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Recently, considerable research has been performed in cryptography and security to optimize the area, power, timing, and energy needed for the point multiplication operations over binary elliptic curves. In this paper, we propose an efficient implementation of point multiplication on Koblitz curves targeting extremely-constrained, secure applications. We utilize the Gaussian normal basis (GNB) representation of field elements over GF(2m) and employ an efficient bit-level GNB multiplier. One advantage of this GNB multiplier is that we are able to reduce the hardware complexity through sharing the addition/accumulation with other field additions. We utilized the special property of normal basis representation and squarings are implemented very efficiently by only rewiring in hardware. We introduce a new technique for point addition in affine coordinate which requires fewer registers. Based on this technique, we propose an extremely small processor architecture for point multiplication. Through application-specific integrated circuit (ASIC) implementations, we evaluate the area, performance, and energy consumption of the proposed crypto-processor. Utilizing two different working frequencies, it is shown that the proposed architecture reaches better results compared to the previous works, making it suitable for extremely-constrained, secure environments.