Modeling Suspicious Email Detection using Enhanced Feature Selection

The paper presents a suspicious email detection model which incorporates enhanced feature selection. In the paper we proposed the use of feature selection strategies along with classification technique for terrorists email detection. The presented model focuses on the evaluation of machine learning algorithms such as decision tree (ID3), logistic regression, Na\"ive Bayes (NB), and Support Vector Machine (SVM) for detecting emails containing suspicious content. In the literature, various algorithms achieved good accuracy for the desired task. However, the results achieved by those algorithms can be further improved by using appropriate feature selection mechanisms. We have identified the use of a specific feature selection scheme that improves the performance of the existing algorithms

Early DDoS Detection Based on Data Mining Techniques

Part 5: Short PapersInternational audienceIn the past few years, internet has experienced a rapid growth in users and services. This led to an increase of different type of cyber-crimes. One of the most important is the Distributed Denial of Service (DDoS) attack, which someone can unleash through many different isolated hosts and make a system to shut down due to resources exhaustion. The importance of the problem can be easily identified due to the huge number of references found in literature trying to detect and prevent such attacks. In the current paper, a novel method based on a data mining technique is introduced in order to early warn the network administrator of a potential DDoS attack. The method uses the advanced All Repeated Patterns Detection (ARPaD) Algorithm, which allows the detection of all repeated patterns in a sequence. The proposed method can give very fast results regarding all IP prefixes in a sequence of hits and, therefore, warn the network administrator if a potential DDoS attack is under development. Based on several experiments conducted, it has been proven experimentally the importance of the method for the detection of a DDoS attack since it can detect a potential DDoS attack at the beginning and before it affects the system

Using Game-based Learning in Order to Enhance Decision Making Under Uncertainty

How do people make their decisions? Searching for the answer in the relevant literature, we can find that decisions are based either on rationality or intuition. Rational thinking is mainly observed in situations characterized by certainty (in terms of data or the consequences of decisions), while heuristic intuitive methods are mainly observed in situations of uncertainty. Training for the enhancement of decision making skills usually employs problem-based activities which mainly focus either only on rationality or only on intuition. However, problems in real life cannot always be solved with the contribution of only one way of thinking. In a decision making process often rationality works up to an extent and then intuition will lead to the final decision. For this reason, we designed and developed a game-based learning activity that enhances both rational and intuitive decision making skills. More specifically, we created a decision scenario in a virtual environment in which participants were provided with uncertainty-based information in their decision making process. As they tried to follow a rational decision making process, most of them realized that based on the given information they were confused and they had to decide intuitively at the end. This experiential learning activity was a tickler for the participants to decide under uncertainty and trust their intuition

COVID-19 pandemic spread against countries’ non-pharmaceutical interventions responses: a data-mining driven comparative study

Abstract Background The first half of 2020 has been marked as the era of COVID-19 pandemic which affected the world globally in almost every aspect of the daily life from societal to economical. To prevent the spread of COVID-19, countries have implemented diverse policies regarding Non-Pharmaceutical Intervention (NPI) measures. This is because in the first stage countries had limited knowledge about the virus and its contagiousness. Also, there was no effective medication or vaccines. This paper studies the effectiveness of the implemented policies and measures against the deaths attributed to the virus between January and May 2020. Methods Data from the European Centre for Disease Prevention and Control regarding the identified cases and deaths of COVID-19 from 48 countries have been used. Additionally, data concerning the NPI measures related policies implemented by the 48 countries and the capacity of their health care systems was collected manually from their national gazettes and official institutes. Data mining, time series analysis, pattern detection, machine learning, clustering methods and visual analytics techniques have been applied to analyze the collected data and discover possible relationships between the implemented NPIs and COVID-19 spread and mortality. Further, we recorded and analyzed the responses of the countries against COVID-19 pandemic, mainly in urban areas which are over-populated and accordingly COVID-19 has the potential to spread easier among humans. Results The data mining and clustering analysis of the collected data showed that the implementation of the NPI measures before the first death case seems to be very effective in controlling the spread of the disease. In other words, delaying the implementation of the NPI measures to after the first death case has practically little effect on limiting the spread of the disease. The success of implementing the NPI measures further depends on the way each government monitored their application. Countries with stricter policing of the measures seems to be more effective in controlling the transmission of the disease. Conclusions The conducted comparative data mining study provides insights regarding the correlation between the early implementation of the NPI measures and controlling COVID-19 contagiousness and mortality. We reported a number of useful observations that could be very helpful to the decision makers or epidemiologists regarding the rapid implementation and monitoring of the NPI measures in case of a future wave of COVID-19 or to deal with other unknown infectious pandemics. Regardless, after the first wave of COVID-19, most countries have decided to lift the restrictions and return to normal. This has resulted in a severe second wave in some countries, a situation which requires re-evaluating the whole process and inspiring lessons for the future

Mineralogy and Geochemistry of Gems

Gems have been used in the manufacture of jewellery and as ornaments since antiquity. Considering gems, recent statistics have shown that about 15 billion Euros are annually at stake. Nowadays, gemmology, i.e., the study of gem materials, is one of the most expanding fields in the earth sciences, positioned between academia and industry. As an applied science, in gemmology, the instruments used should be non- or microdestructive, and their cost should be reasonable both in terms of equipment and time consumption. Gemmology can also be used contribute to the development of pure science and in some cases, destructive techniques may have to be used. Taking into account the fact that gems are albeit rarely available for scientific research, this compilation of 20 articles by around 100 researchers from over 30 different institutions situated in 20 countries from around the globe, presented in the Special Issue entitled “Mineralogy and Geochemistry of Gems”, offers very good examples on the application of various methods for their study which will hopefully contribute to our better understanding of gem formation in general and will enhance scientific debates attracting more scientists from various disciplines to get involved in this field

Editorial for Special Issue “Mineralogy and Geochemistry of Gems”

Gems are materials used for adornment or decoration that must satisfy several criteria where they must be aesthetic and visually appealing; relatively rare; hard and tough enough to resist “normal” wear; and able to withstand corrosion by skin contact and cosmetics [...