Imagine a room with millions of mysterious switches and hundreds of ceiling lamps. You don’t know which switch does what, but you’re curious. As you experiment with different combinations, the lamps’ brightness varies. This scene is a simple metaphor for the complex challenge of genomics research – understanding how different genetic ‘switches’ affect our health. […]

Introduction: Privacy-preserving computation is a crucial discipline that protects the privacy of confidential data while facilitating secure analysis. In graph problems, secure multiparty computation (SMC) presents a promising approach to performing these functionalities. This article delves into the notable advancements in privacy-preserving parallel algorithms recently introduced in a Ph.D. thesis. By integrating graph algorithms with […]

We are living in a world in which data is not just getting bigger; it is also getting more and more interconnected. Large graph analytics is a useful tool for gaining insights from large volumes of interconnected data and has applications in various fields such as social media, biology, and telecommunications. An example of the […]