KLASIFIKASI TINGKAT KEPARAHAN SERANGAN JARINGAN KOMPUTER DENGAN METODE MACHINE LEARNING

Computer networks are currently developing very rapidly, so that many electronic devices are connected to the internet, but the security system adopted by these devices must be qualified so they are not vulnerable to threats and dangers. Researchers want to find out how severe the threat of an attack is detected by a firewall using data records from a company, using machine learning, namely K-Nearest Neighbors, Decission Tree. Classification of the severity of a computer network security system is usually called the severity level. In this study, the limitation of the seriousness level of the attack was divided into 3 parts from the highest level, namely critical, high and medium. The processed dataset is logging into the firewall as many as 5999 with 23 columns or features. The best of the three methods are K-Nearest Neighbors getting 100% accuracy and Decission Tree getting 100% accuracy . With the results of this data processing, the machine learning method is very suitable to be used to classify the severity of computer network attacks

Computer network attacks as an act of aggression in the context of the development of modern international relations: pros and cons

The article analyzes the conflicting approaches to the possible recognition of computer network attacks as an act of aggression in the focus of modern international relations and trends in scientific and technological progress. The question raised in the article is as follows: is aggression against another state possible through the exclusive use of cyber weapons? To solve the indicated problem, the scholastic method of conducting a discussion is used, in which two series of contradictory arguments regarding the subject of discussion are put forth, and the conclusion summarizes the general conclusion based on particular theses. The conclusion is argued that the historically established definition of aggression in modern conditions of development of scientific and technological progress does not meet the interests of international peace and security, since new types of force of destructive influence constantly appear, which can generate consequences comparable in scale and severity to the consequences of using conventional weapons. However, there are still some problematic moments that arise in connection with the qualification of cyberattacks as a crime of aggression, requiring understanding and resolution in accordance with the development of the science of international law and law enforcement practice in the context of international relations.

String Matching untuk Mendeteksi Serangan Sniffing (ARP Spoofing) pada IDS Snort

Sniffing technique (ARP Spoofing) is an attack that sends fake ARP packets or ARP packets that have been modified according to the network address attacker's to poison the victim's ARP cache table. ARP spoofing attack is a dangerous attack because it can monitor the activities of victims in searching the browser and can steal social logins, office and other accounts. This attack supports the occurrence of other computer network attacks such as Denial of service, Man in the middle attack, host impersonating and others. Sniffing attacks are generally found in places that provide public Wi-Fi such as campus, libraries, cafes, and others. IDS Snort can detect sniffing attacks (Arp Spoofing). String Matching Method KMP algorithm is applied to detect attacks on snort logging files to provide alerts (messages) to users. Tests carried out are black box testing to test application functionality, and accuracy testing. All application functionality was successful, and testing the accuracy of the match between manual calculations for string matching and accurate application.

An Enhanced View of Incidence Functions for Applying Graph Theory to Modeling Network Intrusions

Graph theory provides a robust tool for modeling a diverse range of subjects. It has been widely applied to computer networks and even network attacks. However, the incidence function in graph theory is often given a cursory treatment. This current research involves applying a range of information theory equations to describe the incidence function in a graph of a computer network. This improves modeling of computer network attacks and intrusions. Specifically attacks that involve substantial changes in network traffic can be more accurately modeled, if the incidence function of the graph is expanded.

Gezi Park Protests, Corruption Investigation, and the Control of the Online Public Sphere

This chapter focuses on the online sphere. Through the prism of two developments in 2013—the Gezi Park protests and the corruption scandal—it discusses the possibilities and limits of online communications and the AKP's authoritarian reflex toward the burgeoning networked public sphere. It shows that the AKP's regulation and control of the online public sphere along the axes of nationalism, statism, and religious conservatism are not new, and that it has used three types of controls. These are first-generation controls that consist of Internet filtering and blocking, second-generation controls that involve passing legal restrictions, content removal requests, the technical shutdown of websites, and computer-network attacks; and third-generation controls that include warrantless surveillance, the creation of “national cyber-zones,” state-sponsored information campaigns, and direct physical action to silence individuals or group.