The main purpose of this article is to use tensor multiplications and the relationships between them in the network coding process to deal with destructive attacks and enemy contamination to the information transmission network. As we know, one of the most complex and at the same time the most important threats of coded networks is the contamination and malicious attack that attempts to divert and destroy the information flow by entering, directing and penetrating unauthorized information packets into the information flow in the network. In this research, in order to increase the operational capacity of the information transmission network and also in order to deal with the threats of eavesdropping, destruction and pollution of the network, a mathematical model of random coding of the network called codes made using the simple tensor product of two subspaces has been studied and We obtained new structures of codes with optimized parameters that, in addition to improving the previous results, increase network throughput, reduce information transfer time, increase network safety factor, and reduce energy and bandwidth costs of network consumption. In this direction and in order to deal with network pollution attacks, we have investigated a new class of Abelian circuit codes and using the simple tensor product of two subspaces, we have expressed some methods of constructing new codes.