http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Deris Stiawan (검색결과 4 건)
- 무료
- 기관 내 무료
- 유료
-
Penetration Testing and Network Auditing: Linux
Stiawan, Deris,Idris, Mohd. Yazid,Abdullah, Abdul Hanan Korea Information Processing Society 2015 Journal of information processing systems Vol.11 No.1
Along with the evolution of Internet and its new emerging services, the quantity and impact of attacks have been continuously increasing. Currently, the technical capability to attack has tended to decrease. On the contrary, performances of hacking tools are evolving, growing, simple, comprehensive, and accessible to the public. In this work, network penetration testing and auditing of the Redhat operating system (OS) are highlighted as one of the most popular OS for Internet applications. Some types of attacks are from a different side and new attack method have been attempted, such as: scanning for reconnaissance, guessing the password, gaining privileged access, and flooding the victim machine to decrease availability. Some analyses in network auditing and forensic from victim server are also presented in this paper. Our proposed system aims confirmed as hackable or not and we expect for it to be used as a reference for practitioners to protect their systems from cyber-attacks.
-
Penetration Testing and Network Auditing: Linux
( Deris Stiawan ),( Mohd Yazid Idris ),( Abdul Hanan Abdullah ) 한국정보처리학회 2015 Journal of information processing systems Vol.11 No.1
Along with the evolution of Internet and its new emerging services, the quantity and impact of attacks have been continuously increasing. Currently, the technical capability to attack has tended to decrease. On the contrary, performances of hacking tools are evolving, growing, simple, comprehensive, and accessible to the public. In this work, network penetration testing and auditing of the Redhat operating system (OS) are highlighted as one of the most popular OS for Internet applications. Some types of attacks are from a different side and new attack method have been attempted, such as: scanning for reconnaissance, guessing the password, gaining privileged access, and flooding the victim machine to decrease availability. Some analyses in network auditing and forensic from victim server are also presented in this paper. Our proposed system aims confirmed as hackable or not and we expect for it to be used as a reference for practitioners to protecttheir systems from cyber-attacks.
-
IoT botnet attack detection using deep autoencoder and artificial neural networks
( Deris Stiawan ),( Susanto ),( Abdi Bimantara ),( Mohd Yazid Idris ),( Rahmat Budiarto ) 한국인터넷정보학회 2023 KSII Transactions on Internet and Information Syst Vol.17 No.5
As Internet of Things (IoT) applications and devices rapidly grow, cyber-attacks on IoT networks/systems also have an increasing trend, thus increasing the threat to security and privacy. Botnet is one of the threats that dominate the attacks as it can easily compromise devices attached to an IoT networks/systems. The compromised devices will behave like the normal ones, thus it is difficult to recognize them. Several intelligent approaches have been introduced to improve the detection accuracy of this type of cyber-attack, including deep learning and machine learning techniques. Moreover, dimensionality reduction methods are implemented during the preprocessing stage. This research work proposes deep Autoencoder dimensionality reduction method combined with Artificial Neural Network (ANN) classifier as botnet detection system for IoT networks/systems. Experiments were carried out using 3-layer, 4-layer and 5-layer pre-processing data from the MedBIoT dataset. Experimental results show that using a 5-layer Autoencoder has better results, with details of accuracy value of 99.72%, Precision of 99.82%, Sensitivity of 99.82%, Specificity of 99.31%, and F1-score value of 99.82%. On the other hand, the 5-layer Autoencoder model succeeded in reducing the dataset size from 152 MB to 12.6 MB (equivalent to a reduction of 91.2%). Besides that, experiments on the N_BaIoT dataset also have a very high level of accuracy, up to 99.99%.
-
Lukman Lukman,Muhammad Dimyati,Yan Rianto,Imam Much Ibnu Subroto,Tole Sutikno,Deden Sumirat Hidayat,Irene M Nadhiroh,Deris Stiawan,Sam Farisa Chaerul Haviana,Ahmad Heryanto,Herman Yuliansyah 한국과학학술지편집인협의회 2018 Science Editing Vol.5 No.2
This study aimed to propose a tool for measuring the research performance of researchers, institutions, and journals in Indonesia based on bibliometrics. Specifically, the output of this measurement tool, referred to as the S-score, is described, as well as its implementation on the main database portal in Indonesia. The S-score was developed by a focus group discussion. The following 8 evaluation items for journal accreditation were analyzed in the development process: journal title, aims and scope; publisher; editorial and journal management; quality of articles; writing style; format of PDF and e-journal; regularity; and dissemination. The elements of the S-score are as follows: number of journal article documents in Scopus, number of non-journal-article in Scopus, number of citations in Scopus, number of citations in Google Scholar, the h-index in Scopus, and the h-index in Google Scholar. The S-score yields results ranging from S1 to S6. The above metrics were implemented on the Science and Technology Index, a database portal in Indonesia. The measurement tool developed through the focus group discussion was successfully implemented on the database portal. Its validity and reliability should be monitored consistently through regular assessments of S-scores. The S-score may be a good example of a metric for measuring the performance of researchers, institutions, and journals in countries where most journals are not indexed by Scopus.
KISS연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
