The objective of the proposed research is to analyze an attack strategy targeting secondary frequency control (SFC) in dynamic virtual power plants (DVPPs) and the factors influencing its success. In a traditional power grid, frequency control is primarily managed by large synchronous generators (SGs). As power systems are evolving, DVPPs are becoming an integral part of modern grids to coordinate energy resources for efficient operation and contribute to frequency control. One of the key mechanisms for maintaining frequency within an acceptable range is SFC, which adjusts the set-points of SGs and other energy sources at the transmission level that participate in a DVPP through DVPP centralized control (DVPPCC). This adjustment, facilitated by the communication infrastructure, ensures frequency stability and maintains scheduled power transfer between neighboring areas of power systems. However, due to cyber vulnerabilities in communication networks, the SFC signal is susceptible to attacks, potentially leading to abnormal frequency deviations. This thesis will analyze an attack strategy targeting SFC and the factors influencing its success. First, it will outline the attacker model. Next, it will examine how power system parameters and DVPP operating modes, including grid-following support (GFL-support) and grid-forming (GFM), along with energy source dynamics, impact the likelihood of a successful attack. Then, data-driven algorithms will be implemented to establish guidelines for identifying worst-case scenarios from the system operator’s perspective. Adhering to these guidelines can increase the probability of a successful attack, which will be verified in a two-area system with detailed turbine/governor, energy resource, and protection models. Additionally, the thesis will analyze the attacker’s threat model, which identifies the attack surface required to steer the system frequency to an unsafe state while avoiding the activation of the remedial action scheme (RAS). If attackers gain access, they could prevent the tripping of generator circuit breakers, thereby increasing the risk of system-wide collapse and/or blackout. Finally, the thesis will explore detection and mitigation strategies to reduce the impact of such attacks.