A modified pheromone dominant ant colony algorithm for computer virus detection

S. Banerjee, Nashwa El-Bendary, A. Hassanien, Tai-hoon Kim
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Abstract

This paper proposes an elementary pattern detection approach for viruses propagated through e-mail and address books using the non-uniform pheromone deposition mechanism of ant colony. The local temporary tabu memory has been used to learn the pattern and it can combine known information from past viruses with a type of prediction for future viruses. This is achieved through certain generated test signature of viruses associated with e-mail over landscape. A non-uniform and non-decreasing time function for pheromone deposition and evaporation ensures that subsequent ants who are close enough to a previously selected trial solution will follow the trajectory or test landscape. They are capable to examine gradually thicker deposition of pheromone over the trajectory. It is empirically shown that the proposed modified pheromone learning mechanism can be an alternative approach to detect virus pattern for e-mail messages.
一种改进的信息素优势蚁群算法用于计算机病毒检测
本文提出了一种利用蚁群非均匀信息素沉积机制对电子邮件和地址簿传播的病毒进行初步模式检测的方法。局部临时禁忌存储器被用来学习这种模式,它可以将过去病毒的已知信息与对未来病毒的一种预测结合起来。这是通过生成与横向电子邮件相关的病毒的某些测试签名来实现的。信息素沉积和蒸发的非均匀和非递减的时间函数确保了与先前选择的试验解决方案足够接近的后续蚂蚁将遵循轨迹或测试景观。它们能够检查在轨迹上逐渐变厚的信息素沉积。实验结果表明,所提出的改进信息素学习机制可以作为一种检测电子邮件病毒型的替代方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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