BotCloud Detection System

Leveraging cloud services, companies and organizations can significantly improve their efficiency, as well as building novel business opportunities. Cloud computing offers various advantages to companies while having some risks for them too. Advantages offered by service providers are mostly about efficiency and reliability while risks of cloud computing are mostly about security problems. Problems with security of the cloud still demand significant attention in order to tackle the potential problems. Security problems in the cloud as security problems in any area of computing, can not be fully tackled. However creating novel and new solutions can be used by service providers to mitigate the potential threats to a large extent. Looking at the security problem from a very high perspective, there are two focus directions. Security problems that threaten service user’s security and privacy are at one side. On the other hand, security problems that threaten service provider’s security and privacy are on the other side. Both kinds of threats should mostly be detected and mitigated by service providers. Looking a bit closer to the problem, mitigating security problems that target providers can protect both service provider and the user. However, the focus of research community mostly is to provide solutions to protect cloud users. A significant research effort has been put in protecting cloud tenants against external attacks. However, attacks that are originated from elastic, on-demand and legitimate cloud resources should still be considered seriously. The cloud-based botnet or botcloud is one of the prevalent cases of cloud resource misuses. Unfortunately, some of the cloud’s essential characteristics enable criminals to form reliable and low cost botclouds in a short time. In this paper, we present a system that helps to detect distributed infected Virtual Machines (VMs) acting as elements of botclouds. Based on a set of botnet related system level symptoms, our system groups VMs. Grouping VMs helps to separate infected VMs from others and narrows down the target group under inspection. Our system takes advantages of Virtual Machine Introspection (VMI) and data mining techniques.

Heat Demand Forecasting Models’ Development: Use of Data Mining Tools in SQL Server Analysis Services

This thesis introduces heat demand forecasting models which are generated by using data mining algorithms. The forecast spans one full day and this forecast can be used in regulating heat consumption of buildings. For training the data mining models, two years of heat consumption data from a case building and weather measurement data from Finnish Meteorological Institute are used. The thesis utilizes Microsoft SQL Server Analysis Services data mining tools in generating the data mining models and CRISP-DM process framework to implement the research. Results show that the built models can predict heat demand at best with mean average percentage errors of 3.8% for 24-h profile and 5.9% for full day. A deployment model for integrating the generated data mining models into an existing building energy management system is also discussed.

Logistics Cost Optimization of Road Freight Shipments in a Consumer Goods Company

In the industry of the case company, transportation and warehousing costs account for more than 10% of the total cost which is more than on average. A Finnish company has an understanding that by sending larger shipments in parcels, they could save tens of thousands of euros annually in freight costs in Finland’s domestic shipments. To achieve these savings and optimize total logistics cost, company’s interest is to find out which is the cost efficient way of shipping road shipments of certain volumes; in parcel boxes or on pallets, and what should be the split volume determining the shipment type. Distribution center (DC) costs affect this decision and therefore they need to be also evaluated to determine the total logistics cost savings. Main results were achieved by executing activity-based costing-calculations including DC and road freight costs to determine the ideal split volume with which the total logistics cost is optimal. Calculations were done for Finland’s DC, separately for two main road freight destinations, Finland and Sweden, which cover 50% of road shipment spend. Data for calculations was collected both manually and automatically from various internal and external sources, such as the company ERP system and logistics service providers’ (LSP) reporting. DC processes were studied in practice and compared to model processes. Currently used freight rates were compared to existing pricing models and freight service tendering process was evaluated by participating in the process and comparing it to the models based on literature. The results show that the potential savings are not as significant as the company hoped for, mainly because of packing work increasing DC labor cost. Annual savings by setting ideal split volume per country would account for 0,4 % of the warehousing and transportation costs of shipments in scope of this thesis. Split volume should be set separately for each route, mainly because the pricing model for road freight is different in each country. For some routes bigger parcels should be sent but for some routes pallets should be used more. Next step is to do these calculations for remaining routes to determine total savings potential. Other findings show that the processes in the DC are designed well and the company could achieve savings by executing tenders more efficiently. Company should also pay more attention to parcel pricing and packing the shipments accordingly.

Total cost model to compare own and partner manufacturing

Target of this study was to develop a total cost calculation model to compare all costs from manufacturing and logistics from own factories or from partner factories to global distribution centers in a case company. Especially the total cost calculation model was needed to simulate an own factory utilization effect in the total cost calculation context. This study consist of the theoretical literature review and the empirical case study. This study was completed using the constructive research approach. The result of this study was a new total cost calculation model. The new total cost calculation model includes not only all the costs caused by manufacturing and logistics, but also the relevant capital costs. Using the new total cost calculation model, case company is able to complete the total cost calculations taking into account the own factory utilization effect in different volume situations and volume shares between an own factory and a partner factory.

Item-level life-cycle model for maintenance network – from cost to additional value

The importance of industrial maintenance has been emphasized during the last decades; it is no longer a mere cost item, but one of the mainstays of business. Market conditions have worsened lately, investments in production assets have decreased, and at the same time competition has changed from taking place between companies to competition between networks. Companies have focused on their core functions and outsourced support services, like maintenance, above all to decrease costs. This new phenomenon has led to increasing formation of business networks. As a result, a growing need for new kinds of tools for managing these networks effectively has arisen. Maintenance costs are usually a notable part of the life-cycle costs of an item, and it is important to be able to plan the future maintenance operations for the strategic period of the company or for the whole life-cycle period of the item. This thesis introduces an itemlevel life-cycle model (LCM) for industrial maintenance networks. The term item is used as a common definition for a part, a component, a piece of equipment etc. The constructed LCM is a working tool for a maintenance network (consisting of customer companies that buy maintenance services and various supplier companies). Each network member is able to input their own cost and profit data related to the maintenance services of one item. As a result, the model calculates the net present values of maintenance costs and profits and presents them from the points of view of all the network members. The thesis indicates that previous LCMs for calculating maintenance costs have often been very case-specific, suitable only for the item in question, and they have also been constructed for the needs of a single company, without the network perspective. The developed LCM is a proper tool for the decision making of maintenance services in the network environment; it enables analysing the past and making scenarios for the future, and offers choices between alternative maintenance operations. The LCM is also suitable for small companies in building active networks to offer outsourcing services for large companies. The research introduces also a five-step constructing process for designing a life-cycle costing model in the network environment. This five-step designing process defines model components and structure throughout the iteration and exploitation of user feedback. The same method can be followed to develop other models. The thesis contributes to the literature of value and value elements of maintenance services. It examines the value of maintenance services from the perspective of different maintenance network members and presents established value element lists for the customer and the service provider. These value element lists enable making value visible in the maintenance operations of a networked business. The LCM added with value thinking promotes the notion of maintenance from a “cost maker” towards a “value creator”.

Jätevesien puhdistus jätevesialtaissa jäädyttämällä - Kartoitus potentiaalisista sovellutuksista Suomessa

Uusia jäteveden puhdistusprosesseja kartoitetaan Suomessakin esimerkiksi kiristyvien päästömääräyksien vuoksi sekä parempia kustannus- ja energiatehokkuuksia tavoiteltaessa. Jätevesien puhdistus on Suomessa jo nykyään hyvällä tasolla, mutta muun muassa raskasmetallien, torjunta-aineiden, hormonien ja lääkeaineiden pitoisuuksien kasvut jätevesissä asettavat haasteita nykyisin käytössä oleville jäteveden puhdistusmenetelmille, sillä niitä ei ole suunniteltu näiden aineiden talteenottoon ja suurin osa aineista jää veteen. Lisäksi jätevedet halutaan nähdä enemmänkin resurssina kuin jätteenä, josta voidaan ottaa talteen hyödyllisiä komponentteja, kuten suoloja. Alueilla, joissa vuorokauden keskilämpötila pysyttelee edes osan vuodesta pakkasella, veden luonnollista jäätymisprosessia voidaan käyttää hyväksi jäteveden puhdistuksessa. Tässä työssä selvitettiin kiteytymisen teorian ja aikaisempien tutkimusten avulla, millaisten jätevesien puhdistukseen jäädytyskiteytys sopii sekä pohdittiin menetelmän potentiaalisia sovelluskohteita Suomessa. Jäädytyskiteytyksen todettiin olevan turvallinen ja energiatehokas ratkaisu monien koostumukseltaan erilaisien jätevesien puhdistukseen. Menetelmällä voitaneen puhdistaa öljyisiä, orgaanisia ja/tai epäorgaanisia epäpuhtauksia tai raskasmetalleja sisältäviä sekä myrkyllisiä jätevesiä. Olosuhteet prosessille ovat parhaat Pohjois-Suomessa, jossa vuorokauden keskilämpötila pysyttelee nollan alapuolella noin seitsemän kuukautta vuodesta. Etelä-Suomessa vastaava luku on kolme. Menetelmän potentiaalisia sovelluskohteita ovat esimerkiksi kaivosteollisuuden ja kaatopaikkojen jätevedet, joiden puhdistukseen jäädytyskiteytys saattaisi soveltua erinomaisesti. Jäädyttämällä voitaisiin myös puhdistaa tekstiili- ja nahkateollisuuden jätevesiä, sillä niiden sisältämien väriaineiden erottaminen vedestä on perinteisillä jäteveden puhdistusmenetelmillä usein vaikeaa tai jopa mahdotonta. Suolojen kiteyttämiseen vaadittavia korkeampia suolapitoisuuksia todettiin löytyvän lähinnä membraaniprosessien, kuten käänteisosmoosin, rejektivesistä. Sopivimmat eutektiset olosuhteet kiteyttämiseen ovat natriumsulfaatilla, kaliumsulfaatilla ja natriumkarbonaatilla. Veden luonnollisen jäätymisprosessin hyödyntäminen jätevedenpuhdistuksessa on huomionarvoinen idea. Prosessin käyttöönottoa haittaavat esimerkiksi korkeat investointikustannukset, mutta ne tulevat todennäköisesti ajan myötä teknologian kehittyessä laskemaan. Lisäksi monet prosessiin liittyvät käytännön asiat ovat vielä tutkimuksen alla. On myös huomattava, että Suomessakaan lämpötila ei pysyttele koko vuotta pakkasella, joten jäädytyksen rinnalla on oltava jokin toinen prosessi, jolla jätevedet puhdistetaan lämpötilan ollessa nollan yläpuolella.

Benefits of a low-cost one-phase current distortion detection device in appliance supply in low-voltage residential networks

In this bachelor’s thesis are examined the benefits of current distortion detection device application in customer premises low voltage networks. The purpose of this study was to find out if there are benefits for measuring current distortion in low-voltage residential networks. Concluding into who can benefit from measuring the power quality. The research focuses on benefits based on the standardization in Europe and United States of America. In this research, were also given examples of appliances in which current distortion detection device could be used. Along with possible illustration of user interface for the device. The research was conducted as an analysis of the benefits of current distortion detection device in residential low voltage networks. The research was based on literature review. The study was divided to three sections. The first explain the reasons for benefitting from usage of the device and the second portrays the low-cost device, which could detect one-phase current distortion, in theory. The last section discuss of the benefits of usage of current distortion detection device while focusing on the beneficiaries. Based on the result of this research, there are benefits from usage to the current distortion detection device. The main benefitting party of the current distortion detection device was found to be manufactures, as they are held responsible of limiting the current distortion on behalf of consumers. Manufactures could adjust equipment to respond better to the distortion by having access to on-going current distortion in network. The other benefitting party are system operators, who would better locate distortion issues in low-voltage residential network to start prevention of long-term problems caused by current distortion early on.

Improvement of Energy Efficiency in a Gold Mining Industry: Case Study of a Russian Gold Mining Company

The issue of energy efficiency is attracting more and more attention of academia, business and policy makers worldwide due to increasing environmental concerns, depletion of non-renewable energy resources and unstable energy prices. The significant importance of energy efficiency within gold mining industry is justified by considerable energy intensity of this industry as well as by the high share of energy costs in the total operational costs. In the context of increasing industrial energy consumption energy efficiency improvement may provide significant energy savings and reduction of CO2 emission that is highly important in order to contribute to the global goal of sustainability. The purpose of this research is to identify the ways of energy efficiency improvement relevant for a gold mining company. The study implements single holistic case study research strategy focused on a Russian gold mining company. The research involves comprehensive analysis of company’s energy performance including analysis of energy efficiency and energy management practices. This study provides following theoretical and managerial contributions. Firstly, it proposes a methodology for comparative analysis of energy performance of Russian and foreign gold mining companies. Secondly, this study provides comprehensive analysis of main energy efficiency challenges relevant for a Russian gold mining company. Finally, in order to overcome identified challenges this research conceives a guidance for a gold mining company for implementation of energy management system based on the ISO standard.