Deteksi Twitter Bot menggunakan Klasifikasi Decision Tree

Advance development of social media application has affected to human lifestyle. Everyone can obtain information from social media easyly. Its become easier to communicate each other using social media. Twitter is one of the fastest growing social media application. Deliver good and hoax information from one user to another. Event there are alot of fake account (bot) in Twitter. This objection of this study is to detect Twitter Bot accounts on Twitter social media by using the Decission Tree classification. Experiment results show the accuracy performance of the Decision Tree model reached 88.84% and UC curve by 0.965. Its shows that the Decision Tree classification is excellent in detecting Twitter Bot accounts

From Intrusion Detection to Attacker Attribution: A Comprehensive Survey of Unsupervised Methods

Over the last five years there has been an increase in the frequency and diversity of network attacks. This holds true, as more and more organisations admit compromises on a daily basis. Many misuse and anomaly based Intrusion Detection Systems (IDSs) that rely on either signatures, supervised or statistical methods have been proposed in the literature, but their trustworthiness is debatable. Moreover, as this work uncovers, the current IDSs are based on obsolete attack classes that do not reflect the current attack trends. For these reasons, this paper provides a comprehensive overview of unsupervised and hybrid methods for intrusion detection, discussing their potential in the domain. We also present and highlight the importance of feature engineering techniques that have been proposed for intrusion detection. Furthermore, we discuss that current IDSs should evolve from simple detection to correlation and attribution. We descant how IDS data could be used to reconstruct and correlate attacks to identify attackers, with the use of advanced data analytics techniques. Finally, we argue how the present IDS attack classes can be extended to match the modern attacks and propose three new classes regarding the outgoing network communicatio