Transmission system is one of the most important assets in secure power delivery. Recent advancements toward automation of smart grids and application of supervisory control and data acquisition (SCADA) systems have increased vulnerability of power grids to cyberattacks. Cyberattacks on transmission network, specifically the power transmission lines, are among crucial emerging challenges for the operators. If not identified properly and in a timely fashion, they can cause cascading failures leading to blackouts. This chapter tackles false data injection modeling from the attacker’s perspective. It further develops an algorithm for detection of false data injections in transmission lines. To this end, first, a bi-level mixed integer programming problem is introduced to model the attack scenario, where the attacker can target a transmission line in the system and inject false data in load measurements on targeted buses in the system to overflow the targeted line. Second, the problem is analyzed from the operator’s viewpoint and a detection algorithm is proposed using l1 norm minimization approach to identify the bad measurement vector in data readings. In order to evaluate the effectiveness of the proposed attack model, case studies have been conducted on IEEE 57-bus test system.