Amanpreet Kaur

Prof. Amanpreet Kaur


Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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19 February 2023
Verified
Book Chapter
Closed access
PDF file
SSShagun Sharma
Shagun Sharma
KRK. R. Ramkumar
K. R. Ramkumar
AKAmanpreet Kaur
Amanpreet Kaur
Taniya HasijaTaniya Hasija
Taniya Hasija
SMSudesh Mittal
Sudesh Mittal
BSBhupendra Singh
Bhupendra Singh

19 February 2023
Verified
Book Chapter
Closed access
PDF file
Taniya HasijaTaniya Hasija
Taniya Hasija
AKAmanpreet Kaur
Amanpreet Kaur
KRK. R. Ramkumar
K. R. Ramkumar
SSShagun Sharma
Shagun Sharma
SMSudesh Mittal
Sudesh Mittal
BSBhupendra Singh
Bhupendra Singh


1 January 2025 in International Journal of Advanced Computer Science and Applications
Verified
Journal Article
Open access
PDF file
KKKawalpreet Kaur
Kawalpreet Kaur
AKAmanpreet Kaur
Amanpreet Kaur
Yonis GulzarYonis Gulzar
Yonis Gulzar
VGVidhyotma Gandhi
Vidhyotma Gandhi
MMMohammad Shuaib Mir
Mohammad Shuaib Mir
ASArjumand Bano Soomro
Arjumand Bano Soomro
Data security and privacy are critical concerns when integrating Closed-Circuit Television (CCTV) cameras with the Internet of Things (IoT). To enhance security, IoT data must be encrypted before transmission and storage. However, to minimize overheads related to storage space, computational time, and transmission energy, data can be compressed prior to encryption. H.264/AVC (Advanced Video Coding) offers a balanced solution for video compression by addressing processing demands, video quality, and compression efficiency. Encryption is vital for safeguarding data security, yet the integrity of IoT data may sometimes be compromised. Ineffective data selection can lead to inefficiencies and potential security risks, highlighting the importance of addressing CCTV video data security carefully. This study proposes an algorithm that integrates compression with selective encryption techniques to reduce computational overhead while ensuring access to critical information for real-time analysis. By employing frame intervals, the algorithm enhances efficiency without compromising security. The execution details and merits of the proposed approach are analyzed, demonstrating its effectiveness in safeguarding the privacy and integrity of IoT CCTV video data. Results reveal superior performance in terms of compression efficiency and encryption/decryption times, with an average encryption time of 0.00171 seconds for a 128-bit key, enabling fast processing suitable for real-time applications. The decryption time matches the encryption time, confirming the method’s viability for practical IoT CCTV implementations. Metrics such as correlation coefficient, bitrate overhead, and histogram analysis further validate the approach’s robustness against statistical attacks.

30 June 2023
Verified
Book Chapter
Closed access
PDF file
SSShishir Shrivastava
Shishir Shrivastava
ASAvinash Sharma
Avinash Sharma
AKAmanpreet Kaur
Amanpreet Kaur
RGRupesh Gupta
Rupesh Gupta

1 January 2023 in International Journal of Performability Engineering
Verified
Journal Article
Closed access
PDF file
AKAmanpreet Kaur
Amanpreet Kaur
MAMantri Archana
Mantri Archana