Efficient Detection of Spam over Internet Telephony by Machine Learning Algorithms

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F22%3A10250888" target="_blank" >RIV/61989100:27740/22:10250888 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27240/22:10250888
Result on the web
<a href="https://ieeexplore.ieee.org/document/9996400?source=authoralert" target="_blank" >https://ieeexplore.ieee.org/document/9996400?source=authoralert</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ACCESS.2022.3231384" target="_blank" >10.1109/ACCESS.2022.3231384</a>

Result language
angličtina
Original language name
Efficient Detection of Spam over Internet Telephony by Machine Learning Algorithms
Original language description
Recent trends show a growing interest in VoIP services and indicate that guaranteeing security in VoIP services and preventing hacker communities from attacking telecommunication solutions is a challenging task. Spam over Internet Telephony (SPIT) is a type of attack which is a significant detriment to the user's experience. A number of techniques have been produced to detect SPIT calls. We reviewed these techniques and have proposed a new approach for quick, efficient and highly accurate detection of SPIT calls using neural networks and novel call parameters. The performance of this system was compared to other state-of-art machine learning algorithms on a real-world dataset, which has been published online and is publicly available. The results of the study demonstrated that new parameters may help improve the effectiveness and accuracy of applied machine learning algorithms. The study explored the entire process of designing a SPIT detection algorithm, including data collection and processing, defining suitable parameters, and final evaluation of machine learning models.
Czech name
—
Czech description
—

Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
20203 - Telecommunications

Project
<a href="/en/project/EF15_003%2F0000466" target="_blank" >EF15_003/0000466: Artificial Intelligence and Reasoning</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Similar results(10)