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In recent years, research works in field of the network security have been directed to inspire from biological immune system so as to solve complex problems.  Artificial immune system (AIS) and its applied immunity potential with prerequisite for bio defense, is always involved as a method for organization’ security control and network anomaly detection.  In this research, different immunity methods in comparison with other machine learning and meta-heuristic algorithms have been analyzed for our main purpose; that is to provide a novel approach for solving the intrusion detection.  All of evaluations accomplished on WEKA data mining tool v3.6 under NSL-KDD dataset.  Results of experiment show that the AIS methods ARIS2Parallel, Immunos99 and CSCA cause to enhance in accuracy rates sensibly after feature selection phase was embedded to them. So, approach of Bat+ARIS2Parallel with correlation coefficient of 0.946, detection rate of 0.973, accuracy rate of 0.9725 and false positive rate of 0.028  has obtained an idealistic classification compared to other approaches in tests.  Since it has high cc rate, it seems that is reliable to be used in researches for IDS developments in future.
Keywords:   Intrusion detection, feature selection, meta-heuristic algorithms, artificial immune system, information gain. 

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The command and control warfare between hostile countries is a common type of battles. This warfare occurs during the real war surely. Its goal is to destruct the focus of the opposite side's commander. This issue possesses a high importance at the beginning of the war as it affects the analysis of the opposite side whether to start a war, or avoid it. One of the main questions of research is whether you can predict these feedbacks and decisions. The main goal of the article is to create a set of possible suggestions based on mutual decisions. It is obviously important to predict the behavior and to estimate the choices of the rival. In this article, we study modeling and analysis of the scenarios for hostile countries (blue and red) in the Command and control war, by non-cooperative game theory method –a very useful tool for qualitative and quantitative analysis of the partner's decisions- to predict the most likely outcomes. Recognizing the possible actions of the countries and their preferences over the feasible states make the results and equilibrium more accurate. The results of this study show that low cost actions, such as jamming the network of special link of command and control and disorder in the systems of navigation can reduce power of the competitor's combat, and pave the way for the next tough actions