首页> 外文会议>2014 International Conference on Soft Computing amp; Machine Intelligence >Advance Artificial Intelligence Based Mutual Authentication Technique with Four Entities in 4-G Mobile Communications
【24h】

Advance Artificial Intelligence Based Mutual Authentication Technique with Four Entities in 4-G Mobile Communications

机译:4-G移动通信中基于先进的基于人工智能的四实体互认证技术

获取原文
获取原文并翻译 | 示例

摘要

4-G mobile communications system is offering high speed data communications technology having connectivity to all sorts of the networks including 2-G and 3-G mobile networks. Authentication of a mobile subscriber (MS) or a subnetwork and a main network are an important issue to check and minimize security threats or attacks. An advanced artificial intelligence based mutual authentication system applying fuzzy neural network with four entities is proposed. Voice frequency of the salutation or the selective words used by a subscriber like Hello, Good Morning, etc. is taken as first entity. Second entity is chosen as thumb fingerprint matching of the calling subscriber with his/her stored thumb fingerprint. Then third entity is taken as face image matching of the calling subscriber. Fourth entity is granted as probability of the salutation word from subscriber's talking habit while initializing a call. These four entities such as probability of particular range of frequencies for the salutation word, the thumb fingerprint matching, the face image matching of the subscriber, using particular salutation or greeting word at the time of starting a call are used with the most frequently, more frequently, and less frequently by the calling subscriber like uncertainty in Artificial Intelligence. Now different relative grades are assigned to the most frequently, more frequently, and less frequently used parameters. Fuzzy operations such as intersection and union are computed taking three membership functions at a time out of four membership functions to adopt fuzzy neural network. Thereafter, the optimum or the final fuzzy operations are computed according to the assumed weightages. Lastly, the optimized fuzzy operations are defuzzified by the Composite Maxima method and the results are tested according to the invented fuzzy neural rule. If the results are satisfactory, the subscriber or the sub-network and the network (the switch or the server) are mutually authenticated in- 4-G mobile communications.
机译:4-G移动通信系统正在提供高速数据通信技术,该技术可连接到包括2-G和3-G移动网络在内的各种网络。移动用户(MS)或子网和主网络的身份验证是检查和最小化安全威胁或攻击的重要问题。提出了一种先进的基于模糊神经网络的四个实体相互认证系统。由诸如Hello,Good Morning等的用户使用的称呼的语音频率或选择词作为第一实体。选择第二实体作为主叫用户与他/她存储的拇指指纹的拇指指纹匹配。然后将第三实体作为主叫用户的面部图像匹配。第四实体被授予作为初始化呼叫时来自用户通话习惯的称呼词的概率。这四个实体(例如,针对称呼词的特定频率范围的概率,拇指指纹匹配,订户的面部图像匹配,在呼叫开始时使用特定称呼或问候词)使用频率最高,经常出现,而主叫用户则不那么频繁,例如人工智能中的不确定性。现在,将不同的相对等级分配给最频繁,更频繁和不经常使用的参数。采用四个隶属度函数中的三个隶属度函数一次计算相交和并集等模糊运算,以采用模糊神经网络。此后,根据假定的权重计算最佳或最终模糊运算。最后,通过复合极大值方法对优化后的模糊运算进行去模糊处理,并根据发明的模糊神经规则对结果进行检验。如果结果令人满意,则在4-G移动通信中相互认证订户或子网以及网络(交换机或服务器)。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号