Technology Reports of Kansai University (ISSN: 04532198) is a monthly peer-reviewed and open-access international Journal. It was first built in 1959 and officially in 1975 till now by kansai university, japan. The journal covers all sort of engineering topic, mathematics and physics. Technology Reports of Kansai University (TRKU) was closed access journal until 2017. After that TRKU became open access journal. TRKU is a scopus indexed journal and directly run by faculty of engineering, kansai university.
Technology Reports of Kansai University (ISSN: 04532198) is a peer-reviewed journal. The journal covers all sort of engineering topic as well as mathematics and physics. the journal's scopes are
in the following fields but not limited to:
In the capabilities of today technologies, IoT become a merging technology that wildly apply nowadays. Meanwhile, at the same time since IoT technology become more in getting much popularity. At the same time, botnet infection that infect IoT become increasing. Consequently, that’s is a lot botnet detection is infected IoT devices. Based on Cybersecurity Malaysia there are various attack on the IoT via botnet. Then a number of researchers has proposed many various methods in order to detect IoT botnet such as machine learning, deep learning, graph theory and others method. This paper has reviewed the number of detection methods that will propose previous researcher in this review. This paper provides summarize of type of IoT botnet method according on the researcher method. This paper also lists some IoT devices that been attack based on previous paper. The contribution of this paper is to give the community the better understanding of detection method that getting much popularity nowadays to be applied. There a lot of botnet manufactured is difficult to detect. Previous researcher proposed several detections and several methods. The review of previous work is for community understanding. In the capabilities of today technologies, IoT become a merging technology that wildly apply nowadays. Meanwhile, at the same time since IoT technology become more in getting much popularity. At the same time, botnet infection that infect IoT become increasing. Consequently, that’s is a lot botnet detection is infected IoT devices. Based on Cybersecurity Malaysia there are various attack on the IoT via botnet. Then a number of researchers has proposed many various methods in order to detect IoT botnet such as machine learning, deep learning, graph theory and others method. This paper has reviewed the number of detection methods that will propose previous researcher in this review. This paper provides summarize of type of IoT botnet method according on the researcher method. This paper also lists some IoT devices that been attack based on previous paper. The contribution of this paper is to give the community the better understanding of detection method that getting much popularity nowadays to be applied. There a lot of botnet manufactured is difficult to detect. Previous researcher proposed several detections and several methods. The review of previous work is for community understanding
"Open data" is a term officially introduced in the year 2007 as an expansion of data sharing. It is defined as data that anyone can access, use and share. In a global scenario, it can be seen that there is a lot of data residing in silos. Subsequently, these data are just wasted without having a knowledge contribution to the community. On the contrary, there are high demands regarding data in many fields, and this trend becomes tremendously increasing day by day. In a globalised world where sharing potential is at its peak, yet everyone is so concerned about locking up their data. Undeniably, there are sensitive data, and there are reasons to keep it private. Henceforth, we do a preliminary study on the current scenario of data management in the Malaysian Technical University Network (MTUN) to find out the practicalities on data management and concerns that arise towards opening up the data. The results shown were based on personal structured interview sessions to the respective stakeholders of MTUN universities, which are; legal officers, information technology officers and strategic department officers. The interviewees are respectively from four (4) MTUN universities which are Universiti Teknikal Malaysia Melaka (UTeM), Universiti Malaysia Pahang (UMP), Universiti Tun Hussein Onn (UTHM) and Universiti Malaysia Perlis (UNIMAP). Eventually, for evolution, there is a need to share the data whenever possible. Nevertheless, it will bring benefit many parties instead of putting it up in silos
