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:
Kongzhi yu Juece/Control and Decision
Azerbaijan Medical Journal
Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery
Zhenkong Kexue yu Jishu Xuebao/Journal of Vacuum Science and Technology
Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering)
Zhonghua yi shi za zhi (Beijing, China : 1980)
Changjiang Liuyu Ziyuan Yu Huanjing/Resources and Environment in the Yangtze Valley
So far, various methods have been proposed to deal with cyber-attacks, but many of them are not capable of running in the real environment or do not have enough accuracy to detect different types of attacks. In this paper, using the features of k-means clustering algorithm, ineffective data in detection process are removed from the dataset. Then, the accuracy of attack detection increases by using the Gray Wolf Optimization (GWO) algorithm and replacing stronger wolves based on their degree of suitability. In each iteration of the algorithm, the fitness is computed and if it improves the algorithm is repeated again, otherwise the algorithm terminates. The main purpose of the proposed method is to increase the accuracy of detection as well as reduce the likelihood of getting stuck in local optimal points. The simulation results on 4 different types of attacks in the NSL-KDD and synthetic dataset show that about 3.2% better detection accuracy is obtained rather than other researches by adjusting the parameters of the gray wolf algorithm, as a conclusion, the proposed method has the necessary efficiency for detecting attacks on computer networks
with the incremental growth of the communication system, information security becomes an important issue. The need for securing information in fast, reliable, and relatively low-cost methods lead the researchers to work intensively in this field to find the optimum protective method that satisfies these requirements. A stream cipher is the most widely used technique in securing transmission data in the communication system since the overall security of the system depends only on the keystream used. This paper presents an intelligent approach to generate a keystream based on a combinatorial generator and clock-control generator. The design includes new techniques such as the saturated best resilient (SBR) function as a combined function and two nonlinear feedback shifts register (NLFSRs), using recency based memory techniques from the Tabu search to implement the clock-control method. The developed generator focuses on the keystream design for stream cipher by combining the strongest of the combinatorial generator with the complexity in the analysis of the clock control generator to avoid high immunity attacks. The output keystream from the generator passes the entire NIST test and two more correlation test with very good results
