Improving Remote Voting Security with Code Voting

One of the major problems that prevents the spread of elections with the possibility of remote voting over electronic networks, also called Internet Voting, is the use of unreliable client platforms, such as the voter's computer and the Internet infrastructure connecting it to the election server. A computer connected to the Internet is exposed to viruses, worms, Trojans, spyware, malware and other threats that can compromise the election's integrity. For instance, it is possible to write a virus that changes the voter's vote to a predetermined vote on election's day. Another possible attack is the creation of a fake election web site where the voter uses a malicious vote program on the web site that manipulates the voter's vote (phishing/pharming attack). Such attacks may not disturb the election protocol, therefore can remain undetected in the eyes of the election auditors. We propose the use of Code Voting to overcome insecurity of the client platform. Code Voting consists in creating a secure communication channel to communicate the voter's vote between the voter and a trusted component attached to the voter's computer. Consequently, no one controlling the voter's computer can change the his/her's vote. The trusted component can then process the vote according to a cryptographic voting protocol to enable cryptographic verification at the server's side.

Augmented LDPC Graph for Distributed Video Coding with Multiple Side Information

The advances made in channel-capacity codes, such as turbo codes and low-density parity-check (LDPC) codes, have played a major role in the emerging distributed source coding paradigm. LDPC codes can be easily adapted to new source coding strategies due to their natural representation as bipartite graphs and the use of quasi-optimal decoding algorithms, such as belief propagation. This paper tackles a relevant scenario in distributedvideo coding: lossy source coding when multiple side information (SI) hypotheses are available at the decoder, each one correlated with the source according to different correlation noise channels. Thus, it is proposed to exploit multiple SI hypotheses through an efficient joint decoding technique withmultiple LDPC syndrome decoders that exchange information to obtain coding efficiency improvements. At the decoder side, the multiple SI hypotheses are created with motion compensated frame interpolation and fused together in a novel iterative LDPC based Slepian-Wolf decoding algorithm. With the creation of multiple SI hypotheses and the proposed decoding algorithm, bitrate savings up to 8.0% are obtained for similar decoded quality.

Design and performance of a novel low-density parity-check code for distributed video coding

Low-density parity-check (LDPC) codes are nowadays one of the hottest topics in coding theory, notably due to their advantages in terms of bit error rate performance and low complexity. In order to exploit the potential of the Wyner-Ziv coding paradigm, practical distributed video coding (DVC) schemes should use powerful error correcting codes with near-capacity performance. In this paper, new ways to design LDPC codes for the DVC paradigm are proposed and studied. The new LDPC solutions rely on merging parity-check nodes, which corresponds to reduce the number of rows in the parity-check matrix. This allows to change gracefully the compression ratio of the source (DCT coefficient bitplane) according to the correlation between the original and the side information. The proposed LDPC codes reach a good performance for a wide range of source correlations and achieve a better RD performance when compared to the popular turbo codes.