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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Cyber Attack Detection in Scada in Smart Grid using Autoencoder and Incremental Learning |
| Authors Name: | Krishna Singh , Vishwajeet Singh , Gulshan Kumar , Tanam Gupta |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_184865
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| Published Paper Id: | IJNRD2212137 |
| Published In: | Volume 7 Issue 12, December-2022 |
| DOI: | |
| Abstract: | Since the onset of the 21 century, there has been a constant focus on integrating technology with the traditional power infrastructure, aiming at making the power infrastructure more efficient, resilient and intelligent. This resulted in the development of the Cyber-Physical Power System (CPPS). These systems used advanced technologies to eliminate major problems existing in the previous model and hence provided better observability of the whole system. They ultimately resulted in better efficiency compared to the traditional system. But this reliance on modern systems on digital technologies also makes it prone to cyber attacks: offensive maneuvers to breach the information infrastructure. As the system's reliance on computers and digital components grew, the system became progressively vulnerable to these attacks. In this paper, we aim to predict these attacks beforehand. One such attack is the DDOS attack. DDOS is a malicious attempt to disrupt the normal traffic of a targeted server, service, or network by overwhelming the target or its surrounding infrastructure with a flood of internet traffic. These attacks breach the security of the power system and cause detrimental damage to the system and also disturb the normal working of activities dependent on the system. |
| Keywords: | Autoencoder,Incremental learning,cyber attack in Scada |
| Cite Article: | "Cyber Attack Detection in Scada in Smart Grid using Autoencoder and Incremental Learning", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.7, Issue 12, page no.b352-b358, December-2022, Available :http://www.ijnrd.org/papers/IJNRD2212137.pdf |
| Downloads: | 000118759 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2212137 Registration ID: 184865 Published In: Volume 7 Issue 12, December-2022 DOI (Digital Object Identifier): Page No: b352-b358 Country: Lucknow, Uttar Pradesh, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2212137 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2212137 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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