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Network management is facing a great challenge to analyze and identify encrypted network traffic with specific applications and protocols. A significant number of network users applying different encryption techniques to network applications and services to hide the true nature of the network communication. These challenges attract the network community to improve network security and enhance network service quality. Network managers need novel techniques to cope with the failure and shortcomings of the port-based and payload-based classification methods of encrypted network traffic due to emergent security technologies. Mainly, the famous network hopping mechanisms used to make network traffic unknown and anonymous are VPN (virtual private network) and TOR (Onion Router). This paper presents a novel scheme to unveil encrypted network traffic and easily identify the tunneled and anonymous network traffic. The proposed identification scheme uses the highly desirable deep learning techniques to easily and efficiently identify the anonymous network traffic and extract the Voice over IP (VoIP) and Non VoIP ones within encrypted traffic flows. Finally, the captured traffic has been classified into four different categories, i-e., VPN VoIP, VPN Non-VoIP, TOR VoIP, and TOR Non-VoIP. The experimental results show that our identification engine is extremely robust to VPN and TOR network traffic.

With the increasing world population and accelerated global warming, the main challenge faced today is to develop effective strategies to maintain or increase productivity and prevent environmental deterioration. Rice (Oryza sativa) is the most important agricultural staple for more than half of the world’s population and is critically important for global food security. While rice is essential for ensuring global food security, traditional rice cultivation practised in flooded paddy soils demands unsustainably higher water inputs than other cereal crops, emits a large amount of greenhouse gases, especially CH4, and can accumulate heavy metals such as arsenic (As) in rice grain due to its connection with redox chemistry. In addition, in recent years the renewed interest in application of organic fertilisers, especially as in organically produced rice or amendments e.g. rice straw (produced in huge quantities in intensive cropping systems), can significantly increase CH4 emissions because they add an extra source of carbon substrates for methanogens (Snyder et al., 2009) as well as increase heavy metals in rice grain. Water management practices can alter soil oxygen availability, thereby affecting various processes underlying the production of CH4 and N2O emissions and the uptake of heavy metals such as As in rice grain. The two strategies most often proposed to reduce CH4 emissions are to limit the period of soil submergence (i.e. draining the field) and reduce carbon inputs (through residue management). Alternative irrigation systems such as mid-season drainage and alternate wetting and drying (AWD) irrigation have attracted considerable interest among soil scientists as they can simultaneously save water and reduce CH4 emissions, but their effect on N2O emission and grain yield is less clear. However, irrigation management strategies that reduce yields may simply displace food production and associated GHG emissions to a different region. A deeper understanding of the timing and severity of drainage can shed light on the problem of such a practice. In particular, drainage during the early season (ED) could potentially be effective since the system still contains large amounts of available C from inherent or added soil carbon in the system. Finally, despite promising multiple benefits, the adoption of climate-smart techniques (CSA) by farmers has been observed to be relatively low. Therefore, it is imperative to investigate whether the proposed interventions tested are relevant for farmers and what the determinants are in their choice of adoption of various CSA techniques. Therefore, this thesis was written to understand how alternative water management regimes can be a central force in ensuring multiple agronomic and environmental benefits to help achieve sustainable intensification goals and thus make rice production systems climate-smart.The overall objective of this PhD thesis was to identify and test alternative water-saving management regimes that can reduce GWP from intensified rice farming systems per unit of area as well as per unit of yield, reduce As uptake in grain, and identify the key barriers and determinants of adoption of various available climate-smart technologies for rice ecosystems. The specific research questions of this thesis research were: (i) What impact does the timing and duration of drainage practices (ED, MD, AWD) have on CH4 and N2O emissions? (ii) What is the impact on rice grain yield of the alternative water regime employing ED? (iii) What is the impact of the alternative water regime employing ED on the uptake of important heavy metals (As, Pb, Cd) in rice grain? (iv) How does the water-saving crop establishment with the SWP scheduled irrigation practice affect CH4, N2O and irrigation water use compared with other water-saving alternatives such as AWD? (v) What are the key barriers to the adoption of CSA practices and what are the socio-economic variables that could potentially explain the adoption of CSA techniques in the rice agroecosystem? This thesis contains four research chapters, an introduction (Chapter 1) and a general discussion (Chapter 6).In Chapter 2, a growth chamber experiment was described which tested the effectiveness of seven drainage regimes varying in their timing and duration (combinations of ED and MD) to mitigate CH4 and N2O emissions for 101 days. The results suggested that ED + MD drainage may have the potential to reduce CH4 emissions and yield-scaled GWP by 85-90 % compared with CF, and by 75-77 % compared with MD only. A combination of (short or long) ED drainage and one MD drainage episode was found to be the most effective in mitigating CH4 emissions without negatively affecting yield. In particular, compared with CF, the long early-season drainage treatments LE+SM and LE+LM significantly decreased yield-scaled GWP by 85 % and 87 % respectively. It is concluded that ED+MD drainage could be an effective low-tech option for small-scale farmers to reduce GHG emissions and save water while maintaining yield.Chapter 3 described a field experiment that was set up at the Experimental Station of the International Rice Research Institute (IRRI) in Los Baños in the Philippines to answer Research Questions 1, 2 and 3. This tested the effect of early AWD (e-AWD) vs. continuous flooding (CF) water management practices on grain yields, GHG emissions and grain arsenic levels in a split-plot field experiment with organic fertilisers. The treatments included i) farmyard manure, ii) compost and iii) biogas digestate, alone or in combination with mineral fertiliser. The e-AWD water regime demonstrated no difference in yield for the organic treatments. Yields significantly increased by 5-16 % in the combination treatments. The e-AWD water regime reduced seasonal CH4 emissions by 71-85 % for organic treatments and by 51-76 % for combination treatments; this was linked to a reduction in dissolved organic carbon (DOC) of 15-47 %, thereby reducing methanogenesis. Area and yield-scaled GWP were reduced by 67-83 %. The e-AWD altered soil redox potentials, which resulted in a reduction in grain arsenic and lead concentrations of up to 66 and 73% respectively. Application of organic fertiliser and e-AWD also facilitated the reduction of grain cadmium levels by up to 33 % in organic systems. Structural equation modelling revealed that DOC, redox, ammonium and root biomass were the key traits regulating emissions and maintaining yield.Chapter 4 described the second field experiment, which was conducted during the dry season at the International Rice Research Institute (IRRI) in Los Baños, Laguna in the Philippines. The aim of this study was to evaluate the impact of water-saving irrigation (alternate wetting and drying (AWD) vs. soil water potential (SWP)), contrasting land establishment (puddling vs. reduced tillage) and fertiliser application methods (broadcast vs. liquid fertilisation) on water-use efficiency, GHG emissions and rice yield. The experiment was laid out in a randomised complete block design with eight treatments (all combinations of the three factors) and four replicates. AWD combined with broadcasting fertilisation was superior to SWP in terms of maintaining yield. However, seasonal nitrous oxide (N2O) emissions were significantly reduced by 64 % and 66 % in the Broadcast-SWP and Liquid fertiliser-SWP treatment, respectively compared with corresponding treatments in AWD. The SWP also significantly reduced seasonal methane (CH4) emissions by 34 and 30 % in the broadcast and liquid fertilisation treatments, respectively. Area-scaled GWPs were reduced by 48 % and 54 % in the Broadcast-SWP and Liquid fertiliser-SWP treatments respectively compared with the corresponding treatments in AWD. Compared with AWD, the broadcast and liquid fertilisation in SWP irrigation treatments reduced yield-scaled GWPs by 46 % and 37 % respectively. In terms of suitability and based on yield-scaled GWPs, the treatments can be ordered as follows: Broadcast-SWP < Broadcast-AWD = Liquid fertiliser-SWP < Liquid fertiliser-AWD. Growing-season water use was 15 % lower in the SWP treatments compared with the water-saving AWD. Reduced tillage reduced additional water use during land preparation.Chapter 5 described a farm-household survey in Philippines conducted in collaboration with the International Rice Research Institute (IRRI) to assess how the adoption of climate-smart technologies is dependent on the local socio-economic and biophysical environments, food security and gender. A total of 250 households from five municipalities in the province of Bulacan in Central Luzon were surveyed. The results showed that households in which the household head is young and educated are more likely to adopt climate mitigation techniques. A unit increase in the number of years of schooling would result in a 1.5 % increase in the probability of adoption of mitigation and a 1% increase in the probability of adoption of adaptation techniques, as well as a 0.6 % increase in the probability of adoption of good practices. Male-headed households were more likely to adopt CSA technologies than female-headed households, which is linked to the women’s low resource endowments as well as their more limited contact with extension technicians and research institutes promoting such technologies. Access to extension services increased the probability of adoption of climate mitigation, adaptation and good practices by 19, 17 and 15 % respectively. Adoption of climate mitigation techniques and good practices were most significantly impacted by the connection with research institutes, and resulted in a 21 and 15 % increase in the adoption respectively. Households that are food secure were 11 and 21 % more likely to adopt the good practice and climate change mitigation practices respectively than those that were food insecure. Again, increasing women’s empowerment increased the likelihood of the adoption of climate adaptation practice by 23 %. It was concluded that in order to increase adoption of CSA technologies, government investment in sustainable irrigation and the provision of funds and assistance for support programmes are required, as well as the targeting of young farmers and female farmers in terms of improving their access to various information channels.The general discussion (Chapter 6) addressed the main findings of the research and their implications in a broader context. The thesis demonstrates that early-season drainage employed in combination with midseason drainage or AWD has great potential to reduce the total GHG budget from rice paddy systems without affecting yield. Moreover, the e-AWD water regime was also found to be a very effective strategy to reduce water use and uptake of grain heavy metal such as arsenic (by up to 66 %), lead (by up to 73 %) and cadmium (33 %) in organically fertilised rice. Irrigation scheduling informed by soil water potential (SWP) was found to be a more effective water-saving and GHG mitigation strategy than the AWD practice with the equivalent rice yield, but was limited by the requirement for initial investment and by being knowledge intensive. Non-puddling reduced tillage land preparation instead of puddling can reduce additional water use, labour and energy. Water scarcity, lack of capital and shortage of good quality seeds were found to be the most limiting factors for rice-growing farmers in the Philippines. The gender, age and education of farmers were found to have a significant effect on the adoption of different categories of CSA technologies. Contact with research institutes was found to have a significant impact on the adoption of CSA technologies. To increase adoption, young farmers and female farmers need to be specifically targeted in terms of government support, e.g., with incentives and better access to various information channels. Finally, the perspectives and future research directions section offers inspiration and guidance for further research to future science enthusiasts.

The persistent emergence of new network applications, along with encrypted network communication, has make traffic analysis become a challenging issue in network management and cyberspace security. Currently, virtual private network (VPNs) has become one of the most popular encrypted communication services for bypassing censorship and guarantee remote access to geographically locked services. In this paper, a novel identification scheme of VoIP traffic tunneled through VPN is proposed. We employed a set of Flow Spatio-Temporal Features (FSTF) to six well-known classifiers, including decision trees, K-Nearest Neighbor (KNN), Bagging and Boosting via C4.5, and Multi-Layer perceptron (MLP). The overall accuracy, precision, sensitivity, and F-measure verify that the proposed scheme can effectively distinguish between the VoIP flows and Non-VoIP ones in VPN traffic.

Forest soils are often a sink for atmospheric methane (CH4) and are thus worth special attention in the context of mitigation of greenhouse gases (GHGs) and offset of agricultural GHG emissions at farm to national levels. The litter layer influences the exchange of GHGs between soil and atmosphere; however, most studies focus on the contribution of only soil to the CH4 cycle. In order to improve the inventory of this gas, it is worth investigating how litter influences the exchange of GHGs. Its effect on CH4 uptake may vary in deciduous and coniferous sites due to the different properties of litter. Field experiments were carried out to assess the CH4 uptake capability in 5 different soil types (with and without litter) under different forest types (deciduous, coniferous, and mixed) in Poland. During summer 2019, the highest CH4 uptake (about 2 mg C m-2 day-1) in a variant without litter on the ground was detected in Dystric Cambisol (with the highest C/N ratio) under a 100-year-old coniferous forest and in Albic Luvisol under a 58-year-old mixed forest. The presence of the litter level reduced the CH4 flux in the range of 6-27% in these locations. Methane consumption was the lowest in silty soils (~ 0.4 – 1 mg C m-2 day-1) in the mixed forest and decreased by 13-29% when covered with the litter layer. The negative effect of the litter layer on CH4 absorption was the lowest (~ 3-4%) in sandy Eutric Gleysol under a 75-year-old deciduous forest with 90% of oak and 10% of European hornbeam. The dry conditions in the summer 2019 (with total rainfall 163 mm during the tested months in the studied region) resulted in low moisture in both the litter and soil. However, even low-humidity litter (below 10%) reduced CH4 consumption rates in the measured sites.Research was partially conducted under the project financed by Polish National Centre for Research and Development within of ERA-NET CO-FUND ERA-GAS Programme (ERA-GAS/I/GHG-MANAGE/01/2018).

It has been widely reported that although IPCC methodologies appropriate for national-level accounting purposes, they lack the farm level resolution and holistic approach required for whole-farm systems analysis. The importance of evaluating greenhouse gas (GHG) emissions from crop production, animal farming and agroforestry within the whole farm setting is being realized as more important than evaluating these emissions in isolation. Thus, whole-farm systems modelling is widely used for farm-level analysis. Here we compare three whole-farm models e.g. FarmSim, Holos and IFSM to simulate the effect of management practices on GHG emissions at the whole farm level and evaluate the carbon sequestration and methane oxidation potential of afforestation as a compensation mechanism for the mitigation of farm-level GHG emissions. Ideally, we would also want information on model performance in predicting GHG emissions in future climatic scenarios. Initial results indicate that these models can accurately predict CO2 emissions but the accuracy of these models for predicting methane (CH4) and nitrous oxide (N2O) emissions is quite low. We found that the most prominent drivers for GHG emissions in a whole farm setting were the enteric CH4 from animal farming and N2O emissions from soil management in cropland. Thus, the low prediction accuracy for CH4 and N2O emissions in whole-farm models may introduce substantial errors into GHG inventories and lead to incorrect mitigation recommendations, which necessitates further fine-tuning of these models. Efforts are ongoing to integrate carbon sequestration and soil methane oxidation potential of farm-level afforestation in the whole farm models. There are indications that afforestation can be an effective mitigation strategy. The variation we found in farm system parameters, and the inherent uncertainties associated with emissions of CH4 and N2O can have substantial implications for reported agricultural emissions requiring uncertainty or sensitivity analysis in any modelling approach. Although there is considerable variation among the quality of farm data, boundary assumptions, the emission factors used we suggest that whole-farm systems models are an appropriate tool to develop and measure GHG mitigation strategies for the European farmed landscape.

Flooded rice production is crucial to global food security, but there are associated environmental concerns. In particular, it is a significant source of methane (CH4) and nitrous oxide (N2O) emissions and a large consumer of water resources, while arsenic levels in the grain are a serious health concern. There is also a tendency to use more organic fertilisers to close nutrient cycles, posing a threat of even higher GHG emissions and grain arsenic levels. It has been shown that alternate wetting and drying (AWD) water management reduces both water use and GHG emissions, but success at maintaining yields varies. This study tested the effect of early AWD (e-AWD) versus continuous flooding (CF) water management practices on grain yields, GHG emissions and grain arsenic levels in a split-plot field experiment with organic fertilisers under organic management. The treatments included: i) farmyard manure, ii) compost, and iii) biogas digestate, alone or in combination with mineral fertiliser. The e-AWD water regime showed no difference in yield for the organic treatments. Yields significantly increased by 5–16 % in the combination treatments. Root biomass and length increased in the e-AWD treatments up to 72 and 41 %, respectively. The e-AWD water regime reduced seasonal CH4 emissions by 71–85 % for organic treatments and by 51–76 % for combination treatments; this was linked to a 15–47 % reduction in dissolved organic carbon (DOC), thereby reducing methanogenesis. N2O emissions increased by 23–305 % but accounted for

Rice production systems are the largest anthropogenic wetlands on earth and feed more than half of the world's population. However, they are also a major source of global anthropogenic greenhouse gas (GHG) emissions. Several agronomic strategies have been proposed to improve water-use efficiency and reduce GHG emissions. The aim of this study was to evaluate the impact of water-saving irrigation (alternate wetting and drying (AWD) vs. soil water potential (SWP)), contrasting land establishment (puddling vs. reduced tillage) and fertiliser application methods (broadcast vs. liquid fertilisation) on water-use efficiency, GHG emissions and rice yield. The experiment was laid out in a randomised complete block design with eight treatments (all combinations of the three factors) and four replicates. AWD combined with broadcasting fertilisation was superior to SWP in terms of maintaining yield. However, seasonal nitrous oxide (N2O) emissions were significantly reduced by 64% and 66% in the Broadcast-SWP and Liquid fertiliser-SWP treatments, respectively, compared to corresponding treatments in AWD. The SWP also significantly reduced seasonal methane (CH4) emissions by 34 and 30% in the broadcast and liquid fertilisation treatments, respectively. Area-scaled GWPs were reduced by 48% and 54% in Broadcast-SWP and Liquid fertiliser-SWP treatments respectively compared to the corresponding treatments in AWD. Compared to AWD, the broadcast and liquid fertilisation in SWP irrigation treatments reduced yield-scaled GWPs by 46% and 37%, respectively. In terms of suitability, based on yield-scaled GWPs, the treatments can be ordered as follows: Broadcast-SWP < Broadcast-AWD = Liquid fertiliser-SWP < Liquid fertiliser-AWD. Growing-season water use was 15% lower in the SWP treatments compared with the water-saving AWD. Reduced tillage reduced additional water use during land preparation. The conclusions of this study are that improved water management and timely coordination of N fertiliser with crop demand can reduce water use, N loss via N2O emissions, and CH4 emissions.

Global rice production systems face two opposing challenges: the need to increase production to accommodate the world's growing population while simultaneously reducing greenhouse gas (GHG) emissions. Adaptations to drainage regimes are one of the most promising options for methane mitigation in rice production. Whereas several studies have focused on mid-season drainage (MD) to mitigate GHG emissions, early-season drainage (ED) varying in timing and duration has not been extensively studied. However, such ED periods could potentially be very effective since initial available C levels (and thereby the potential for methanogenesis) can be very high in paddy systems with rice straw incorporation. This study tested the effectiveness of seven drainage regimes varying in their timing and duration (combinations of ED and MD) to mitigate CH4 and N2O emissions in a 101-day growth chamber experiment. Emissions were considerably reduced by early-season drainage compared to both conventional continuous flooding (CF) and the MD drainage regime. The results suggest that ED + MD drainage may have the potential to reduce CH4 emissions and yield-scaled GWP by 85–90% compared to CF and by 75–77% compared to MD only. A combination of (short or long) ED drainage and one MD drainage episode was found to be the most effective in mitigating CH4 emissions without negatively affecting yield. In particular, compared with CF, the long early-season drainage treatments LE + SM and LE + LM significantly (p < 0.01) decreased yield-scaled GWP by 85% and 87% respectively. This was associated with carbon being stabilised early in the season, thereby reducing available C for methanogenesis. Overall N2O emissions were small and not significantly affected by ED. It is concluded that ED + MD drainage might be an effective low-tech option for small-scale farmers to reduce GHG emissions and save water while maintaining yield.

S-box plays an imperative role in designing a cryptographically strong block cipher. Designing S-box based on chaos has attracted lots of attentions because of its distinct characteristics relevant to cryptography. In this paper, a 4D-4wing hyperchaotic system is investigated. Its sophisticated nonlinear behaviors are used to generate two pseudorandom 8-bit integer sequences, which further drive iterative two-position swap on the identical map on GF(28). According to the indicator of typical evaluation criteria including nonlinearity, differential uniformity, strict avalanche criterion, output bits independence criterion and bijective property, the preferred S-box is obtained from all those batch-generated ones. The comparison with the state-of-the-art chaos-based schemes shows that the obtained S-box achieves better cryptographical performance.