Efficient hardware-based private information retrieval using partial reshuffle

The paper proposes a novel hardware-based private information retrieval （HWPIR） protocol. By partially reshuffling previously accessed items in each round, instead of frequently reshuffling the whole database, the scheme makes better use of shuffled data copies and achieves the computation overhead at O（/N/K）,where N and k are the sizes of the database and secure storage respectively. For securestorage with moderate size, e.g. k = O（/N）, the overhead is 0（4/N）. The result is much better than the state-of-art schemes （as compared to e.g. O（log2N））. Without increasing response time and communication cost, the proposed protocol is truly practicable regardless of the database size. The security and preformance of the protocol is formally analyzed.

Private membership test protocol with low communication complexity

We introduce a practical method to perform private membership tests.In this method,clients are able to test whether an item is in a set controlled by the server without revealing their query item to the server.After executing the queries,the content of the server's set remains secret.One use case for a private membership test is to check whether a file contains any malware by checking its signature against a database of malware samples in a privacy-preserving way.We apply the Bloom filter and the Cuckoo filter in the membership test procedure.In order to achieve privacy properties,we present a novel protocol based on some homomorphic encryption schemes.In our protocol,we rearrange the data in the set into N-dimensional hypercubes.We have implemented our method in a realistic scenario where a client of an anti-malware company wants to privately check whether a hash value of a given file is in the malware database of the company.The evaluation shows that our method is feasible for real-world applications.We also have tested the performance of our protocol for databases of different sizes and data structures with different dimensions:2-dimensional,3-dimensional,and 4-dimensional hypercubes.We present formulas to estimate the cost of computation and communication in our protocol.

Asymmetric Consortium Blockchain and Homomorphically Polynomial-Based PIR for Secured Smart Parking Systems

In crowded cities,searching for the availability of parking lots is a herculean task as it results in the wastage of drivers’time,increases air pollution,and traffic congestion.Smart parking systems facilitate the drivers to determine the information about the parking lot in real time and book them depending on the requirement.But the existing smart parking systems necessitate the drivers to reveal their sensitive information that includes their mobile number,personal identity,and desired destination.This disclosure of sensitive information makes the existing centralized smart parking systems more vulnerable to service providers’security breaches,single points of failure,and bottlenecks.In this paper,an Improved Asymmetric Consortium Blockchain and Homomorphically Computing Univariate Polynomial-based private information retrieval(IACB-HCUPPIR)scheme is proposed to ensure parking lots’availability with transparency security in a privacy-preserving smart parking system.In specific,an improved Asymmetric Consortium Blockchain is used for achieving secure transactions between different parties interacting in the smart parking environment.It further adopted the method of Homomorphically Computing Univariate Polynomial-based private information retrieval(HCUPPIR)scheme for preserving the location privacy of drivers.The results of IACB-HCUPPIR confirmed better results in terms of minimized computation and communication overload with throughput,latency,and response time with maximized drivers’privacy preservation.Moreover,the proposed fully homomorphic algorithm(FHE)was compared against partial-homomorphic encryption(PHE)and technique without encryption and found that the proposed model has quick communication in allocating the parking slots starting with 24.3 s,whereas PHE starts allocating from 24.7 s and the technique without encryption starts at 27.4 s.Thus,we ensure the proposed model performs well in allocating parking slots with less time and high security with privacy preservation.

PIR-based data integrity verification method in sensor network

Since a sensor node handles wireless communication in data transmission and reception and is installed in poor environment, it is easily exposed to certain attacks such as data transformation and sniffing. Therefore, it is necessary to verify data integrity to properly respond to an adversary's ill-intentioned data modification. In sensor network environment, the data integrity verification method verifies the final data only, requesting multiple communications. An energy-efficient private information retrieval(PIR)-based data integrity verification method is proposed. Because the proposed method verifies the integrity of data between parent and child nodes, it is more efficient than the existing method which verifies data integrity after receiving data from the entire network or in a cluster. Since the number of messages for verification is reduced, in addition, energy could be used more efficiently. Lastly, the excellence of the proposed method is verified through performance evaluation.

Human-Centered A.I. and Security Primitives

The paper reviews how human-centered artificial intelligence and securityprimitive have influenced life in the modern world and how it’s useful inthe future. Human-centered A.I. has enhanced our capabilities by the wayof intelligence, human informed technology. It has created a technologythat has made machines and computer intelligently carry their function.The security primitive has enhanced the safety of the data and increasedaccessibility of data from anywhere regardless of the password is known.This has improved personalized customer activities and filled the gapbetween the human-machine. This has been successful due to the usageof heuristics which solve belowems by experimental, support vector machinewhich evaluates and group the data, natural language processingsystems which change speech to language. The results of this will lead toimage recognition, games, speech recognition, translation, and answeringquestions. In conclusion, human-centered A.I. and security primitivesis an advanced mode of technology that uses statistical mathematicalmodels that provides tools to perform certain work. The results keep onadvancing and spreading with years and it will be common in our lives.

Decoy-state method for quantum-key-distribution-based quantum private query

The quantum private query(QPQ)is a quantum solution for the symmetrically private information retrieval problem.We study the security of quantum-key-distribution-based QPQ with weak coherent pulses.The result shows that multiphoton pulses have posed a serious threat to the participant’s privacy in QPQ protocols.Then we propose a decoy-state method that can help the honest participant detect the attack by exploiting multiphoton pulses and improving the key distillation process to defend against such attack.The analysis demonstrates that our decoy-state method significantly improves the security of the QPQ with weak coherent pulses,which solves a major obstacle in the practical application of the QPQ.