Abstract:
In the telecommunication industry, effective identity management is crucial for maintaining secure and reliable communication services. With the increasing prevalence of digital services and the proliferation of user data, telecommunications companies face significant challenges in accurately identifying and managing customer identities. Traditional deterministic matching algorithms often fall short in handling the complexities of identity matching, leading to errors and vulnerabilities.
This abstract proposes the utilization of probabilistic matching algorithms as a solution to enhance identity management in the telecommunication industry. Probabilistic matching algorithms leverage statistical and machine learning techniques to determine the likelihood of two or more records belonging to the same individual, even in the presence of data inconsistencies, errors, or incomplete information. By employing probabilistic matching algorithms, telecommunication companies can achieve more accurate and reliable identity management, leading to improved customer experience, security, and operational efficiency.
This research aims to explore the benefits and challenges associated with employing probabilistic matching algorithms for identity management in the telecommunication industry. It will investigate various probabilistic matching techniques, such as fuzzy matching, machine learning-based matching, and record linkage, and evaluate their effectiveness in dealing with real-world identity management scenarios. The research will also consider the scalability and computational requirements of these algorithms to ensure their practical applicability in large-scale telecommunication systems.
Furthermore, this study will address the privacy and ethical considerations associated with probabilistic matching algorithms in the telecommunication industry. It will explore methods to ensure data protection, consent management, and compliance with relevant regulations, such as GDPR or CCPA, to maintain a balance between identity management efficiency and individual privacy rights.
The research outcomes will provide valuable insights into the feasibility and potential of employing probabilistic matching algorithms for identity management in the telecommunication industry. The findings will contribute to the development of more robust and accurate identity management systems, enabling telecommunication companies to better serve their customers while safeguarding their information.
EMPLOYING PROBABILISTIC MATCHING ALGORITHMS FOR IDENTITY MANAGEMENT IN THE TELECOMMUNICATION INDUSTRY, GET MOREÂ Â COMPUTER SCIENCE PROJECT TOPICS AND MATERIALS
