Relevant bibliographies by topics / Partially homomorphic systems

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Partially homomorphic systems'

Author: Grafiati
Published: 28 May 2022
Last updated: 30 July 2025

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Journal articles on the topic "Partially homomorphic systems"

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Karimov, Abdukodir Abdisalomovich, and Iskandar Salimboyevich Olimov. "ANALYSIS OF HOMOMORPHIC ENCRYPTION METHODS IN CLOUD COMPUTING SYSTEMS." Innovative Development in Educational Activities 2, no. 11 (2023): 377–81. https://doi.org/10.5281/zenodo.8045525.

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This article discusses gamma encryption in detail. In addition, a comparative analysis of commonly used types of gamma encryption, i.e. partially homomorphic and fully homomorphic encryption, is presented. RSA, El-Gamal, Paillier, Goldwasser-Micali, Boneh-Goh-Nissim and Gentry Homomorphic encryption systems were analysed and the results presented.
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Prasad, S. V. Suriya, and K. Kumanan. "Homomorphic Encryption Using Enhanced BGV Encryption Scheme For Cloud Security." International Journal Of Engineering And Computer Science 7, no. 03 (2018): 23785–89. http://dx.doi.org/10.18535/ijecs/v7i3.22.

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Fully Homomorphic Encryption is used to enhance the security incase of un-trusted systems or applications that deals with sensitive data. Homomorphic encryption enables computation on encrypted data without decryption. Homomorphic encryption prevents sharing of data within the cloud service where data is stored in a public cloud . In Partially Homomorphic Encryption it performs either additive or multiplicative operation, but not both operation can be carried out at a same time. Whereas , in case of Fully Homomorphic Encryption both operations can be carried out at same time. In this model , E
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Kölsch, Johannes, Christopher Heinz, Axel Ratzke, and Christoph Grimm. "Simulation-Based Performance Validation of Homomorphic Encryption Algorithms in the Internet of Things." Future Internet 11, no. 10 (2019): 218. http://dx.doi.org/10.3390/fi11100218.

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IoT systems consist of Hardware/Software systems (e.g., sensors) that are embedded in a physical world, networked and that interact with complex software platforms. The validation of such systems is a challenge and currently mostly done by prototypes. This paper presents the virtual environment for simulation, emulation and validation of an IoT platform and its semantic model in real life scenarios. It is based on a decentralized, bottom up approach that offers interoperability of IoT devices and the value-added services they want to use across different domains. The framework is demonstrated
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Sadeghikhorami, Ladan, and Ali Akbar Safavi. "Secure distributed Kalman filter using partially homomorphic encryption." Journal of the Franklin Institute 358, no. 5 (2021): 2801–25. http://dx.doi.org/10.1016/j.jfranklin.2020.08.048.

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Nidhyananthan, S. Selva, Prasad M., and Shantha Selva Kumari R. "Secure Speaker Recognition using BGN Cryptosystem with Prime Order Bilinear Group." International Journal of Information Security and Privacy 9, no. 4 (2015): 1–19. http://dx.doi.org/10.4018/ijisp.2015100101.

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Speech being a unique characteristic of an individual is widely used in speaker verification and speaker identification tasks in applications such as authentication and surveillance respectively. In this paper, framework for secure speaker recognition system using BGN Cryptosystem, where the system is able to perform the necessary operations without being able to observe the speech input provided by the user during speaker recognition process. Secure speaker recognition makes use of Secure Multiparty Computation (SMC) based on the homomorphic properties of cryptosystem. Among the cryptosytem w
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Medileh, Saci, Abdelkader Laouid, Mohammad Hammoudeh, et al. "A Multi-Key with Partially Homomorphic Encryption Scheme for Low-End Devices Ensuring Data Integrity." Information 14, no. 5 (2023): 263. http://dx.doi.org/10.3390/info14050263.

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In today’s hyperconnected world, the Internet of Things and Cloud Computing complement each other in several areas. Cloud Computing provides IoT systems with an efficient and flexible environment that supports application requirements such as real-time control/monitoring, scalability, fault tolerance, and numerous security services. Hardware and software limitations of IoT devices can be mitigated using the massive on-demand cloud resources. However, IoT cloud-based solutions pose some security and privacy concerns, specifically when an untrusted cloud is used. This calls for strong encryption
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Catak, Ferhat Ozgur, Ismail Aydin, Ogerta Elezaj, and Sule Yildirim-Yayilgan. "Practical Implementation of Privacy Preserving Clustering Methods Using a Partially Homomorphic Encryption Algorithm." Electronics 9, no. 2 (2020): 229. http://dx.doi.org/10.3390/electronics9020229.

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The protection and processing of sensitive data in big data systems are common problems as the increase in data size increases the need for high processing power. Protection of the sensitive data on a system that contains multiple connections with different privacy policies, also brings the need to use proper cryptographic key exchange methods for each party, as extra work. Homomorphic encryption methods can perform similar arithmetic operations on encrypted data in the same way as a plain format of the data. Thus, these methods provide data privacy, as data are processed in the encrypted doma
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Yu, Haining, Hongli Zhang, and Xiangzhan Yu. "Hail the Closest Driver on Roads: Privacy-Preserving Ride Matching in Online Ride Hailing Services." Security and Communication Networks 2020 (June 12, 2020): 1–13. http://dx.doi.org/10.1155/2020/4948387.

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Online ride hailing (ORH) services enable a rider to request a driver to take him wherever he wants through a smartphone app on short notice. To use ORH services, users have to submit their ride information to the ORH service provider to make ride matching, such as pick-up/drop-off location. However, the submission of ride information may lead to the leakages of users’ privacy. In this paper, we focus on the issue of protecting the location information of both riders and drivers during ride matching and propose a privacy-preserving online ride matching scheme, called pRMatch. It enables an ORH
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Alsumayt, Albandari, Nahla El-Haggar, Lobna Amouri, Zeyad M. Alfawaer, and Sumayh S. Aljameel. "Smart Flood Detection with AI and Blockchain Integration in Saudi Arabia Using Drones." Sensors 23, no. 11 (2023): 5148. http://dx.doi.org/10.3390/s23115148.

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Global warming and climate change are responsible for many disasters. Floods pose a serious risk and require immediate management and strategies for optimal response times. Technology can respond in place of humans in emergencies by providing information. As one of these emerging artificial intelligence (AI) technologies, drones are controlled in their amended systems by unmanned aerial vehicles (UAVs). In this study, we propose a secure method of flood detection in Saudi Arabia using a Flood Detection Secure System (FDSS) based on deep active learning (DeepAL) based classification model in fe
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Wu, Yuncheng, Naili Xing, Gang Chen, et al. "Falcon: A Privacy-Preserving and Interpretable Vertical Federated Learning System." Proceedings of the VLDB Endowment 16, no. 10 (2023): 2471–84. http://dx.doi.org/10.14778/3603581.3603588.

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Federated learning (FL) enables multiple data owners to collaboratively train machine learning (ML) models without disclosing their raw data. In the vertical federated learning (VFL) setting, the collaborating parties have data from the same set of users but with disjoint attributes. After constructing the VFL models, the parties deploy the models in production systems to infer prediction requests. In practice, the prediction output itself may not be convincing for party users to make the decisions, especially in high-stakes applications. Model interpretability is therefore essential to provid
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Dissertations / Theses on the topic "Partially homomorphic systems"

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Шишлєвський, Д. О. "Системи гомоморфного шифрування". Master's thesis, Сумський державний університет, 2019. http://essuir.sumdu.edu.ua/handle/123456789/75672.

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У даній роботі були досліджені переваги та недоліки частково гомоморфних алгоритмів. Була створена програма для шифрування та розшифрування тексту та для аналізу роботи обраних алгоритмів за системою оцінок від 1 до 5.
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Book chapters on the topic "Partially homomorphic systems"

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Raval, Aashka, Jaivik Jariwala, Vrundan Sojitra, and Nishant Doshi. "A Review: Implementation of Partially Homomorphic Encryption and Fully Homomorphic Encryption on Cloud Computing." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-97-8602-2_14.

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Boomija, M. D., and S. V. Kasmir Raja. "Secure Predictive Analysis on Heart Diseases Using Partially Homomorphic Machine Learning Model." In Algorithms for Intelligent Systems. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0332-8_42.

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Agrawal, Aniket, Kamalakanta Sethi, and Padmalochan Bera. "Blockchain-Based Cardinal E-Voting System Using Biometrics, Watermarked QR Code and Partial Homomorphic Encryption." In Proceedings of the International Conference on Cybersecurity, Situational Awareness and Social Media. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-6414-5_23.

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Vamsi, Desam, and Pradeep Reddy. "Electronic Health Record Security in Cloud." In Advances in Healthcare Information Systems and Administration. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-0261-7.ch002.

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Security is the primary issue nowadays because cybercrimes are increasing. The organizations can store and maintain their data on their own, but it is not cost effective, so for convenience they are choosing cloud. Due to its popularity, the healthcare organizations are storing their sensitive data to cloud-based storage systems, that is, electronic health records (EHR). One of the most feasible methods for maintaining privacy is homomorphism encryption (HE). HE can combine different services without losing security or displaying sensitive data. HE is nothing but computations performed on encr
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Vamsi, Desam, and Pradeep Reddy. "Electronic Health Record Security in Cloud." In Research Anthology on Securing Medical Systems and Records. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-6311-6.ch041.

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Security is the primary issue nowadays because cybercrimes are increasing. The organizations can store and maintain their data on their own, but it is not cost effective, so for convenience they are choosing cloud. Due to its popularity, the healthcare organizations are storing their sensitive data to cloud-based storage systems, that is, electronic health records (EHR). One of the most feasible methods for maintaining privacy is homomorphism encryption (HE). HE can combine different services without losing security or displaying sensitive data. HE is nothing but computations performed on encr
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Nidhyananthan, S. Selva, M. Prasad, and R. Shantha Selva Kumari. "Secure Speaker Recognition using BGN Cryptosystem with Prime Order Bilinear Group." In Cryptography. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1763-5.ch016.

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Speech being a unique characteristic of an individual is widely used in speaker verification and speaker identification tasks in applications such as authentication and surveillance respectively. In this paper, framework for secure speaker recognition system using BGN Cryptosystem, where the system is able to perform the necessary operations without being able to observe the speech input provided by the user during speaker recognition process. Secure speaker recognition makes use of Secure Multiparty Computation (SMC) based on the homomorphic properties of cryptosystem. Among the cryptosytem w
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Conference papers on the topic "Partially homomorphic systems"

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Galymzhankyzy, Zeynep, Ildar Rinatov, Aliya Abdiraman, and Shynbolat Unaybaev. "Assessing Electoral Integrity: Paillier’s Partial Homomorphic Encryption in E-Voting System." In 2024 IEEE 4th International Conference on Smart Information Systems and Technologies (SIST). IEEE, 2024. http://dx.doi.org/10.1109/sist61555.2024.10629522.

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Shafagh, Hossein, Anwar Hithnawi, Lukas Burkhalter, Pascal Fischli, and Simon Duquennoy. "Secure Sharing of Partially Homomorphic Encrypted IoT Data." In SenSys '17: The 15th ACM Conference on Embedded Network Sensor Systems. ACM, 2017. http://dx.doi.org/10.1145/3131672.3131697.

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Zhang, Zhenyong, Junfeng Wu, David Yau, Peng Cheng, and Jiming Chen. "Secure Kalman Filter State Estimation by Partially Homomorphic Encryption." In 2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS). IEEE, 2018. http://dx.doi.org/10.1109/iccps.2018.00046.

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Jiang, Tingcong, Chuanneng Sun, Salim El Rouayheb, and Dario Pompili. "FaceGroup: Continual Face Authentication via Partially Homomorphic Encryption & Group Testing." In 2023 IEEE 20th International Conference on Mobile Ad Hoc and Smart Systems (MASS). IEEE, 2023. http://dx.doi.org/10.1109/mass58611.2023.00062.

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Kawase, Hiroaki, Kaoru Teranishi, and Kiminao Kogiso. "Dynamic Quantizer Synthesis for Encrypted State-Feedback Control Systems with Partially Homomorphic Encryption." In 2022 American Control Conference (ACC). IEEE, 2022. http://dx.doi.org/10.23919/acc53348.2022.9867367.

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Kogiso, Kiminao, and Masaki Miyamoto. "Development and Examination of Secure Quadcopter Control System with Partially Homomorphic Encryption*." In 2023 IEEE/SICE International Symposium on System Integration (SII). IEEE, 2023. http://dx.doi.org/10.1109/sii55687.2023.10039142.

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S, Kavitha, B. S. Pavithra, A. B. Shashikala, B. N. Jagadeesh, P. Uma Mageswari, and Dileep Marichi. "Preserve the Medical Data using Secure Partially Homomorphic Encryption with Blockchain Technology in Smart Healthcare." In 2024 Second International Conference on Data Science and Information System (ICDSIS). IEEE, 2024. http://dx.doi.org/10.1109/icdsis61070.2024.10594531.

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Yu, Albert, Arun V. Sathanur, and Vikram Jandhyala. "A partial homomorphic encryption scheme for secure design automation on public clouds." In 2012 IEEE 21st Conference on Electrical Performance of Electronic Packaging and Systems (EPEPS). IEEE, 2012. http://dx.doi.org/10.1109/epeps.2012.6457871.

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Yaji, Sharath, Kajal Bangera, and B. Neelima. "Privacy Preserving in Blockchain Based on Partial Homomorphic Encryption System for Ai Applications." In 2018 IEEE 25th International Conference on High Performance Computing Workshops (HiPCW). IEEE, 2018. http://dx.doi.org/10.1109/hipcw.2018.8634280.

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Agrawal, Aniket, Kamalakanta Sethi, and Padmalochan Bera. "IoT-Based Aggregate Smart Grid Energy Data Extraction using Image Recognition and Partial Homomorphic Encryption." In 2021 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS). IEEE, 2021. http://dx.doi.org/10.1109/ants52808.2021.9936902.

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