In this paper, a problem of random disturbance attenuation capabilities for linear time-invariant continuous systems, affected by random disturbances with bounded 𝜎-entropy, is studied. The 𝜎-entropy norm defines a performance index of the system on the set of the aforementioned input signals. Two problems are considered. The first is a state-space 𝜎-entropy analysis of linear systems, and the second is an optimal control design using the 𝜎-entropy norm as an optimization objective. The state-space solution to the 𝜎-entropy analysis problem is derived from the representation of the 𝜎-entropy norm in the frequency domain. The formulae of the 𝜎-entropy norm computation in the state space are presented in the form of coupled matrix equations: one algebraic Riccati equation, one nonlinear equation over log determinant function, and two Lyapunov equations. Optimal control law is obtained using game theory and a saddle-point condition of optimality. The optimal state-feedback control, which minimizes the 𝜎-entropy norm of the closed-loop system, is found from the solution of two algebraic Riccati equations, one Lyapunov equation, and the log determinant equation.