BSc thesis: Artificial intelligence for cyber security

The thesis underscores the effectiveness of artificial intelligence in combating phishing attacks and underscores the importance of continued research and innovation to safeguard users and their data in the digital realm. Beyond technical aspects, the paper provides a theoretical framework on cyber security, phishing attacks, and the role of artificial intelligence in modern cyber defense. It emphasizes the ongoing need for research and improvement in this area due to the evolving nature of cyber threats. This BSc theis work was done by Mr Ivan Novakovic under the menthorship of prof. Armin Alibasic.

Mr Novakovic defended his BSc thesis on AI in cybersecurity

ABSTRACT – This thesis addresses the critical issue of detecting phishing URLs, a prevalent cyber threat, using advanced artificial intelligence techniques. It examines three models—Logistic Regression, Random Forest, and LightGBM—through rigorous analysis and real data testing to assess their effectiveness in identifying malicious URLs. The results demonstrate that these models, when properly trained and calibrated, can achieve high accuracy in predicting the maliciousness of URLs.

BSc thesis: Time series and their application in meteorology

Mr Anel Gredic defended his BSc thesis titled “Time series and their application in meteorology” under mentorship of prof. Luka Filipovic. Thesis discusses the significance of time series analysis in meteorology. Time series, which are continuous records of meteorological data like temperature, precipitation, humidity, and wind speed, play a vital role in meteorological science. They are collected by specialized weather stations and satellites and are essential for meteorologists and climate researchers. Time series analysis involves using statistical methods and models to understand the variability of weather conditions over time. It helps identify seasonal patterns, trends, and extreme events, which in turn aids in weather forecasting and climate change monitoring. The application of time series analysis extends beyond meteorology, impacting various aspects of everyday life. This research has profound implications for society and various industries, improving safety, sustainability, and efficiency.

ABSTRACT – Time series are continuous sequences of meteorological data, such as temperature, precipitation, humidity, wind speed, etc., recorded over time at the same location. These data sets are often collected by specialized weather stations and satellites, and are an invaluable resource for meteorologists and climate researchers. Time series analysis is a fundamental component of meteorological science. Through the use of statistical methods, models and techniques, meteorologists can better understand the variability of weather conditions over time. This analysis enables the identification of seasonal patterns, trends and extreme events. It also helps develop models for weather forecasting and climate change monitoring. The application of time series extends to various aspects of our everyday life. Analysis of time series and their application in meteorology are crucial for understanding and predicting weather phenomena, climate change and protection against extreme weather events. This research has a profound and far-reaching impact on our society and various industries, contributing to the improvement of safety, sustainability and efficiency.

BSc Thesis: Computer vision and deep learning for analysis of identification documents

Mr Filip Radinovic defended his BSc thesis “A system for analyzing identification documents by leveraging Computer vision and Deep Learning” under co-mentorhsip of mr Stevan Cakic and prof. Tomo Popovic. The thesis focuses on the importance of identity in our digital world and how it impacts the security measures used by organizations. The main goal of the thesis is to use artificial intelligence to verify a person’s identity online. The researchers trained a model using various datasets and images, teaching it to spot even the smallest inconsistencies. The most significant discovery they made is that this model is very accurate, with a precision rate of around 90%. Additionally, the model is very efficient, taking only 3 to 4 seconds to process data, which is much faster than manual methods. Overall, the thesis highlights the potential of using AI for identity verification, making it both precise and time-saving.

The thesis focused on the use of computer vision and HPC/AI to develop tools for ID document analysis

ABSTRACT – Identity is one of the most sacred values and currencies in our digital era, affecting the working models of private and public institutions. This causes many strict security measures and protocols with a price of time, which is where this thesis’ goal arises. The approach of the thesis is leveraging artificial intelligence to accomplish identity verification over the web. The model was trained on a myriad of datasets and images, utilizing standard deep learning algorithms. By the end of training, it was able to detect the most subtle inconsistencies, making it quite precise. The biggest research finding is the potential that a model like this holds. Its precision varies around 90%, which is a good number by today’s standards and model’s testing conditions and hardware. The other aspect is time, in which the model excels. From the point when the model receives the data, the processing of it begins and it takes 3 to 4 seconds (on modest hardware). This implies superior efficiency than manual or alternative ways of accomplishing the same goal.

Presentation on HPC and EUROCC during Science and Innovations Days@UDG

NCC Montenegro representative Ms Sanja Nikolic gave a presentation for to the undergraduate students of Facullty for Information Systems and Technogies, within the scope of Science and Innovation Days@UDG. The presentation covered the following topics:

  • HPC/HPDA/AI technological aspects, commercial aplications and industry benfits,
  • MNE market reserach results on Cloud HPC awearness and utilisation,
  • EuroCC2 project, Euro HPC supercomputing opportunities and MNE NCC activities and results,
  • HPC/AI Succes Stories in the areas of smart solutions for poultry farms, precise weather forecast in challenging topography of Montenegro and short-term predictive pricing posibilities in energy markets.
Presentation to the students of the final BSc year at FIST

EuroCC powered Master program in Artifitial Intelligence and HPC related training courses were also presented, in the scope of their potential enrollment and competences development. Following the interactive discussion, students also demonstrated the interest in understanding access to supercomputing resources and performances, and challanges related to industry interraction and HPC/AI uptake by SMEs.

Students expressed their interest in AI master program and HPC technology

EuroHPC JU Information Day for AI on Supercomputers

Representatives of NCC Montenegro attended virtual event EuroHPC JU Information Day for AI on Supercomputers held on 26 September 2023. Further topics were thoroughly elaborated and interactively discussed:

  • how EuroHPC JU supercomputers can be used for AI applications,
  • EuroHPC supercomputers access opportunities,
  • current and upcoming AI related calls and activities,
  • the support possibilities of EuroCC national competence centers
  • examples of HPC/AI success stories from Croatia, Sweden, Denmark, Spain and North Macedonia.
NCC Montenegro attended the virtual event Information Day for AI on Supercomputers (EuroHPC JU)

Meeting with colleagues from FON UoB

Researchers from University of Donja Gorica (UDG) and NCC Montenegro visited partners from Faculty of organizational sciences University of Belgrade (FON UoB) during their summer school at Perast. Colleagues from FON presented their exhibition of AI generated images titled “Imagine Boka” and their activities about startups and marketing.

We presented the most interesting activities on UDG along with activities on NCC Montenegro and the EuroCC project. We spoke about possibilities of future collaboration on educational programs, training courses, digital transformation topics, AI and similar subjects.

AI4S3 – Application of computer vision and deep learning in agriculture and food production, medicine and energy

NCC Montenegro team members and the Faculty of Information Systems and Technologies (UDG), with the support of the Innovation Fund of Montenegro as part of the program to encourage the development of innovation culture and the organization of education in the areas of expertise in Montenegro, organizes a three-month training called “AI4S3 – Application of computer vision and deep learning in agriculture and food production, medicine and energy” which will be held in the period from the beginning of October to the end of December 2023.

AI4S3 – Computer vision applications in S3

The purpose of education is to provide young people with high-quality education in order to acquire the relevant knowledge and skills needed for a successful career, but also to, above all, interest participants in the field of artificial intelligence and to become participants in the digital transformation of Montenegro. The education program is divided into 5 modules: Python Programming, Introduction to Artificial Intelligence, Artificial Intelligence and Computer Vision, Python Libraries and Tools for Artificial Intelligence and Artificial Intelligence in S3 Areas, and final project work. In addition to the fact that participants will acquire enough knowledge and skills needed for further research in this very current field, they will have the opportunity to expand their network of acquaintances and meet young people with similar interests. The program and agenda (in Montenegrin) is available here.

Registration is open until Sep 28th ath the following link.

The organization of this 3-month training is supported by the Innovation fund of Montenegro