Constructions of secure channel encoders, based on secret pruning, are considered in this paper. The key defines how pruning is applied on a mother convolutional code. This results in a secret subspace that legitimate users are using to perform decoding, in contrast to an eavesdropper that employs the mother code. Both reliability and security aspects of the joint scheme are treated. We derive the expected weight enumerating function of the secret subcode and show that the legitimate users achieve a better performance (that depends on the pruning rate) in terms of word and bit error rate compared with the eavesdroppers. The security relies on the notion of indistinguishability against chosen plaintext attacks. The security proofs are given in the random oracle model, and it is shown that a randomized version of the proposed joint scheme is semantically secure by relying on the hardness of the learning parities with noise problem. The above-mentioned results are achieved by introducing a new model for physical encryption to consider the contribution of the channel noise to the system's security.

A cooperative jamming protocol is studied in this paper and its ability to protect the communications of a pair of users in the presence of an eavesdropper. Communication of users is assisted by many helping interferers, assuming knowledge of channel state information. Closed form expressions are given for the optimal weights and power allocation maximizing the difference in the SNR between destination and eavesdropper; these are determined under transmit, reliability, and security constraints. Simulations show that noticeable improvements, of more than 30dB, may be attained in the SNR difference compared to the non-cooperative case.

Secure encoders are schemes aiming at providing both reliability and security in a lightweight fashion. In this paper, a secure channel encoder based on turbo codes is constructed by using the techniques of puncturing and trellis pruning. Puncturing is employed to downgrade the performance of the code and thus increase the error probability experienced by an eavesdropper at a given SNR. This has the advantage that various cryptanalytic attacks, whose complexity depends on the error probability, will become infeasible. On the other hand, trellis pruning is implemented in a secret fashion to enable legitimate users communicate reliably. An algorithm that, based on EXIT analysis, computes the corresponding puncturing and pruning rates is proposed.

This paper investigates the security offered by PHY schemes that are well oriented towards jointly providing security and protection form channel errors. In particular, we focus on constructions that were recently proposed in the literature, whose security relies on the secrecy of parameters defining the encoding/decoding process of convolutional codes. Such schemes were shown to be quite promising in terms of error correcting capabilities, but no security analysis was provided to justify their use for wireless communications. To this end, we evaluate the strength of the PHY security scheme against chosen plaintext attacks, as well as known plaintext attacks that are built upon an extension of the known algorithm of Blum, Kalai, and Wasserman. The security analysis derives the parameters to be used for achieving a high security level against such type of attacks with low encoding and decoding complexity.

Constructions of secure channel encoders based on trellis pruning are considered in this paper. The key defines how pruning is applied on the trellis of a mother convolutional code; this results into a secret pruned trellis that legitimate users are using to perform decoding, in contrast to the eavesdroppers that employ the full mother trellis diagram. We focus on two special forms of the pruning function, and in each case we compute the expected weight enumerating function of the secret pruned code. The theoretical analysis ensures that the legitimate users achieve superior performance, in terms of word and bit error rate, than the eavesdroppers, which depends on the pruning rate. We also derive design guidelines on properties that mother encoders must have to fully exploit the proposed scheme. Simulation results also show the potential of catastrophic encoders for PHY security and yet the ability of the legitimate users to communicate reliably.

In this study, a method is presented for constructing convolutional codes of variable rate and decoding complexity. Starting with an (n,1,m) mother code, the techniques of puncturing and path pruning are utilized in order to construct large families of convolutional codes of various code rates and complexity. Decoding is performed using the trellis of the mother code.

It is known that an (n,n-1) non catastrophic antipodal punctured convolutional encoder of memory m is minimal. That is, the corresponding code cannot be produced by an encoder of smaller memory size. In this letter it is shown that the trellis module of a code produced by an (n,n-1) non catastrophic punctured convolutional encoder is optimum, if and only if the encoder is antipodal.

In this paper, new constructions of low trellis complexity convolutional codes are presented. New codes are found by searching into a specific class of time varying convolutional codes, which is shaped by some basic properties and search restrictions. An efficient technique for obtaining minimal trellis modules for the proposed codes is provided. Finally, new low complexity convolutional codes of various code rates and memory sizes are tabulated.

In this paper new constructions of low trellis complexity convolutional codes are presented. New codes are found by searching into a specific class of time varying convolutional codes, which is shaped by some basic properties and search restrictions. An efficient technique for obtaining minimal trellis modules for the proposed codes is provided. Finally, new low complexity convolutional codes of various code rates and memory sizes are tabulated.