Anonymity and privacy in the electoral process are mandatory features found in any democratic society, and many authors consider these fundamental civil liberties and rights. During the election process, every voter must be identified as eligible, but after casting a vote, the voter must stay anonymous, assuring voter and vote unlinkability. Voter anonymity and privacy are the most critical issues and challenges of almost all electronic voting systems. However, vote immutability must be assured as well, which is a problem in many new democracies, and Blockchain as a distributed technology meets this data immutability requirement. Our paper analyzes current solutions in Blockchain and proposes a new approach through the combination of two different Blockchains to achieve privacy and anonymity. The first Blockchain will be used for key management, while the second will store anonymous votes. The encrypted vote is salted with a nonce, hashed, and finally digitally signed with the voter’s private key, and by mixing the timestamp of votes and shuffling the order of cast votes, the chances of linking the vote to the voter will be reduced. Adopting this approach with Blockchain technology will significantly transform the current voting process by guaranteeing anonymity and privacy.

Personal mobile devices currently have access to a significant portion of their user's private sensitive data and are increasingly used for processing mobile payments. Consequently, securing access to these mobile devices is a requirement for securing access to the sensitive data and potentially costly services. Face authentication is one of the promising biometrics-based user authentication mechanisms that has been widely available in this era of mobile computing. With a built-in camera capability on smartphones, tablets, and laptops, face authentication provides an attractive alternative of legacy passwords for its memory-less authentication process, which is so sophisticated that it can unlock the device faster than a fingerprint. Nevertheless, face authentication in the context of smartphones has proven to be vulnerable to attacks. In most current implementations, a sufficiently high-resolution face image displayed on another mobile device will be enough to circumvent security measures and bypass the authentication process. In order to prevent such bypass attacks, gesture recognition together with location is proposed to be additionally modeled. Gestures provide a faster and more convenient method of authentication compared to a complex password. The focus of this paper is to build a secure authentication system with face, location and gesture recognition as components. User gestures and location data are a sequence of time series; therefore, in this paper we propose to use unsupervised learning in the long short-term memory recurrent neural network to actively learn to recognize, group and discriminate user gestures and location. Moreover, a clustering-based technique is also implemented for recognizing gestures and location.

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Recently crowdsourcing is being established as the new platform for capturing ideas from multiple users, i.e., the crowd. Many companies have already shifted their approach towards utilising the power of the crowd. Transparency and quality of election process is the main factor for acknowledging the general election results. Voters, crowd feedback can be utilised to maintain a desired election process transparency and quality. This paper presents an efficient solution using crowdsourcing techniques for increasing transparency and the quality of election processes through a simple feedback web form in polling stations. These polling stations are securely connected to central election commission monitoring room, where the overall transparency and quality in national scale can be monitored. The survey conducted with more than 600 respondents shows that this approach will be acceptable from citizens and will increase the overall transparency, quality, and acceptance of election results.

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