Vol. 25 No. 1/2021

Advanced Telecom Systems to Facilitate Collaborative Decision-making in Distributed Settings
Maria VISAN, Firicel MONE, Florin Gheorghe FILIP 5
The paper presents several practical issues concerning the multi-participant decision-making processes with emphasis on the crowdsourcing approach. The development of effective modern telecom systems that enable effective operations of multi-participant decision units are detailed. System scalability and operator’s agility to incorporate continuous changing technologies chal-lenge further research.
Keywords: Business Intelligence, Collaborative activities, Communication Infrastructure, Data Science, Decision Support System, crowdsourcing

Conceptual Algorithmic of the Managerial Information Subsystems
Tudor LEAHU, Sergiu ȘIȘIANU, Alexandr GRECU 18
The informative role sub-systems of the integrated unitary economic management process are highlighted. Depending on the precedence and subsequence to material activities, their systematization is carried out. At the conceptual level, according to the logic of the solution succession, imposed by the managerial functions realization, within each sub-system are profiled the complexes of issues, and in each complex – the issues totalities. According to such an approach, the place, role and functional value are elucidated, determined the composition and content of the algorithmic interface of these managerial units (sub-system – issues complex – issue). Material incorporates the composition of groups of general character algorithms of the information sub-systems, precedent the economic activities of human materials (manufacturing, distribution (commercialization), consumption) – those of rate-setting, settlement, current foreseeing, as well as operative foreseeing and conducting of these activities. Starting from the predestination of economic management functions, the overall functional content of the fundamental algorithms of the nominated sub -systems is revealed.
Keywords: Conceptual algorithmic, Economic integrated managerial system, Information sub-systems, Material activities, Composition

Technical and Economical Evaluation of IoT Attacks and Their Corresponding Vulnerabilities
Stefan NICULA, Răzvan-Daniel ZOTA 31
An increase in popularity and adoption of IoT products encountered a direct proportionate interest in attacks and exploits on such solutions, having a measurable economic impact on the business industry and the IoT customers. The research analysis conducted on various IoT devices revealed security issues with patterns that are strongly related to high-risk vulnerabilities used in common exploit chains and malware campaigns. This includes vulnerabilities such as weak or default credentials, usage of outdated and vulnerable software, sensitive data exposure and missing security best practices and standards. This paper tackles multiple vectors of attack that are threatening the privacy and security integrity level of IoT devices in order to discover potential entry points and post-exploitation techniques that are often used on IoT attacks. The research perspective covers the malware incident aspect, vulnerabilities that are affecting different components and the overall security level provided by the products, with a focus on the economic impact delivered by such outcomes. Malware outbreaks are studied along with the impact of publicly known vulnerabilities, the attack surface of an IoT device and the mitigation enforced by some vendors. The security evaluation methodology was based on Penetration Testing practices, targeting all the components exposed by the IoT devices that were studied. This included the network capabilities, web and mobile applications and targeted the physical attack vectors as well. The recent IoT attacks were studied in order to draw conclusions and create potential recommendations and improvements to the IoT landscape.
Keywords: IoT, security, vulnerabilities, malware, economic impact

A Study on How the Pandemic Changed the Cybersecurity Landscape
Tiberiu-Marian GEORGESCU 42
This article studies the main changes inflicted by COVID-19 on the cybersecurity field. First, we analyze the main changes in how people used technology during the pandemic compared to before. The changes are classified into two categories: those that take place in the personal life and those specific to the professional environment. Then, the article studies to what extent each of the two categories impacted the cybersecurity domain. The main types of attacks that raised in popularity during the pandemic are discussed, together with causes, consequences, and miti-gation strategies. Our work shows that the most important changes in terms of incidents have been related to ransomware, phishing, and remote desktop protocol (RDP) attacks. We studied how COVID-19 restrictions generated the increase in phishing and RDP attacks. Then, to prove that ransomware was also influenced by the pandemic, we had to validate our hypothesis that the increase in both RDP and phishing attacks were the main causes of the intensification of ransomware attacks. We obtained strong correlation indicators which validated our hypoth-esis. The measures taken by companies are further discussed, whether they are cybersecurity-related companies or specialized in other areas. The paper also studies the evolution of cyber-security companies' stocks before and after the start of the pandemic. A correlation matrix based on the stock price evolution was performed, which indicates the influence of the pandem-ic on cybersecurity.
Keywords: Cybersecurity, COVID-19 impact, Remote work, Ransomware, Cybersecurity stocks

Using Artificial Intelligence for Quantifying Strategic Business-IT Alignment
Bassel DIAB 61
This paper aims to test an artificial model and a calculator the author developed based on deep learning, Neural Networks, and machine learning, Random Forest. The “Diab BITA Model” and the “Diab Calculator” are generated to enable organizations, of any size and in any industry, of calculating the value of Strategic Business-IT Alignment (BITA) following a scale of 7 degrees. Principally, the same sample of one of his previous papers is addressed in which top managers subjectively assessed the BITA maturity; the current paper targets to empirically prove the accuracy of managers’ perceptions using both the model and the calculator. Findings show an 89% accuracy rate in estimating those organizations’ BITA levels using the model and 92% using the calculator.
Keywords: Deep learning, Machine learning, Diab BITA Model, Diab Calculator

Credit Card Fraud Detection using Deep Learning Techniques
Oona VOICAN 70
The objective of this paper is to identify credit card fraud and this topic can be solved with the help of advanced machine learning and deep learning techniques. Due to the fact that credit card fraud is a serious worldwide problem, we have chosen to create a model for detecting im-poster scams by using deep neural networks. The purpose is to understand, determine and learn the normal behavior of the user and more precisely the detection of identity fraud. Each person has a trading pattern, uses certain operating systems, has a specific time to complete the transaction and spends large amounts of money usually within a certain time range. Transac-tions made by a certain user have a certain pattern, which can be identified with the help of neural networks. Machine learning involves teaching computers to recognize patterns in data in the same way as our brains do. Deep learning is just a subfield of machine learning that deals with algorithms inspired by the structure and function of the brain. Deep learning at the core is the ability to form higher and higher level of abstractions of representations in data and raw patterns. The data used to train the model is real, and it will be processed using the one-hot encoding method, so that categorical data/variables can be used by the machine learning algorithm.
Keywords: Artificial intelligence, Credit card fraud, Deep Learning, Neural network model, User behavior.

Digital Transformation During Lockdown
Ioan DRAGAN 86
This paper presents some preliminary findings of the digital transformation methodology inno-vation research done as part of the PhD studies. The COVID-19 pandemic changed the way we work and a large majority of the companies found themselves not prepared to move to a full remote or hybrid workforce model. Traditional software platforms and components are not de-signed for remote use, nor offer the right information protection and governance features. This paper presents a study of how business executives see the future workplace and a methodology for short term mitigation and long-term planning in the context of hybrid workplace.
Keywords: digital transformation, collaboration, cloud, end user, education, COVID-19, workplace

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