Bio-Inspired Private Information Retrieval System Over Cloud Service Using the Social Bees' Lifestyle With a 3D Visualisation

Author(s):  
Hadj Ahmed Bouarara ◽  
Reda Mohamed Hamou ◽  
Amine Abdelmalek

In the last decade, a new paradigm had seen the light named Cloud Computing, which allows the delocalization of data and applications on a dematerialized infrastructure accessible from Internet. Unfortunately, the cloud services are facing many drawbacks especially in terms of security and data confidentiality. However, in a world where digital information is everywhere, finding the desired information has become a crucial problem. For the purpose to preserve the user privacy life new approaches and ideas had been published. The content of this chapter is a new system of bio-inspired private information retrieval (BI-PIR) using the lifestyle of social bees, which allows both to find and hid, the sensitive desired information. It is based on a multi-filters cryptosystem used by the server for the encryption of stored document and the retrieval model using a combination of filters by 3 types of workers bees (Purveyor, guardian and cleaner), the queen bee represents the query, and the hive represents the class of relevant documents. We have tested this system on the benchmark MEDLINE dataset with panoply of validation tools (recall, precision, f-measure, entropy, silence, noise, and accuracy) and a comparative study had been realized with other systems existed in literature. Finally, a 3D visualization tool had been developed in order to make the results in graphical format understandable by humans. Our objectives is to improve the services quality of cloud computing.

Author(s):  
Hadj Ahmed Bouarara ◽  
Reda Mohamed Hamou ◽  
Amine Abdelmalek

In the last decade, a new paradigm had seen the light named Cloud Computing, which allows the delocalization of data and applications on a dematerialized infrastructure accessible from Internet. Unfortunately, the cloud services are facing many drawbacks especially in terms of security and data confidentiality. However, in a world where digital information is everywhere, finding the desired information has become a crucial problem. For the purpose to preserve the user privacy life new approaches and ideas had been published. The content of this chapter is a new system of bio-inspired private information retrieval (BI-PIR) using the lifestyle of social bees, which allows both to find and hid, the sensitive desired information. It is based on a multi-filters cryptosystem used by the server for the encryption of stored document and the retrieval model using a combination of filters by 3 types of workers bees (Purveyor, guardian and cleaner), the queen bee represents the query, and the hive represents the class of relevant documents. We have tested this system on the benchmark MEDLINE dataset with panoply of validation tools (recall, precision, f-measure, entropy, silence, noise, and accuracy) and a comparative study had been realized with other systems existed in literature. Finally, a 3D visualization tool had been developed in order to make the results in graphical format understandable by humans. Our objectives is to improve the services quality of cloud computing.


2016 ◽  
Vol 30 (25) ◽  
pp. 1650178
Author(s):  
Tian-Yin Wang ◽  
Xiao-Qiu Cai ◽  
Rui-Ling Zhang

We propose two symmetrically-private information retrieval protocols based on quantum key distribution, which provide a good degree of database and user privacy while being flexible, loss-resistant and easily generalized to a large database similar to the precedent works. Furthermore, one protocol is robust to a collective-dephasing noise, and the other is robust to a collective-rotation noise.


Entropy ◽  
2020 ◽  
Vol 23 (1) ◽  
pp. 54
Author(s):  
Wen Yu Kon ◽  
Charles Ci Wen Lim

Private information retrieval (PIR) is a database query protocol that provides user privacy in that the user can learn a particular entry of the database of his interest but his query would be hidden from the data centre. Symmetric private information retrieval (SPIR) takes PIR further by additionally offering database privacy, where the user cannot learn any additional entries of the database. Unconditionally secure SPIR solutions with multiple databases are known classically, but are unrealistic because they require long shared secret keys between the parties for secure communication and shared randomness in the protocol. Here, we propose using quantum key distribution (QKD) instead for a practical implementation, which can realise both the secure communication and shared randomness requirements. We prove that QKD maintains the security of the SPIR protocol and that it is also secure against any external eavesdropper. We also show how such a classical-quantum system could be implemented practically, using the example of a two-database SPIR protocol with keys generated by measurement device-independent QKD. Through key rate calculations, we show that such an implementation is feasible at the metropolitan level with current QKD technology.


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