{'fraction_non_alphanumeric': 0.018641810918774968, 'fraction_numerical': 0.0, 'mean_word_length': 5.5064935064935066, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Public delegation & verifiability of matrix multiplication to a malicious cloud server

The rapid development of cloud computing services and expansion of mobile computing devices have made computation outsourcing a promising solution for execution of extensive computation. In this framework, a computationally weak client outsources its large computation load to a cloud server. However, outsourcing of data and computation to a cloud server brings many security and privacy concern. In this paper, we are addressing matrix multiplication (MM) problem, because MM is a computation-intensive problem and useful in many domains. In the proposed MM outsourcing algorithm, the client outsources input dataset to the cloud server without revealing to them both the input dataset and the output. The algorithm is a non-interactive solution to the client, it sends only input and receives output along with the proof of verification from the cloud server. Further, this work extends the definition of verifiable computation to public verifiable computation, which allows participating worker (not only the client) to verify the correctness of the result computed on the cloud server. The analytical analysis shows that the algorithm is successfully meeting the challenges of correctness, security, verifiability, and efficiency. The practical evaluation validates the proposed algorithm. The result analysis shows that the algorithm is highly efficient and endorses the practical usability of the algorithm.