Rank Computation by a Recommender System: Malicious Attacks, Secret Sharing, Privacy, Fairness, Correctness & Rationality

Abstract : This work deals with the problem of rank computation by a corrupted recommender
system. It presents Fair Recommendation Algorithm (FRA) and related complexity analysis. Secure
multi-party computation may be an interesting solution for the aforesaid problem from the
perspectives of secret sharing, privacy, fairness, correctness, rationality, trust, commitment,
integrity, consistency, transparency and accountability. It is also important to verify
authentication, authorization, correct identification, privacy and audit of rank computation by an
efficient recommender system. Another critical issue is how to share a secret through threshold
cryptographic schema. This work analyzes two test cases with the support of fair recommendation
algorithm: (a) ranking in assessment and accreditation of education institutes and also digital
advertising and (b) rank computation in joint entrance examination (e.g. medical, engineering). This
study can be extended to various application domains such as financial service, healthcare,
education and corporate governance.
Keywords: Recommender System, Shilling attack, Rank computation, Secret Sharing, Privacy,
Fairness, Correctness, Rationality, Secure multi-party Computation, Threshold cryptography.