Homes with integrated state of the art technology are considered Smart Homes. A smart home has special systems which enable remote control via remote computer or smart phones. These modern integrated services are supported by electrical power infrastructures called Smart Grids, which provides a stable electrical power environment to support all functionalities, with intelligent power systems that provide increased power quality. Inside a Smart home, a legacy metering system called Smart Meters are installed offering new functionalities such as remote readings of power consumption, and different time usage of tariffs.Preliminary research has already indicated vulnerability attacks on smart meters which affect the security and privacy in smart meters. Security issues in this system include vulnerabilities and privacy issues includes information leakage in real-time consumption data that is recorded by the smart meters.Enhancing both security and privacy in the smart meters are the main purpose of this thesis. The principle goal of this research is to provide more understanding about the smart meters from a security and privacy perspective. This thesis investigates issues and problems in smart meters and proposes a secure communication protocol in the application layer, in addition to a proof-of-concept of the final solution. In this research we introduce the solution by means of two scenarios, we highlight the effects of an attack on the smart meters on levels of simulation and theory. The first scenario is to "take control over the smart meter to access the data consumptions in the smart meters". The proposed solution of using the Smart Phone as a third part to protect the smart meters has been evaluated using a network simulation tool. The result shows that the data captured by attacking node is encrypted and can't be used for any useful operation. In the second scenario, "monitoring the data consumptions to harm the user's privacy", in other words, stealing the user's devices. The proposed solution is using the home electrical power routing to moderate the home's load signature in order to hide appliance usage information. Data clusters are implemented as a proof of concept to evaluate the data. The results show that there is only 99.5 % correct clustered data with good quality.