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Filters: Author is Shafiq, Arham  [Clear All Filters]
2020-08-10
Wasi, Sarwar, Shams, Sarmad, Nasim, Shahzad, Shafiq, Arham.  2019.  Intrusion Detection Using Deep Learning and Statistical Data Analysis. 2019 4th International Conference on Emerging Trends in Engineering, Sciences and Technology (ICEEST). :1–5.
Innovation and creativity have played an important role in the development of every field of life, relatively less but it has created several problems too. Intrusion detection is one of those problems which became difficult with the advancement in computer networks, multiple researchers with multiple techniques have come forward to solve this crucial issue, but network security is still a challenge. In our research, we have come across an idea to detect intrusion using a deep learning algorithm in combination with statistical data analysis of KDD cup 99 datasets. Firstly, we have applied statistical analysis on the given data set to generate a simplified form of data, so that a less complex binary classification model of artificial neural network could apply for data classification. Our system has decreased the complexity of the system and has improved the response time.