Ransomware viruses have become a dangerous threat increasing rapidly in recent years. One of the variants is Conti ransomware that can spread infection and encrypt data simultaneously. Attacks become a severe threat and damage the system, namely by encrypting data on the victim's computer, spreading it to other computers on the same computer network, and demanding a ransom. The working principle of this Ransomware acts by utilizing Registry Query, which covers all forms of behavior in accessing, deleting, creating, manipulating data, and communicating with C2 (Command and Control) servers. This study analyzes the Conti virus attack through a network forensic process based on network behavior logs. The research process consists of three stages, the first stage is simulating attacks on the host computer, the second stage is carrying network forensics by using live forensics methods, and the third stage is analysing malware by using statistical and dynamic analysis. The results of this study provide forensic data and virus behavior when running on RAM and computer networks so that the data obtained makes it possible to identify ransomware traffic on the network and deal with zero-day, especially ransomware threats. It is possible to do so because the analysis is an initial step in generating virus signatures based on network indicators.

Sodinokibi Ransomware virus becomes a severe threat by targeting data encryption on a server, and this virus infection continues to spread to encrypt data on other computers. This study aims to mitigate by experiment with building a prevention system through computer network management. The mitigation process is carried out through static, dynamic, and Software-Defined Networking (SDN) analysis to prevent the impact of attacks through programmatic network management. SDN consists of two main components in its implementation, the Ryu controller and Open Virtual Switch (OVS). Result testing mitigation system on infected networks by crippling TCP internet protocol access can reduce virus spread by 17.13% and suppress Sodinokibi traffic logs by up to 73.97%. Based on the percentage data, SDN-based mitigation in this study is per the objectives to make it possible to mitigate Ransomware attacks on computer network traffic.

Kesehatan jantung merupakan investasi jangka panjang untuk keberlangsungan hidup. Oleh karena itu untuk mewujudkan jantung sehat dan terhindar dari penyakit kardiovaskular ini, dibuatlah sebuah inovasi alat prototipe monitoring kesehatan jantung dengan sistem online. Sistem monitoring ini mengkombinasikan antara sistem pakar VCIRS (Variable Centered Intelligence Rule System ), pengukuran detak jantung BPM (beat per minute), dan IoT (Internet of Things) yang bertujuan untuk memonitoring kesehatan jantung dan mendeteksi penyakit jantung secara dini serta dilakukan mandiri. Keluaran dari sistem ini adalah pernyataan bahwa pengguna dalam kondisi jantung sehat atau menderita gejala penyakit jantung kemudian dilanjutkan dengan analisa dari pengguna dengan memilih gejala sesuai yang form yang disediakan. Berdasarkan pengujian dan analisa sistem bahwa prototipe alat monitoring kesehatan jantung telah mampu menganalisa serta berjalan dengan baik. Hasil dari analisa alat ini dapat dilihat secara online di situs website.

This study aims to reconstruct an attack event and analyze the source of viral infection based on network traffic logs so that the information obtained can be used for a new reference in the security system. Recent attacks on computer network systems cannot be easily detected, as cybercrime has used a variant of the Ryuk Ransomware virus to penetrate security systems, encrypt drives, and computer network resources. This virus is very destructive and has an effective design with a file size of about 200,487 Bytes so it does not look suspicious. The research steps are done through Trigger, Acquire, Analysis, Report, and Action (TAARA). The forensic tools used to obtain log data are Wireshark, NetworkMiner, and TCPDUMP. Based on the results of forensic data obtained include a timestamp, source of the attack, IP address, MAC address, hash signature sha256, internet protocol, and the process of infection. Based on the data obtained in this study has been by the expected objectives.

Digital evidence plays an essential role in meeting the forensic need to uncover cybercrime and search for trace information of perpetrators. Digital evidence is vulnerable to system changes, human error, theft, deletion, and data manipulation, requiring security efforts to maintain authenticity. This study offers optimization of the chain of custody systems to maintain digital evidence integrity using authentication applications connected to the website server database. The design of the chain of custody system uses blockchain technology and K-means clustering algorithm. This research process consists of two stages. The first stage is the prototype of blockchain-based user access authentication applications. The second stage is the implementation of K-means clustering to determine the place of data storage according to its classification. The results of this study are the maximum security for blockchain-based chain of custody with the efficiency value of this application of 94.73% and the system load value of 0.223%. The total cost of deploying the application is 0.026702786 ETH. Based on this research can help to secure digital evidence information.