Parisa Babaheidarian

Parisa Babaheidarian, Somayeh Salimi, Panos Papadimitratos

In this paper, we present an achievable security scheme for an interference channel with arbitrary number of users. In this model, each receiver should be able to decode its intended message while it cannot decode any meaningful information regarding messages intended for other receivers. Our scheme achieves individual secure rates which scale linearly with log(SNR) and achieves sum secure rates which is within constant gap of sum secure capacity. To design the encoders at the transmitters side, we combine nested lattice coding, random i.i.d. codes, and cooperative jamming techniques. Asymmetric compute-and-forward framework is used to perform the decoding operation at the receivers. The novelty of our scheme is that it is the first asymptotically optimal achievable scheme for this security scenario which scales to arbitrary number of users and works for any finite-valued SNR. Also, our scheme achieves the upper bound sum secure degrees of freedom of $1$ without using external helpers.

Parisa Babaheidarian, Mark Wallace

Recent work (Baluja, 2017) showed that using a pair of deep encoders and decoders, embedding a full-size secret image into a container image of the same size is achieved. This method distributes the information of the secret image across all color channels of the cover image, thereby, it is difficult to discover the secret image using conventional methods. In this paper, we propose a new steganalysis technique which achieves complete recovery of the embedded secret in steganography images. We incorporate a deep neural network to decode an approximate estimate of the secret image followed by a domain adaptation technique based on generative adversarial networks which transfers the decoded image into a high quality RGB image with details visible to human eyes. Our steganalysis technique can be served as an attack model against which the security level of an arbitrary embedded-based digital watermarking or a steganography algorithm can be evaluated. Furthermore, our method can be used as a general framework to decode a high quality image message from a noisy observation of an encoded message.

Parisa Babaheidarian, Somayeh Salimi

We consider a Gaussian multiple access channel with $K$ transmitters, a (intended) receiver and an external eavesdropper. The transmitters wish to reliably communicate with the receiver while concealing their messages from the eavesdropper. This scenario has been investigated in prior works using two different coding techniques; the random i.i.d. Gaussian coding and the signal alignment coding. Although, the latter offers promising results in a very high SNR regime, extending these results to the finite SNR regime is a challenging task. In this paper, we propose a new lattice alignment scheme based on the compute-and-forward framework which works at any finite SNR. We show that our achievable secure sum rate scales with $\log(\mathrm{SNR})$ and hence, in most SNR regimes, our scheme outperforms the random coding scheme in which the secure sum rate does not grow with power. Furthermore, we show that our result matches the prior work in the infinite SNR regime. Additionally, we analyze our result numerically.