http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
WORM-HUNTER: A Worm Guard System using Software-defined Networking
( Yixun Hu ),( Kangfeng Zheng ),( Xu Wang ),( Yixian Yang ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.1
Network security is rapidly developing, but so are attack methods. Network worms are one of the most widely used attack methods and have are able to propagate quickly. As an active defense approach to network worms, the honeynet technique has long been limited by the closed architecture of traditional network devices. In this paper, we propose a closed loop defense system of worms based on a Software-Defined Networking (SDN) technology, called Worm-Hunter. The flexibility of SDN in network building is introduced to structure the network infrastructures of Worm-Hunter. By using well-designed flow tables, Worm-Hunter is able to easily deploy different honeynet systems with different network structures and dynamically. When anomalous traffic is detected by the analyzer in Worm-Hunter, it can be redirected into the honeynet and then safely analyzed. Throughout the process, attackers will not be aware that they are caught, and all of the attack behavior is recorded in the system for further analysis. Finally, we verify the system via experiments. The experiments show that Worm-Hunter is able to build multiple honeynet systems on one physical platform. Meanwhile, all of the honeynet systems with the same topology operate without interference.
A Nature-inspired Multiple Kernel Extreme Learning Machine Model for Intrusion Detection
( Yanping Shen ),( Kangfeng Zheng ),( Chunhua Wu ),( Yixian Yang ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.2
The application of machine learning (ML) in intrusion detection has attracted much attention with the rapid growth of information security threat. As an efficient multi-label classifier, kernel extreme learning machine (KELM) has been gradually used in intrusion detection system. However, the performance of KELM heavily relies on the kernel selection. In this paper, a novel multiple kernel extreme learning machine (MKELM) model combining the ReliefF with nature-inspired methods is proposed for intrusion detection. The MKELM is designed to estimate whether the attack is carried out and the ReliefF is used as a preprocessor of MKELM to select appropriate features. In addition, the nature-inspired methods whose fitness functions are defined based on the kernel alignment are employed to build the optimal composite kernel in the MKELM. The KDD99, NSL and Kyoto datasets are used to evaluate the performance of the model. The experimental results indicate that the optimal composite kernel function can be determined by using any heuristic optimization method, including PSO, GA, GWO, BA and DE. Since the filter-based feature selection method is combined with the multiple kernel learning approach independent of the classifier, the proposed model can have a good performance while saving a lot of training time.
Hierarchical Identity-based Broadcast Encryption Scheme from LWE
Chunli Yang,Shihui Zheng,Licheng Wang,Xiuhua Lu,Yixian Yang 한국통신학회 2014 Journal of communications and networks Vol.16 No.3
A hierarchical identity-based broadcast encryption (HIBBE)scheme is an identity-based broadcast encryption (IBBE)scheme in a hierarchical environment. In order to obtain secure HIBBEschemes in the quantum era, we propose an H-IBBE schemebased on the learning with errors problemassumption.Our schemeachieves indistinguishability from random under adaptive chosenplaintextand chosen-identity attacks in the random oracle model.
Yuanqing Hu,Fengxia Li,Yixian Zheng,Xinan Jiao,Liqing Guo 한국미생물·생명공학회 2020 Journal of microbiology and biotechnology Vol.30 No.6
Vibrio parahaemolyticus is a major gastroenteritis-causing pathogen in many Asian countries. Antimicrobial resistance in V. parahaemolyticus has been recognized as a critical threat to food safety. In this study, we determined the prevalence and incidence of antimicrobial resistance in V. parahaemolyticus in the southern Fujian coast, China. A total of 62 isolates were confirmed in retail aquatic products from June to October of 2018. The serotype O3:K6 strains, the virulence genes tdh and trh, antibiotic susceptibility and molecular typing were investigated. Then plasmid profiling analysis and curing experiment were performed for multidrug-resistant strains. The results showed that the total occurrence of V. parahaemolyticus was 31% out of 200 samples. Five strains (8.1%) out of 62 isolates were identified as the V. parahaemolyticus O3:K6 pandemic clone. A large majority of isolates exhibited higher resistance to penicillin (77.4%), oxacillin (71%), ampicillin (66.1%) and vancomycin (59.7%). Seventy-one percent (44/62) of the isolates exhibited multiple antimicrobial resistance. All 62 isolates were grouped into 7 clusters by randomly amplified polymorphic DNA, and most of the isolates (80.6%) were distributed within cluster A. Plasmids were detected in approximately 75% of the isolates, and seven different profiles were observed. Seventy-six percent (25/33) of the isolates carrying the plasmids were eliminated by 0.006% SDS incubated at 42°C, a sublethal condition. The occurrence of multidrug-resistant strains could be an indication of the excessive use of antibiotics in aquaculture farming. The rational use of antimicrobial agents and the surveillance of antibiotic administration may reduce the acquisition of resistance by microorganisms in aquatic ecosystems.