Muhamad Maulana
Indonesian Islamic University

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Faux Insider Hazard Investigation on Non-Public Cloud Computing by Using ADAM’s Technique Dwi Kurnia Wibowo; Ahmad Luthfi; Yudi Prayudi; Erika Ramadhani; Muhamad Maulana
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 6 (2022): Desember 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v6i6.4714

Abstract

Cloud computing is a service system mechanism that businesses and organizations use to perform computerized and integrated transactions over computer networks. The service system must, of course, be”matched”with a”certain amount”of security. It is applied to” forecast the probability of cybercrime. A Cloud Service Provider (CSP) often offers cloud-based services with a basic level of security. Typically, CSPs are set up to offer their services on the open internet. Data security-focused organizations strive to shield their systems from a wide range of attackers. One of the alternatives is to construct a private cloud computing system. The issue is the potential for Man in the Cloud (MITC) assaults, which compromise and modify identities and are identified in cloud systems as phony insider threats. Based on the ISO 27032 standard research, the goal of this work is to undertake a threat analysis of MITC attack methodologies against private cloud computing services. With regards to risks to cloud services in a private cloud computing environment, it is intended that reporting and documenting the study' findings would lead to suggestions for more research and cybersecurity management procedures.
Klasifikasi Serangan Jaringan untuk Investigasi Forensik Jaringan: Tinjauan Literatur Muhamad Maulana; Ahmad Luthfi; Dwi Kurnia Wibowo
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 5 (2023): October 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i5.5153

Abstract

The computer network plays an important role in supporting various jobs and other activities in the cyber world. Various kinds of crimes have often occurred on computer networks. It is very demanding to build a computer network architecture that is safe from attacks to protect the data transacted. If there has been an attack on the computer network, of course, further investigation must be carried out to identify the attacker and the motive for the attack. An additional need is to evaluate the security of the network. This article reports a systematic review of the literature aiming to map the classification of attacks on computer networks and map future research. Based on the exploration, 30 key studies were selected that reveal the mapping of attack classifications on computer networks. The results of the literature review show that attacks on computer networks vary widely. Based on the results of the literature review conducted, it produces a roadmap for future research, which is to classify attacks on computer networks using a machine learning approach. The use of machine learning serves to help classify and investigate the needs for attacks on computer networks. The SVM method in this case was chosen based on previous research that was widely used for data-based classification.