Zobrazeno 1 - 10
of 1 058
pro vyhledávání: '"NIDS"'
Autor:
Muchemwa, Marifa, Odimegwu, Clifford
Publikováno v:
Journal of Entrepreneurship in Emerging Economies, 2023, Vol. 16, Issue 5, pp. 1319-1337.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/JEEE-12-2022-0376
Publikováno v:
PeerJ Computer Science, Vol 10, p e2333 (2024)
Cyberattacks are increasingly becoming more complex, which makes intrusion detection extremely difficult. Several intrusion detection approaches have been developed in the literature and utilized to tackle computer security intrusions. Implementing m
Externí odkaz:
https://doaj.org/article/7e1a1376284843e48da26c5400615a3f
Publikováno v:
PeerJ, Vol 12, p e18048 (2024)
Background This study aimed to assess the impact of the COVID-19 pandemic on the disease burden of Taiwan’s notifiable infectious diseases (NIDs). We compared disease burdens between the pandemic and pre-pandemic year of 2020 (with non-pharmaceutic
Externí odkaz:
https://doaj.org/article/bff5c23710604097bd6844550fb7191c
Publikováno v:
Egyptian Informatics Journal, Vol 27, Iss , Pp 100501- (2024)
The expanding use of Unmanned Aerial Vehicle (UAVs)/drones has been noticeable in recent years. Drones have several uses in a wide range of industries, including the military, delivery, agricultural, and surveillance. This led to a visible increase i
Externí odkaz:
https://doaj.org/article/72433a81fa1648d5935e27389e70da34
Publikováno v:
Review of Behavioral Finance, 2022, Vol. 16, Issue 1, pp. 186-201.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/RBF-03-2022-0083
Autor:
Touati B. Adli, Salem-Bilal B. Amokrane, Boban Z. Pavlović, Mohammad Zouaoui M. Laidouni, Taki-eddine Ahmed A. Benyahia
Publikováno v:
Vojnotehnički Glasnik, Vol 71, Iss 4, Pp 941-969 (2023)
Introduction/purpose: Anomaly detection-based Network Intrusion Detection Systems (NIDSs) have emerged as a valuable tool, particularly in military fields, for protecting networks against cyberattacks, specifically focusing on Netflow data, to identi
Externí odkaz:
https://doaj.org/article/2f0d10a6fb52416f8a677871dc569fdf
Publikováno v:
In Journal of Network and Computer Applications March 2025 235
Publikováno v:
Tongxin xuebao, Vol 45, Pp 106-118 (2024)
To solve the problems that the network intrusion detection system in the Internet of things couldn’t identify new attacks and has limited flexibility, a network intrusion detection system based on honeyfarm was proposed, which could effectively ide
Externí odkaz:
https://doaj.org/article/0464fab0600d45deb27e95300b859587
Publikováno v:
IEEE Access, Vol 12, Pp 137618-137633 (2024)
Intrusion detection systems (IDS) stand as formidable guardians in network security, playing a pivotal role in identifying and mitigating potential threats. As our digital landscape evolves, the imperative for robust intrusion detection mechanisms gr
Externí odkaz:
https://doaj.org/article/5d18f669bb394a61990b72dc233c6eb3
Publikováno v:
IEEE Access, Vol 12, Pp 58851-58870 (2024)
This study introduces a deep learning approach for network intrusion detection (NIDS), which excels in both binary and multi-classification tasks. This approach combines the strengths of six distinct deep learning algorithms: DNN, CNN, RNN, LSTM, GRU
Externí odkaz:
https://doaj.org/article/35417d0f51564013bea4ebc337510b70