Vol. 23 No. 2/2019

Issue Topic: Cybersecurity

Collaborative Platforms for Crowdsourcing and Consensus-based Decisions in Multi-Participant Environments
Cristian CIUREA, Florin Gheorghe FILIP 5
The paper presents a new approach related to crowdsourcing and consensus in the multi-participant decision-making process. Multi-participant decision-making techniques, based on consensus building models frequently assume there are not really many decision makers in the group (appropriate operations can be done by complete enumeration). The consensus building and the crowdsourcing approach in the decision-making process are described. The most well-known top ten crowdsourcing platforms are analyzed and a comparison between them is made, in order to show existing and partially supported features.
Keywords: Consensus building, Collaborative decision-making, Evaluation criteria, Crowdsourcing platforms.

Web Crawler for Indexing Video e-Learning Resources: A YouTube Case Study
Bogdan IANCU 15
The main objective of the current paper is to develop and validate an algorithm focused on au-tomatically indexing YouTube e-learning resources about a certain domain of interest. After identifying the keywords specific to the desired domain, a web crawler is developed for evaluat-ing video resources (from the YouTube platform) in terms of relevance for that domain. Once the most relevant video resources are found, they are indexed with the usage of a NER engine applied on their transcripts. In this manner, semantic queries can be used further in order to find exactly the needed information inside these multimedia resources. The crawler will repeat the indexing process daily in order to maintain the repository of semantically indexed videos up to date. The final chapter presents the obtained results together with the validation of the model.
Keywords: Crawler, YouTube, NER, Semantic web, E-learning

Additional Limit Conditions for Breakout Trading Strategies
Cristian PĂUNA 25
One of the most popular trading methods used in financial markets is the Turtle strategy. Long time passed since the middle of 1983 when Richard Dennis and Bill Eckhardt disputed about whether great traders were born or made. To decide the matter, they recruited and trained some traders (the Turtles) and give them real accounts and a complete trading strategy to see which idea is right. That was a breakout trading strategy, meaning they bought when the price exceeded the maximum 20 or 50 days value, and sold when the price fell below the minimum of the same interval. Since then many changes have occurred in financial markets. Electronic trading was widespread released and financial trading has become accessible to everyone. Algorithmic trading became the significant part of the trading decision systems and high-frequency trading pushed the volatility of the financial markets to new and incredible limits nowadays. The orders are built and sent almost instantly by smart computers using advanced mathematical algorithms. With all these changes there are many questions today regarding the breakouts strategies. Are the Turtle rules still functional? How can the Turtle strategy be automated for algorithmic trading? Are the results comparable with other modern trading strategies? After a short display of the history and the system’s rules, this paper will find some answers to all these questions. We will reveal a method to automate a breakout strategy. More different trading strategies originating from the Turtle rules will be presented. A mathematical model to build the trading signals will be described in order to automate the trading process. It was found that all of these rules have a positive expectancy when they are combined with modern limit conditions. The paper will also include trading results obtained with the methods presented in order to compare and to analyze this capital investment methodology adapted especially for algorithmic trading.
Keywords: Financial markets, Breakout strategy, Turtle strategy, Trading signals, Algorithmic trading, High-frequency trading, Automated trading systems

Cyber Security Beyond the Industry 4.0 Era. A Short Review on a Few Technological Promises
Antonio CLIM 34
The global development industries progress towards meeting the ever evolving contemporary and future demands. This transformative evolution introduced phenomena such as Industry 4.0 and 5.0 which are facilitated by both information and operational technologies: collaborative robotics, IoT, AI. Their integration into a hyper-connected system facilitates the production of goods and services. In addition, these industries are characterized by automation, as well as by unmatched levels of data exchange throughout the value chain. Cyber security risks are crucial as the prevalence of these information and operation technologies has changed the appearance of cyber threats. Addressing the premises and realities of cyber security in Industries 4.0 and 5.0 is crucial. Risk mitigation strategies provided by various organizations are crucial for lowering risks. Given the loopholes and vulnerabilities generated by interconnections, cyber security is vital for the advancement of digital industrial transformation.
Keywords: Collaborative robots (cobots), IPv6 Low power Wireless Personal Area Networks (6LoWPAN), Sigma routing metric, Routing Protocol for LLN (RPL), ContikiOS, Cyber-physical production systems (CPPSs), Destination-Oriented Directed Acyclic Graph (DODAG)

A Comparative Assessment of Obfuscated Ransomware Detection Methods
Sergiu SECHEL 45
Ransomware represents a class of malicious applications that encrypts the files of infected system and demands from victims a payment in cryptocurrency in order to receive the decryption key. The mainstream adoption of cryptocurrencies increased the number of ransomware attack. The outbreaks had risen in complexity and received mass-media attention in 2017 when two destructive campaigns crippled companies and institutions around the world. These outbreaks continue at an accelerated pace even though efforts are made to improve the detection and mitigation of ransomware. The purpose of this research is to assess the efficiency of current malware analysis methods and technologies in the detection of ransomware. The experiments presented here were performed using antivirus engines and dynamic malware analysis against live obfuscated ransomware samples.
Keywords: Malware, Ransomware, Detection Techniques, Malware Analysis, Malware Classification, Mutation, Cybersecurity

Smartphones and IoT Security
Mobile devices (smartphones or IoT devices) threats are all over and come in many ways. Nowadays the number of mobile devices is extremely high and we use them to cover many personal needs like ordering food, buying plane tickets, controlling our home from distance (using IoT devices) and so on. But all of this comes with a cost and that cost is that we have to give personal data to some devices which lead to threats. This paper contains a classification for the threats and vulnerabilities for smartphones and tablets and a short one for IoT devices. Here are described some attack scenarios for IoT and a few representative attacks. As method of research was used a qualitative one by documenting from articles related to this theme, reports realized by companies which operates in this field and other resources.
Keywords: Mobile devices, IoT, Aattacks, Malware, Ransomware

Software Effort Estimation Using Multilayer Perceptron and Long Short Term Memory
Eduard-Florin PREDESCU, Alexandru ȘTEFAN, Alexis-Valentin ZAHARIA 76
Software effort estimation is a hot topic for study in the last decades. The biggest challenge for project managers is to meet their goals within the given time limit. Machine learning software can take project management software to a whole new level. The objective of this paper is to show the applicability of using neural network algorithms in software effort estimation for pro-ject management. To prove the concept we are using two machine learning algorithms: Multi-layer Perceptron (MLP) and Long Short-Term Memory (LSTM). To train and test these ma-chine learning algorithms we are using the Desharnais dataset. The dataset consists of 77 sam-ple projects. From our results we have seen that Multilayer Perceptron algorithm has better performance than Long Short-Term Memory, by having a better determination coefficient for software effort estimation. Our success in implementing a machine learning that can estimate the software effort brings real benefits in the field of project management assisted by computer, further enhancing the ability of a manager to organize the tasks within the time limit of the pro-ject. Although, we need to take into consideration that we had a limited dataset that we could use so a real advancement would be to implement and test these algorithms using a real life company as a subject of testing.
Keywords: Software effort estimation, Multilayer perceptron, Long short-term memory, Neural network algorithms, Machine learning, Desharnais dataset

Implementation of Mobile Solutions in Romania`s Education System
Rareș-Constantin CIOBANU 88
In the light of the technology development nowadays, the society and more specific, the education area is facing new challenges in meeting the learners’ demands. The continuously changing expectations and the ubiquity of the mobile devices in everyday life has led to the apparition of a new modern learning method, the m-learning, whose theoretical approaches will be further analysed, followed by an examination of the advantages and disadvantages for the mobile learners. This paper also investigates the implementation status of mobile solutions on the Romania`s education systems.
Keywords: Mobile applications, Education system, E-learning, M-learning

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