ACTA TECHNICA NAPOCENSIS ELECTRONICS AND TELECOMMUNICATIONS

URI permanent pentru această colecțiehttps://oasis.utcluj.app/handle/123456789/447

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2023 - 20244

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Autor: search.filters.author.ZINCA Daniel

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Acum arăt 1 - 4 din 4
  • Articol
    SECURITY ISSUES IN INTERNET OF THINGS BOTNETS: A HIGH INTERACTION HONEYPOT APPROACH
    (Technical University of Cluj-Napoca, 2023-12-11) LAZAR Alexandru; BLAGA Tudor-Mihai; ZINCA Daniel; DOBROTA Virgil
    For a better awareness of the tactics employed by the malicious entities in Internet of Things, a system called Honeypot tricks the attackers into exploiting its “sweet” fake resources. While implementing nine types of devices only six of those were attacked. Despite this, the honeypot managed to capture attacks destined for three devices that were not implemented. Overall, several real-world attacks were captured and analyzed providing different indicators of compromise. No new threats were identified but the server only ran for a short period of time and with limited resources. This approach looks like a promising avenue for creating attacker profiles and collecting data on botnet behavior.
  • Articol
    SECURE ACCESS WITH TELTONIKA GPS TRACKING DEVICES FOR INTELLIGENT TRANSPORTATION SYSTEMS
    (Terebes Romulus, 2023-03-27) ANDREICA Gheorghe-Romeo; STANGU Ciprian; IVANCIU Iustin-Alexandru; ZINCA Daniel; DOBROTA Virgil
    GPS tracking devices are widely used in industries like logistics, transportation, and security. However, they are susceptible to cyber-attacks, including Man-in-the-Middle (MITM). This study focuses on Teltonika GPS tracking devices and examines the impact of MITM attacks on their operation. We propose implementing encryption protocols and other measures to enhance the security and resilience of Teltonika GPS tracking devices.
  • Articol
    DDoS ATTACK DETECTION USING SUPERVISED MACHINE LEARNING ALGORITHMS OVER THE CIDDOS2019 DATASET
    (Terebes Romulus, 2023-06-22) ZINCA Daniel; DOBROTA Virgil
    Distributed Denial-of-Service (DDoS) attacks are one of the most common types of cyber-attacks that can cause severe damage to networks and systems. Traditional methods to detect them rely on signature-based Intrusion Detection Systems (IDS), which are limited by the need of prior knowledge of specific patterns and by the usual ineffectiveness against zero-day attacks. However machine learning (ML) algorithms have the potential to support the detection of new and unknown attacks. This article compares the DDoS detection performance of three Machine Learning techniques: Gaussian Naïve Bayes, Logistic Regression and Random Forest, based on validation metrics such as precision, recall and F1 score. The system was trained using three datasets extracted from CICDDoS2019 database. The results proved the detection of attacks at Layer 4 (TCP SYN/ UDP flood), and at reflective Layer 7 (MSSQL, NetBIOS). The Random Forests and Logistic Regression methods achieved a precision between 93.7% and 99.4 % over these three datasets.
  • Articol
    INTEGRATION OF THE SURICATA INTRUSION DETECTION SYSTEM AND OF THE WAZUH SECURITY INFORMATION AND EVENT MANAGEMENT FOR REAL-TIME DENIAL-OF-SERVICE AND DATA TAMPERING DETECTION AND ALERTING
    (Terebes Romulus, 2024) Gheorghe-Romeo ANDREICA; IVANCIU Iustin-Alexandru; ZINCA Daniel; DOBROTA Virgil
    This paper addresses one of the cybersecurity challenges posed by the rapid growth of IoT and intelligent transport systems. It aims to develop a security monitoring and alerting system for GPS devices in these systems, integrating the Suricata Intrusion Detection System (IDS) mechanism and the Wazuh Security Information and Event Management (SIEM). The solution is focused on detecting, alerting and real-time monitoring for Denial-of-Service (DoS) and Data Tampering attacks, ensuring robust protection against emerging cyber threats in IoT GPS tracking systems