Detecting and Analyzing Network Attacks: A Time-Series Analysis Using the Kitsune Dataset DOI Creative Commons

Dima Abu Khalil,

Yousef Abuzir

Journal of Emerging Computer Technologies, Год журнала: 2024, Номер 5(1), С. 9 - 23

Опубликована: Ноя. 2, 2024

Network security is a critical concern in today’s digital world, requiring efficient methods for the automatic detection and analysis of cyber attacks. This study uses Kitsune Attack Dataset to explore network traffic behavior IoT devices under various attack scenarios, including ARP MitM, SYN DoS, Mirai Botnet. Utilizing Python-based data tools, we preprocess analyze millions packets uncover patterns indicative malicious activities. The employs packet-level time-series visualize detect anomalies specific each type. Key findings include high packet volumes attacks such as SSDP Flood Botnet, with Botnet involving multiple IP addresses lasting over 2 hours. Notable attack-specific behaviors on port -1 targeted ports like 53195. DoS are characterized by their prolonged durations, suggesting significant disruption. Overall, highlights distinctive underscores importance understanding these characteristics enhance response mechanisms.

Язык: Английский

Positional Packet Capture for Anomaly Detection in Multitenant Virtual Networks DOI Creative Commons
Daniel Spiekermann

International Journal of Network Management, Год журнала: 2025, Номер 35(2)

Опубликована: Янв. 29, 2025

ABSTRACT Anomaly detection in multitenant virtual networks presents significant challenges due to the dynamic, ephemeral nature of virtualized environments and complex traffic patterns they generate. This paper a definition preferable positions within enhance anomaly efficacy. Leveraging combination overlay underlay capture positions, this examines strategic impact network positioning on accuracy, particularly utilizing software‐defined networking (SDN) function virtualization (NFV). Through controlled testing with realistic attack scenarios, including data exfiltration, denial service, malware infiltration, advantages constraints each position are demonstrated. The findings underscore necessity adaptable mechanisms address variability volume, encapsulation challenges, privacy concerns unique ecosystems. further introduces cost calculation model that evaluates by weighting key factors, enabling an optimized trade‐off between accuracy resource efficiency. derived classification positional value significantly improves real‐time both internal external threats networks.

Язык: Английский

Процитировано

0
Utilizing Artificial Intelligence to Enhance Sensory Feedback in Prosthetic Limbs DOI
Mohammed Thakır Mahmood, Hala Adnan. Fadel, Arshad Ali

и другие.

Lecture notes in networks and systems, Год журнала: 2025, Номер unknown, С. 227 - 241

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
An Enhanced LSTM Approach for Detecting IoT-Based DDoS Attacks Using Honeypot Data DOI Creative Commons
Arjun Kumar Bose Arnob,

M. F. Mridha,

Mejdl Safran

и другие.

International Journal of Computational Intelligence Systems, Год журнала: 2025, Номер 18(1)

Опубликована: Фев. 5, 2025

Язык: Английский

Процитировано

0
Detecting and Analyzing Network Attacks: A Time-Series Analysis Using the Kitsune Dataset DOI Creative Commons

Dima Abu Khalil,

Yousef Abuzir

Journal of Emerging Computer Technologies, Год журнала: 2024, Номер 5(1), С. 9 - 23

Опубликована: Ноя. 2, 2024

Network security is a critical concern in today’s digital world, requiring efficient methods for the automatic detection and analysis of cyber attacks. This study uses Kitsune Attack Dataset to explore network traffic behavior IoT devices under various attack scenarios, including ARP MitM, SYN DoS, Mirai Botnet. Utilizing Python-based data tools, we preprocess analyze millions packets uncover patterns indicative malicious activities. The employs packet-level time-series visualize detect anomalies specific each type. Key findings include high packet volumes attacks such as SSDP Flood Botnet, with Botnet involving multiple IP addresses lasting over 2 hours. Notable attack-specific behaviors on port -1 targeted ports like 53195. DoS are characterized by their prolonged durations, suggesting significant disruption. Overall, highlights distinctive underscores importance understanding these characteristics enhance response mechanisms.

Язык: Английский

Процитировано

0