3,551 research outputs found
Public channel cryptography by synchronization of neural networks and chaotic maps
Two different kinds of synchronization have been applied to cryptography:
Synchronization of chaotic maps by one common external signal and
synchronization of neural networks by mutual learning. By combining these two
mechanisms, where the external signal to the chaotic maps is synchronized by
the nets, we construct a hybrid network which allows a secure generation of
secret encryption keys over a public channel. The security with respect to
attacks, recently proposed by Shamir et al, is increased by chaotic
synchronization.Comment: 4 page
Cryptocurrency with a Conscience: Using Artificial Intelligence to Develop Money that Advances Human Ethical Values
Cryptocurrencies like Bitcoin are offering new avenues for economic empowerment
to individuals around the world. However, they also provide a powerful tool that
facilitates criminal activities such as human trafficking and illegal weapons sales
that cause great harm to individuals and communities. Cryptocurrency advocates
have argued that the ethical dimensions of cryptocurrency are not qualitatively new,
insofar as money has always been understood as a passive instrument that lacks
ethical values and can be used for good or ill purposes. In this paper, we challenge
such a presumption that money must be ‘value-neutral.’ Building on advances in
artificial intelligence, cryptography, and machine ethics, we argue that it is possible
to design artificially intelligent cryptocurrencies that are not ethically neutral but
which autonomously regulate their own use in a way that reflects the ethical values
of particular human beings – or even entire human societies. We propose a technological framework for such cryptocurrencies and then analyse the legal, ethical, and
economic implications of their use. Finally, we suggest that the development of
cryptocurrencies possessing ethical as well as monetary value can provide human
beings with a new economic means of positively influencing the ethos and values
of their societies
Neural Network Contribute to Reverse Cryptographic Processes in Bitcoin Systems: attention on SHA256
Bitcoin is a digital currency created in January 2009 following the housing market crash that promises lower transaction fees than traditional online payment mechanisms. Though each bitcoin transaction is recorded in a public log, the names of buyers and sellers are never revealed. While that keeps bitcoin users' transactions private, it also lets them buy or sell anything without easily tracing it back to them. Bitcoin is based on cryptographic evidence, which therefore does not suffer from the weakness present in a model based on trust in guarantee authorities. The use of cryptography is of crucial importance in the Bitcoin system. In addition to maintaining data secrecy, in the case of Bitcoin, cryptography is used to make it impossible for anyone to spend money from another user's wallet. In our paper, we develop the idea that it is possible to reverse the cryptography process based on hash functions (one-way) through Machine Translation with neural networks. Assuming this hypothesis is true and considering some quantistic algorithms to decrypt certain types of hash functions, we will highlight their effects on the Bitcoin system
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