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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.

Voting algorithms, such as histogram and Hough transforms, are frequently used algorithms in various domains, such as statistics and image processing. Algorithms in these domains may be accelerated using GPUs. Implementing voting algorithms efficiently on a GPU however is far from trivial due to irregularities and unpredictable memory accesses. Existing GPU implementations therefore target only specific voting algorithms while we propose in this work a methodology which targets voting algorithms in general. This methodology is used in gpu-vote, a framework to accelerate current and future voting algorithms on a GPU without significant programming effort. We classify voting algorithms into four categories. We describe a transformation to merge categories which enables gpu-vote to have a single implementation for all voting algorithms. Despite the generality of gpu-vote, being able to handle various voting algorithms, its performance is not compromised. Compared to recently published GPU implementations of the Hough transform and the histogram algorithms, gpu-vote yields a 11% and 38% lower execution time respectively. Additionally, we give an accurate and intuitive performance prediction model for the generalized GPU voting algorithm. Our model can predict the execution time of gpu-vote within an average absolute error of 5%.

Both Norway and England have used the supplementary vote (SV) method to elect mayors. SV was intended to elect mayors with a broad popular mandate, and deemed easy for voters to use. Previous research on English mayoral elections focusing on the supply side of the elections has found that voters supporting minority candidates with their first vote face difficulties using the optional second vote to choose among the remaining two top-candidates in municipalities where there are many candidates in the race. A close race, on the other hand, seems to give voters a helping hand in making this choice. Drawing on these findings, we link data on the 48 Norwegian mayoral races to survey data to further explore how the supply side of the elections and individual voter resources affect effective voting and use of the optional second vote. We use both standard logistic regression and multi-level models as statistical tools. The result reveals that 27 out the 48 elected mayors in Norway came out as majority w...

The Single Transferable Vote (STV) is an attractive way of achieving representation that is proportional in terms of whatever characteristics of candidates voters value. Increasingly sophisticated methods of implementing STV have been advanced to overcome identified limitations of earlier methods. But every refinement comes at a cost of increased difficulty of understanding the vote-counting algorithm and increased cost of undertaking the count. This paper uses votes from actual elections to provide evidence about the frequency with which the choice of a particular STV method affects the outcome, and about the type of difference that different methods make. The most sophisticated STV method is CPO-STV, the comparison of pairs of outcomes by STV. This method avoids sequential exclusions and therefore overcomes the limitations of previous methods, that a paucity of votes in the early stages of a count can lead to the exclusion of a candidate who is the consensus choice of voters whose preferred candidates will be excluded at later stages of the count.

This chapter draws on research into variables influencing Election Officers’ decision-making on e-voting adoption in the UK with additional data from a senior executive of the Association of Electoral Administrators (AEA).

Estonia has implemented a specific form of electronic voting – internet voting – as a method to participate in various types of legally binding elections since 2005. The mitigation of security risks in the method has lead to changes in the voting procedures. Those changes might affect the way we think about traditional voting.

Let \({\mathcal{F}}\) be a family of subsets of the ground set [n] = {1, 2, . . . , n}. For each \({i \in [n]}\) we let \({p(\mathcal{F},i)}\) be the number of pairs of subsets that differ in the element i and exactly one of them is in \({\mathcal{F}}\). We interpret \({p(\mathcal{F},i)}\) as the influence of that element. The normalized Banzhaf vector of \({\mathcal{F}}\), denoted \({B(\mathcal{F})}\), is the vector \({(B(\mathcal{F},1),\dots,B(\mathcal{F},n))}\), where \({B(\mathcal{F},i)=\frac{p(\mathcal{F},i)}{p(\mathcal{F})}}\) and \({p(\mathcal{F})}\) is the sum of all \({p(\mathcal{F},i)}\). The Banzhaf vector has been studied in the context of measuring voting power in voting games as well as in Boolean circuit theory. In this paper we investigate which non-negative vectors of sum 1 can be closely approximated by Banzhaf vectors of simple voting games. In particular, we show that if a vector has most of its weight concentrated in k < n coordinates, then it must be essentially the Banzhaf vector of some simple voting game with n − k dummy voters.

Pilot projects in the area of remote Internet voting have been carried out in several countries. However, legally binding Internet-cast voting is valid in few countries, Estonia being the first country to introduce it at national level. A good communications infrastructure, voters’ high e-readiness, the widespread use of the national e-ID card, which enables secure authentication of on-line voters, and its relatively small population of 1.3 million are the key factors for the success of I-voting in Estonia. This case-study provides a detailed description of the Estonian remote I-voting system, the motivation behind implementing such a system, a short analysis of the experience and problems emerged as well as about future prospects.

This paper presents results of experiments on some data sets using bagging on the MLEM2 rule induction algorithm. Three different methods of ensemble voting, based on support (a non-democratic voting in which ensembles vote with their strengths), strength only (an ensemble with the largest strength decides to which concept a case belongs) and democratic voting (each ensemble has at most one vote) were used. Our conclusions are that though in most cases democratic voting was the best, it is not significantly better than voting based on support. The strength voting was the worst voting method.

Borda's vote method was used by the French Academy from 1796 to 1803 when Napoleon got it abolished. In the laws and regulations of the Academy there are stipulations regarding the election of new members. The practice is demonstrated by some examples from the protocols. In fact, Borda presented two vote methods which he showed would give the same conclusion. The method which has not been in the limelight proves to be the same one as is used for selecting the best player in chess tournaments.

There are many situations wherein a group of individuals (e.g., voters, experts, sports writers) must produce an ordered list of ‘best’ alternatives selected from a given group of alternatives (e.g., candidates, proposals, sports teams). Two long established mechanisms that have been used for this task are ‘Zermelo’s Ranking Method’ (1929) and ‘Borda’s Voting Scheme’ (1781). The main purpose of this paper is to point out that they are, under certain common circumstances, identical. We then show that Zermelo’s Method can be used in situations that Borda’s Method is not designed to handle.

It has been demonstrated that combining the decisions of several classifiers can lead to better recognition results. The combination can be implemented using a variety of schemes, among which voting method is the simplest, but it has been found to be just as effective as more complicated strategies in improving the recognition results. In this paper, we propose a voting method for object location, which can be viewed as generalization of majority vote rule. Using this method, we locate eye centers in face region. The experimental results demonstrate that the locating performance is comparable with other newly proposed eye locating methods. The voting method can be considered as a general fusion scheme for precise location of object.

This paper describes the retrieval approach proposed by the SIG/EVI group of the IRIT research centre in INEX'2004 evaluation. The approach uses a voting method coupled with some processes to answer content only and content and structure queries. This approach is based on previous works we leaded in the context of automatic text categorization.

In 2000 and 2002 the first direct elections for mayors were held in England. They were elected using the supplementary vote method. This article summarises the discussion which led to the adoptation of this electoral system, analyses some of the main arguments used, states some general criteria by which electoral systems can be judged, and evaluates some other possible methods for conducting such elections. It concludes that in the light of at least some general conditions, supplementary vote (SV) is a less desirable way of choosing a mayor than alternative vote (AV) and some other systems. However, it seems as if a simple amendment of the original SV procedure will avoid some of its most apparent problems.

The discussion on electronic voting has so far mostly focused on technical issues, mainly concerning security and privacy. This paper reports an empirical study on how the symbolic values of democracy, as manifested in the act of voting, are considered by e-voters. The study found that the voters in a student election in actions as well as in stated views gave priority to convenience over security and privacy. They voted electronically from home despite uncertainty about the security of the technical system. We argue that this is an indication that the view of the principles of democratic practices will change, and that what might be called an "e-practices mode of thinking" will to some extent prevail over a "rigid democracy mode".