Among the SAT-resilient logic locking techniques, the Stripped-Functionality-Logic-Locking (SFLL) is the most promising solution which can guard the intellectual property against approximate, sensitization, SAT, and structural attacks which target Point-function techniques. However, even the SFLL technique has been shown to be vulnerable to a recent class of structural attacks that identify the perturbation logic. In this paper, we first categorize all possible classes of attacks on SFLL. Then we propose ENTANGLE a novel logic locking technique built upon SFLL that can resist all of these attacks, including the emerging ML-Based attacks. We test our technique against publicly available SFLL attacks. The implementation results show that ENTANGLE can secure large-sized industrial circuits with an average overhead of 11.6 percent and 9.1 percent for area and power, respectively.