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Steganographer detection aims to identify the guilty user who utilizes steganographic methods to hide secret information in the spread of multimedia data, especially image data, from a large amount of innocent users on social networks. A true embedding probability map illustrates the probability distribution of embedding secret information in the corresponding images by specific steganographic methods and settings, which has been successfully used as the guidance for content-adaptive steganographic and steganalytic methods. Unfortunately, in real-world situation, the detailed steganographic settings adopted by the guilty user cannot be known in advance. It thus becomes necessary to propose an automatic embedding probability estimation method. In this article, we propose a novel content-adaptive steganographer detection method via embedding probability estimation. The embedding probability estimation is first formulated as a learning-based saliency detection problem and the multi-scale estimated map is then integrated into the CNN to extract steganalytic features. Finally, the guilty user is detected via an efficient Gaussian vote method with the extracted steganalytic features. The experimental results prove that the proposed method is superior to the state-of-the-art methods in both spatial and frequency domains.

As the use of network services increase, security is considered as a crucial and major issue in the network. Several computers connected with the network play an essential role in business and other applications running over the network to provide services. Therefore, we need to search out the best ways to protect the system. One of the methods is to provide security to the system and analyze network traffic through intrusion detection or intrusion prevention. In this paper, a hybrid intrusion detection framework is suggested. Proposed hybrid IDS is a combination of two machine learning algorithms J48 DT and SVM. To select relevant features from the KDD CUP dataset Particle Swarm Optimization is used. WEKA is used to implement classification on the KDD CUP dataset. The dataset is divided into ratios of 60:40, 70:30, and 80:20 for training and testing purpose. The experiment result showed 99.1% accuracy, 99.6% detection rate and 1.0% FAR for 60:40 datasets whereas accuracy, detection rate and FAR for 70:30 datasets are 99.2%, 99.6% and 0.9% respectively for 80:20 datasets 99.1%, 99.6% and 0.9% respectively.

The 2013 German Bundestag election is analyzed in the same way as the 2017 Bundestag election is analyzed in Chapter 8. The positions of 28 German parties on 38 topical policy issues are compared with the statistics of relevant public opinion polls. The results are summarized in the indices of popularity (the average percentage of the population represented) and universality (frequency of representing a majority) at both the party and the coalition levels. We show that the election winners are not the best representatives of public opinion, whereas the best representatives receive too few votes to be allocated Bundestag seats. Since the same problem is inherent in the 2009, 2013 and 2017 Bundestag elections, we conclude that such an election failure is not occasional but appears to have a systemic character. To overcome it, the Third Vote method introduced in Chapter 10 is applied to hypothetically reallocate the Bundestag seats, resulting, as previously, in a significant gain in the Bundestag’s representativeness.

The introduction of remote electoral methods (also, e.g., postal voting) serves the citizen in providing an easily accessible and comfortable means of voting. In addition, remote voting is also considered a viable alternative for disenfranchised voters whose participation in elections has always been dependent on the methods they are offered – voters living or residing permanently abroad, voters who are living in conditions which make it difficult for them to attend elections for geographical reasons and voters with disabilities. All these voters need to make extra efforts in participating in the democratic process, and in all these cases, the principle of universality (or general elections) prevails over the possible concerns connected with the way of voting.