SPATIAL MODELING OF THE THREAT OF DAMAGE TO THE PEATLAND ECOSYSTEM IN THE MAINLAND OF BENGKALIS REGENCY, RIAU PROVINCE

Peatlands are the stretch of ecosystem landscape with unique characteristics, both physically, chemically, and biodiversity. Anthropogenic activities in peatland use and disasters pose a threat to the preservation of the peatland ecosystem, which has impacts toward abiotic to the element of biodiversity (biotic). The purpose of this research is to model how the threat of the peatland ecosystem by using spatial data modeling. The method in this research using cloud-based GIS data analysis from Google earth engine, modeling distance parameter to variable modeling of interaction among landscapes on the peatland, and weight sum the value over raster-based spatial layer to determinate the thereat in the peatland ecosystem. The results of this study found zones where hot spots often occur. Modeling with euclidean distance to all modeling variables (except temperature) gives a clear effect on how the threats from each landscape interact with each other. We found that the threat of peatland damage in the high threat class dominates the plantation area reaching 30.9% of the total peatland area, whereas the forest landscape only has a high threat with a percentage of 1.9% and a low threat which the ecosystem is stable and natural reaching over 34.7 %. From this model, we succeeded in bringing up the idea to determine the priority area for policies where need to be done in handling the protection of peatland ecosystems, especially in plantations where the highest percentage of the ecosystem threat is in the high level with integrated peatland management. Keywords: Peatland ecosystem, landscape, threa

Systemic Risk and Vulnerability Analysis of Multi-cloud Environments

With the increasing use of multi-cloud environments, security professionals face challenges in configuration, management, and integration due to uneven security capabilities and features among providers. As a result, a fragmented approach toward security has been observed, leading to new attack vectors and potential vulnerabilities. Other research has focused on single-cloud platforms or specific applications of multi-cloud environments. Therefore, there is a need for a holistic security and vulnerability assessment and defense strategy that applies to multi-cloud platforms. We perform a risk and vulnerability analysis to identify attack vectors from software, hardware, and the network, as well as interoperability security issues in multi-cloud environments. Applying the STRIDE and DREAD threat modeling methods, we present an analysis of the ecosystem across six attack vectors: cloud architecture, APIs, authentication, automation, management differences, and cybersecurity legislation. We quantitatively determine and rank the threats in multi-cloud environments and suggest mitigation strategies.Comment: 27 pages, 9 figure

Data-Driven Threat Analysis for Ensuring Security in Cloud Enabled Systems

Cloud computing offers many benefits including business flexibility, scalability and cost savings but despite these benefits, there exist threats that require adequate attention for secure service delivery. Threats in a cloud-based system need to be considered from a holistic perspective that accounts for data, application, infrastructure and service, which can pose potential risks. Data certainly plays a critical role within the whole ecosystem and organisations should take account of and protect data from any potential threats. Due to the variation of data types, status, and location, understanding the potential security concerns in cloud-based infrastructures is more complex than in a traditional system. The existing threat modeling approaches lack the ability to analyse and prioritise data-related threats. The main contribution of the paper is a novel data-driven threat analysis (d-TM) approach for the cloud-based systems. The main motivation of d-TM is the integration of data from three levels of abstractions, i.e., management, control, and business and three phases, i.e., storage, process and transmittance, within each level. The d-TM provides a systematic flow of attack surface analysis from the user agent to the cloud service provider based on the threat layers in cloud computing. Finally, a cloud-based use case scenario was used to demonstrate the applicability of the proposed approach. The result shows that d-TM revealed four critical threats out of the seven threats based on the identified assets. The threats targeted management and business data in general, while targeting data in process and transit more specifically

Cloud Security : A Review of Recent Threats and Solution Models

The most significant barrier to the wide adoption of cloud services has been attributed to perceived cloud insecurity (Smitha, Anna and Dan, 2012). In an attempt to review this subject, this paper will explore some of the major security threats to the cloud and the security models employed in tackling them. Access control violations, message integrity violations, data leakages, inability to guarantee complete data deletion, code injection, malwares and lack of expertise in cloud technology rank the major threats. The European Union invested €3m in City University London to research into the certification of Cloud security services. This and more recent developments are significant in addressing increasing public concerns regarding the confidentiality, integrity and privacy of data held in cloud environments. Some of the current cloud security models adopted in addressing cloud security threats were – Encryption of all data at storage and during transmission. The Cisco IronPort S-Series web security appliance was among security solutions to solve cloud access control issues. 2-factor Authentication with RSA SecurID and close monitoring appeared to be the most popular solutions to authentication and access control issues in the cloud. Database Active Monitoring, File Active Monitoring, URL Filters and Data Loss Prevention were solutions for detecting and preventing unauthorised data migration into and within clouds. There is yet no guarantee for a complete deletion of data by cloud providers on client requests however; FADE may be a solution (Yang et al., 2012)

An acoustic view of ocean mixing

Knowledge of the parameter K (turbulent diffusivity/"mixing intensity") is a key to understand transport processes of matter and energy in the ocean. Especially the almost vertical component of K across the ocean stratification (diapycnal diffusivity) is vital for research on biogeochemical cycles or greenhouse gas budgets. Recent boost in precision of water velocity data that can be obtained from vessel-mounted acoustic instruments (vmADCP) allows identifying ocean regions of elevated diapycnal diffusivity during research cruises - in high horizontal resolution and without extra ship time needed. This contribution relates acoustic data from two cruises in the Tropical North East Atlantic Oxygen Minimum Zone to simultaneous field observations of diapycnal diffusivity: pointwise measurements by a microstructure profiler as well as one integrative value from a large scale Tracer Release Experiment

A Policy Maker’s Guide to Designing Payments for Ecosystem Services

Over the past five years, there has been increasing interest around the globe in payment schemes for the provision of ecosystem services, such as water purification, carbon sequestration, flood control, etc. Written for an Asian Development Bank project in China, this report provides a user-friendly guide to designing payments for the provision of ecosystem services. Part I explains the different types of ecosystem services, different ways of assessing their value, and why they are traditionally under-protected by law and policy. This is followed by an analysis of when payments for services are a preferable approach to other policy instruments. Part II explains the design issues underlying payments for services. These include identification of the service as well as potential buyers and sellers, the level of service needed, payment timing, payment type, and risk allocation. Part II contains a detailed analysis of the different types of payment mechanisms, ranging from general subsidy and certification to mitigation and offset payments. Part III explores the challenges to designing a payment scheme. These include the ability to monitor service provision, secure property rights, perverse incentives, supporting institutions, and poverty alleviation