Privacy-preserving medical data indexing in post-quantum clouds
Mehru Salahuddin Tahsildarmehrutahsildar@gmail.comDepartment of PathologyKrishna Institute of Medical SciencesKrishna Vishwa Vidyapeeth (Deemed to be University)Karad, Maharashtra, 415539, IndiaView full profile → , Manisha Sagar Pawarmanisha.pawar@vit.eduDepartment of Engineering Science and HumanitiesVishwakarma Institute of TechnologyPune, Maharashtra, 411037, IndiaView full profile → , *Samir N. AjaniCorresponding authorsamir.ajani@gmail.comSchool of Computer Science and EngineeringRamdeobaba UniversityNagpur, Maharashtra, 440013, IndiaView full profile → , Ravula Arun Kumararunravula121@vardhaman.orgDepartment of Computer Science and EngineeringVardhaman College of EngineeringShamshabad, Hyderabad, Telangana, 501218, IndiaView full profile → , Vimal Bibhuvimal.bhibu@niu.edu.inSchool of Engineering & TechnologyNoida International UniversityGreater Noida, Uttar Pradesh, 201312, IndiaView full profile → , Subbulakshmi Packirisamysubbup@maher.ac.inDepartment of PharmacologyMeenakshi Ammal Dental College & HospitalMeenakshi Academy of Higher Education & ResearchChennai, Tamil Nadu, 600095, IndiaView full profile →
* Corresponding author · click or hover a name for details
- Received:
- 01 Mar 2026
- Published Online:
- 31 Oct 2026
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIOS-2503
- Pages:
- 3789–3798
Abstract
Cloud-based medical data indexing enhances clinical data retrieval, but raises concerns about the privacy of medical data and the patterns of their searches when subjected to new quantum attacks. The privacy-preserving indexing framework proposed in this work is a hybrid between post-quantum key derivation, cryptographic hashing, probabilistic security and encrypted keyword vectors. Medical documents are converted to vector format, and queried with trapdoors, which are random but contain specific keywords and access patterns. Lattice resistant primitives provide security against classical and quantum adversaries for construction of indexes, processing of queries and establishment of session keys. Experimental testing shows that 96.8% retrieval accuracy, 34.6% lower search latency and 29.4% communication overhead reduction are achieved compared to the conventional encrypted indexing. It provides privacy, allows for searches that are not connected to the other data, and enables quick retrieval of data, thus helping secure cloud-based healthcare applications without compromising patient privacy in the post-quantum era.
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References
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