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<Article>
<Journal>
<PublisherName>OICC Press</PublisherName>
<JournalTitle>Majlesi Journal of Electrical Engineering</JournalTitle>
<Issn>2345-3796</Issn>
<Volume>19</Volume>
<Issue>2</Issue>
<PubDate PubStatus="epublish">
<Year>2025</Year>
<Month>06</Month>
<Day>01</Day>
</PubDate>
</Journal>
<ArticleTitle>Advances in network security and new anomaly detection techniques</ArticleTitle>
<VernacularTitle></VernacularTitle>
<FirstPage></FirstPage>
<LastPage></LastPage>
<ELocationID EIdType="doi">10.57647/j.mjee.2025.1902.26</ELocationID>
<Language>EN</Language>
<AuthorList>
<Author>
<FirstName>Sajad</FirstName>
<LastName>Balali Dehkordi</LastName>
<Affiliation>Department of Electrical Engineering, Na.C., Islamic Azad University, Najafabad, Iran</Affiliation>
<Identifier Source="ORCID">https://orcid.org/0009-0000-8812-956X</Identifier>
</Author>
<Author>
<FirstName>Saeed</FirstName>
<LastName>Nasri</LastName>
<Affiliation>Department of Electrical Engineering, Na.C., Islamic Azad University, Najafabad, Iran; Digital Processing and Machine Vision Research Center, Na.C., Islamic Azad University, Najafabad, Iran</Affiliation>
<Identifier Source="ORCID">https://orcid.org/0000-0002-2225-6707</Identifier>
</Author>
<Author>
<FirstName>Sina</FirstName>
<LastName>Dami</LastName>
<Affiliation>Department of Computer Engineering, WT.C., Islamic Azad University, Tehran, Iran</Affiliation>
<Identifier Source="ORCID">https://orcid.org/0000-0002-1309-5913</Identifier>
</Author>
</AuthorList>
<PublicationType>Journal Article</PublicationType>
<History>
<PubDate PubStatus="received">
<Year>2025</Year>
<Month>06</Month>
<Day>01</Day>
</PubDate>
</History>
<Abstract>Anomaly detection in diverse domains is confronted with the challenges posed by the increasing volume, velocity, and complexity of data. This paper presents a comprehensive review of recent advancements and research trends in anomaly detection across various domains, including high-dimensional big data, sensor systems, information and communication technology, IoT data, energy consumption, and real-time networks amidst cyber-attacks. Through a systematic analysis of recent literature, this review synthesizes key findings, methodologies, and challenges, providing insights into current strategies and future directions for anomaly detection technology. The reviewed papers highlight the importance of addressing domain-specific challenges, fostering interdisciplinary collaboration, and advancing methodological innovation to develop robust, scalable, and effective anomaly detection solutions capable of meeting the evolving demands of today's data-driven world.</Abstract>
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<Object Type="keyword">
<Param Name="value">Anomaly detection</Param>
</Object>
<Object Type="keyword">
<Param Name="value">Network Security</Param>
</Object>
<Object Type="keyword">
<Param Name="value">IoT</Param>
</Object>
<Object Type="keyword">
<Param Name="value">Energy consumption</Param>
</Object>
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</Article>
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