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Among the many hacking attempts carried out against information systems for the past few years, cyber-attacks that could lead to a national-level threat included attacks against nuclear facilities particularly nuclear power stations. Two of the typical examples are the Stuxnet attack against an Iranian nuclear facility and the cyber threat against Korea Hydro and Nuclear Power in December 2015. The former has proven that a direct cyber-attack can actually stop the nuclear power station, and the latter has shown that people can be terrorized with only a (cyber) threat. After these incidents, security measures for cyber-attacks against industrial control systems have been strengthened. The nuclear power stations also changed their passive concept of executing security measures by operating the plant with an isolated network to prepare for the cyber-attacks carried out by malicious codes. The difference between the two concepts is that the latter has been formulated based on the possibility that most of the control systems can be targets of cyber-attacks. Threats against control systems are gradually increasing nowadays, so the relevant industries are implementing some measures to identify/develop safe and reliable digital equipment and identify risks to establish effective cyber security plans. Thus, this paper proposes a security measure based on the classification of past attack incidents against control systems and the big data analysis technique that processes the data generated from individual security equipment. The security of control systems is expected to be strengthened through such effective measure.

Recently, the cloud services have largely increased due to smart working which allows people to work freely anywhere. For this reason, the volume and the types of data have also increased so that it has become an urgent priority to meet the functional requirements for the services. The solution can be cloud service. However, even the cloud services require a method to support the HW resources (e.g., memory, server or network) when the system experiences capacity deficits because of its limited capacity. Thus, so called a ‘multi-clouds’, which allows provision of needed resources by configuring a multiple number of clouds, is necessary. In this study, we present a method of measuring quality and the standard of service level when a multi-cloud service is required due to the limitations of a single-cloud which cannot deal with both capacity and service requirements. By supporting the service with multi-cloud resources that cannot be included in the single-cloud, a better quality service will be provided to the users. When a customer uses a single cloud, the service provider will not be able to provide unlimited service due to the limitation of available resources. The multi-cloud system can deal with this problem but a suitable quality assurance method should be secured as well. In the study, we have conducted a research on the method of securing improved SLA for multi-clouds.

The areas where artificial intelligence (AI) is employed are gradually increasing. The latest malicious codes are continually being found in the security control area and the security teams in various organizations are investigating an average of 200,000 security incidents a day and often wasting much of their time in tracking wrong targets or attacking methods. It is expected that the security-related incidents will be increased more than twice in near future. Thus, the security control staff will be able to prevent security breaches only by rapidly analyzing the latest vulnerabilities and logs in their systems or security equipment. In this study, we have studied the possibility of utilizing current AIs used for diagnosis of cancers, translations or simple conversations, along with the future direction of AI for security control. The study also attempts to find an effective method of reducing damages by rapidly analyzing attack methods and vulnerabilities, hoping the method will be effective in protecting the systems from a new variety of attacks.

Purpose: A multicentre open clinical trial was conducted to evaluate the clinical usefulness of a slower titration of topiramate (TPM) to 300 mg /day as adjunctive therapy for medically intractable partial epilepsies.Methods: Ninteen centres participated in the trial. Study patients had to have had two or more seizures per 4 weeks whilst taking maximum tolerated doses of one but not more than two anti-epileptic drugs. The starting dose of TPM was 25 mg /day and the dose was increased weekly by 25 mg /day until 100 mg /day was reached. Thereafter TPM was increased by 50 mg /day weekly up to the target dose of 300 mg /day, which was followed by an 8 week maintence phase. Seizure outcomes were measured by intention-to-treat analysis (ITTA)Results: Two hundred and thirteen patients entered the study. Median seizure frequency reduction rate was 44.8%, responder rate was 47.6%, and seizure free rate was 9.0%. These results were comparable to that of TPM 600 mg /day in our previous controlled trial. In subgroup analysis, seizure free rate was higher in those patients with a lower baseline seizure frequency rate. Seventeen patients (8.0%) were prematurely withdrawn from the study due to adverse events (AE) or lack of effect. One or more AEs were reported in 22% of patients, with dizziness being the most frequent AE. Other AEs occurred in less than 5% of patients.Conclusion: TPM 300 mg /day was effective and in conjunction with a slower dose-titration, markedly reduced the incidence of AEs, compared with previous study.

OBJECTIVE: To assess the efficacy and safety of Cerebrolysin over 4 weeks in patients with probable Alzheimer's disease (AD). DESIGN: A 4-week randomized, double-blind, placebo-controlled, multicenter clinical trial. An unequal (Cerebrolysin:placebo = 2:1) randomization was used to assign more patients to the treatment group. SETTINGS: University medical centers and community geriatric hospitals in Korea. PARTICIPANTS: Fifty-three men and women at least 50 years of age admitted to hospitals with mild to moderate AD and otherwise in good health. INTERVENTION: The treatment group (n = 34) received Cerebrolysin (30 mL Cerebrolysin in 100 mL physiologic saline IV) once a day from Monday to Friday for 4 weeks. The control group (n = 19) received placebo. MEASUREMENTS: Primary outcome measures were the Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog) and the Clinical Global Impression of Severity/Change (CGIS/C). Secondary outcome measures included Mini-Mental State Examination (MMSE), Geriatric Depression Scale (GDS), Katz Index of Activities of Daily Living (ADL), and Lawton Instrumental Activities of Daily Living (IADL) Scale. RESULTS: After 4 weeks of treatment, Cerebrolysin-treated patients demonstrated significant improvements in the ADAS-Cog (P = .02), CGIS/C (P = .01), and MMSE (P = .04) compared with placebo-treated patients. Among Cerebrolysin-treated patients, 82%, 62%, and 44% were rated improved on ADAS-Cog, CGIS/C, and MMSE, respectively, compared with 31.6%, 22%, and 17% of placebo-treated patients, respectively. However, there were no significant improvements in the Cerebrolysin group compared with the placebo group on the GDS, ADL, and IADL. There were no dropouts in either groups, with 100% compliance to Cerebrolysin and placebo. Only one patient reported a febrile sensation, which was transient and mild in severity. CONCLUSIONS: This study indicates that Cerebrolysin is a safe drug that improves the cognitive deficits and global function in patients with mild to moderate AD. Long-term efficacy and safety of Cerebrolysin in Alzheimer's patients should be evaluated in the future.

Cyber hacking has been increased every year and it has resulted in severe damages and losses to companies to the extent that it may lose whole business. Recent trend of hacking shows that aims of hacking is to get personal information profile as many as possible, such as ID, residential registration number, password, etc, and to use it for other purposed. The prominent target of hacking is the database of company. This thesis aims to suggest one way data transmission method as one of network partition solutions for the purpose of protecting database where critical information is stored, even when server is attacked and damaged by hacking. The suggested architecture reduced transmission time for data exchange, a problem in existing architectures, for example between web server and Database, to enable real-time safe transmission of even large-scale data.

In The use of cloud computing has increased rapidly in many organizations. General firms have already adopted the cloud computing and successfully applied to ‘smart working’ for security & remote-services. In addition, government organizations have recently introduced this system, which is gaining more users.

WISDOM is an international initiative to deploy large-scale in-silico docking on a public grid infrastructure in an attempt to find potential drugs against neglected or emerging diseases such as Malaria and Avian Flu. Within the framework of the WISDOM initiative, large-scale deployments of in silico docking have been done on production grid infrastructures, demonstrating the relevance of large scale grids for high throughput virtual screening from scientific and grid deployment perspective. However, from the usability point of view, there still seems to be a lot to be done in order to be able to get the grid-enabled large-scale virtual screening approach handier for non-experts of grid computing. To address this issue, we have developed an intuitive and easy-to-use grid-enabled virtual screening tool called Drugscreener-G (DSG), aiming to help scientists in drug discovery including biologists and biochemists to more easily carryout large-scale deployment of molecular docking on grids without having to know details of grid middleware services and tools. With the help of DSG, scientists can easily have access to the PDB database, download and view the 3D structure of target proteins of their interest, launch and manage millions of in-silico docking simulations on the Grid. To facilitate the analysis of docking results, visualization and molecular modeling tools such as Jmol and Chimera have been integrated into DSG as well. The DSG client tool is now being used and tested by biologists in Chonnam National University, one of long-time partners of the WISDOM collaboration. With the help of tools like DSG, their long-time dream of large-scale virtual screening on their own at any time with any help from grid experts is to be made realized in the near future.

This paper related to a method and apparatus for producing the IPv6 mapped EPC code, the electronic product code is used in the RFID (radio frequency identification) system to identify products. But the code is not accessible using Internet address because the EPC code is just an object identifier such as the bar code. This paper suggests the mechanism producing IPv6 mapped EPC address to communicate between objects. This paper is composed of the step to prepare the EPC code from the electronic tag and to assemble the network prefix address with EPC code.