available for this record.

Francisca Adoma

The importance of big data in machine learning cannot be overemphasized in recent times. Through the evolution of big data, most scientific technologies that relied heavily on enormous data in solving complex issues in human lives gained grounds; machine learning is an instance of these technologies. Various machine learning models that yield groundbreaking throughputs with high efficiency rates in predicting, detecting, classifying, discovering and acquiring in-depth knowledge about events that would otherwise be very difficult to ascertain have been made possible due to big data. Although big data has undoubtedly helped in the field of machine learning research ,over the years, its mode of acquisition has posed great challenge in industries,education and other agencies that obtained them for various purposes. This is because these large quantities of data cannot be stored on personal computers with limited storage capabicity but required the use of high storage capacity servers for effective storage. These servers may be owned by a group of companies or individuals who had the singular priviledge to modify the data in their possession as and when deemed relevant thus the creation of a centralized data storage environment. These were mostly refered to as the Third Parties (TP) in the data acquisition process. For the services they rendered, these trusted parties priced data in their possession expensively. The adverse effect is a limitation on various researches that could help solve a number of problems in human lives. It is worth mentioning that the security of these data being purchased expensively cannot be even assured limiting various researches that thrive on secured data. In order to curb these occurrences and have better machine learning models, the incorporation of Blockchain Technology databases into machine learning. This paper discusses the concept of big data, Machine Learning and Blockchains. It further discusses how Big data has impacted the Machine learning Community, the significance of Machine Learning and how the BlockChain Technology could be used similarly impact the Machine Learning Community. The aim of this paper is to encourge further research in incoporating the BlockChain Technology into Machine Learning.

Jérémy Charlier, Radu State, Jean Hilger

Background: Past few months have seen the rise of blockchain and cryptocurrencies. In this context, the Ethereum platform, an open-source blockchain-based platform using Ether cryptocurrency, has been designed to use smart contracts programs. These are self-executing blockchain contracts. Due to their high volume of transactions, analyzing their behavior is very challenging. We address this challenge in our paper. Methods: We develop for this purpose an innovative approach based on the non-negative tensor decomposition Paratuck2 combined with long short-term memory. The objective is to assess if predictive analysis can forecast smart contracts activities over time. Three statistical tests are performed on the predictive analytics, the mean absolute percentage error, the mean directional accuracy and the Jaccard distance. Results: Among dozens of GB of transactions, the Paratuck2 tensor decomposition allows asymmetric modeling of the smart contracts. Furthermore, it highlights time dependent latent groups. The latent activities are modeled by the long short term memory network for predictive analytics. The highly accurate predictions underline the accuracy of the method and show that blockchain activities are not pure randomness. Conclusion: Herein, we are able to detect the most active contracts, and predict their behavior. In the context of future regulations, our approach opens new perspective for monitoring blockchain activities.

T. S Brinda

Wireless sensor network (WSN) have become a prominent solution for various interesting applications like security surveillance and monitoring of geographical areas. Various types of sensors are used and deployed in the network to collect useful physical parameters and some highly sensitive information is then been transmitted between the nodes and to the base station, without any human intervention. Hence, message authenticity and security are major requirements in WSN. Since the cryptographic schemes used for wired networks tend to exhaust wireless sensor network resources, they cannot be directly used in sensor networks. In this, the zero knowledge protocol (ZKP) is investigated that it is an under applied authentication mechanism used to identify compromised nodes from genuine ones. Here the Zero Knowledge Protocol (ZKP) is implemented in the network for the authentication and verification of sender sensor nodes before transmitting any sensitive information. The proposed scheme addresses the improvement in the security while maintaining the message confidentiality. In proposed scheme an optimal number of challenge questions are also used to maintain a balance between the added security and the increase in cost. Increase in the number of challenge question makes up to the reduced key size thus providing an improved security. The proposed scheme was assessed based on the mat lab simulation and an analysis was performed.

Craig Wright

The concept of a Turing machine has been well defined. It would be sufficient to show that Bitcoin uses a dual stack architecture that acts as a dual counter machine. Such systems have already been demonstrated as being Turing complete. We demonstrate that Bitcoin script is a minimal family of which λ and R are members. Further using the compositional product rule and the iteration rule we demonstrate that Bitcoin scripting is Turing complete with the limitations imposed on any realworld computer. This limitation is that there cannot be an infinite tape. Iterations can be simulated using an “unrolled” loop function with allocation to the “Alt” stack. As the product rule states that if A, B are machines, then A.B is also a machine. The iteration rule shows that if A is a machine then (A) is also a machine. Further the minimum power of A under which the observed square of the final configuration is blank. The consequence of these rules is that for every partial recursive function of in variables we can show that it can be evaluated by machine of the proposed family.

Xavier Bultel, Jannik Dreier, Jean‐Guillaume Dumas, Pascal Lafourcade

Akari, Takuzu, Kakuro and KenKen are logic games similar to Sudoku. In Akari, a labyrinth on a grid has to be lit by placing lanterns, respecting various constraints. In Takuzu a grid has to be filled with 0's and 1's, while respecting certain constraints. In Kakuro a grid has to be filled with numbers such that the sums per row and column match given values; similarly in KenKen a grid has to be filled with numbers such that in given areas the product, sum, difference or quotient equals a given value. We give physical algorithms to realize zero-knowledge proofs for these games which allow a player to show that he knows a solution without revealing it. These interactive proofs can be realized with simple office material as they only rely on cards and envelopes. Moreover, we formalize our algorithms and prove their security.

Iftach Haitner, Omer Reingold

Interactive hashing, introduced by Naor, Ostrovsky, Venkatesan, and Yung (J. Cryptol. 11(2):87–108, 1998 ), plays an important role in many cryptographic protocols. In particular, interactive hashing is a major component in all known constructions of statistically hiding commitment schemes and of statistical zero-knowledge arguments based on general one-way permutations/functions. Interactive hashing with respect to a one-way function f is a two-party protocol that enables a sender who knows y = f ( x ) to transfer a random hash z = h ( y ) to a receiver such that the sender is committed to y : the sender cannot come up with x and x ′ such that f ( x )≠ f ( x ′), but h ( f ( x ))= h ( f ( x ′))= z . Specifically, if f is a permutation and h is a two-to-one hash function, then the receiver does not learn which of the two preimages { y , y ′}= h −1 ( z ) is the one the sender can invert with respect to f . This paper reexamines the notion of interactive hashing, and proves the security of a variant of the Naor et al. protocol, which yields a more versatile interactive hashing theorem. When applying our new proof to (an equivalent variant of) the Naor et al. protocol, we get an alternative proof for this protocol that seems simpler and more intuitive than the original one, and achieves better parameters (in terms of how security preserving the reduction is).

Richard Sabey

The cipher (or athbash, under which name Web3 defines it) is a Hebrew substitution cipher which replaces the first letter of the Hebrew alphabet (aleph, 1\) by the last (tav, ) the second (beth, J) by the last but one (shin, IJI), and so on, unti I we get to the last (ta , n), which i replaced by the first (aleph, 1\). Jan Anderson described it in Fledge Ledge Edge (WW 8. 1997229). Naturally, the idea can be applied to our alphabet; following the precedent set by atbash I name it the azby cipher.