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The darknet (i.e., a set of unused IP addresses) is a very useful solution for observing the global trends of cyber threats and analyzing attack activities on the Internet. Since the darknet is not connected with real systems, in most cases, the incoming packets on the darknet ('the darknet traffic') do not contain a payload. This means that we are unable to get real malware from the darknet traffic. This situation makes it difficult for security experts (e.g., academic researchers, engineers, operators, etc.) to identify whether the source hosts of the darknet traffic are infected by real malware or not. In this paper, we present the overall procedure of the in-depth analysis between the darknet traffic and IDS alerts using real data collected at the Science and Technology Cyber Security Center (S&T CSC) in Korea and provide the detailed in-depth analysis results. The ultimate goal of this paper is to provide practical experience, insight and know-how to security experts so that they are able to identify and trace the root cause of the darknet traffic. The experimental results show that correlation analysis between the darknet traffic and IDS alerts is very useful to discover potential attack hosts, especially internal hosts, and to find out what kinds of malware infected them. [ABSTRACT FROM AUTHOR]

Here we report on the issue of Advanced Persistent Threats (APT), which use malware for the purpose of leaking the data of large corporations and government agencies. APT attacks target systems continuously by utilizing intelligent and complex technologies. To overthrow the elaborate security network of target systems, it conducts an attack after undergoing a pre-reconnaissance phase. An APT attack causes financial loss, information leakage, etc. They can easily bypass the antivirus system of a target system. In this paper, we propose a Multi-Layer Defense System (MLDS) that can defend against APT. This system applies a reinforced defense system by collecting and analyzing log information and various information from devices, by installing the agent on the network appliance, server and end-user. It also discusses how to detect an APT attack when one cannot block the initial intrusion while continuing to conduct other activities. Thus, this system is able to minimize the possibility of initial intrusion and damages of the system by promptly responding through rapid detection of an attack when the target system is attacked. [ABSTRACT FROM AUTHOR]

Water availability is endangering the production, quality, and economic viability of growing wine grapes worldwide. Climate change projections reveal warming and drying trends for the upcoming decades, constraining the sustainability of viticulture. In this context, a great research effort over the last years has been devoted to understanding the effects of water stress on grapevine performance. Moreover, irrigation scheduling and other management practices have been tested in order to alleviate the deleterious effects of water stress on wine production. The current manuscript provides a comprehensive overview of the advances in the research on optimizing water management in vineyards, including the use of novel technologies (modeling, remote sensing). In addition, methods for assessing vine water status are summarized. Moreover, the manuscript will focus on the interactions between grapevine water status and biotic stressors. Finally, future perspectives for research are provided. These include the performance of multifactorial studies accounting for the interrelations between water availability and other stressors, the development of a cost-effective and easy-to-use tool for assessing vine water status, and the study of less-known cultivars under different soil and climate conditions. [ABSTRACT FROM AUTHOR]