Search results for: intrusion%20detection%20system

Authors: Adel Sabry Eesa, Adnan Mohsin Abdulazeez Brifcani, Zeynep Orman

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Feature selection has been used in many fields such as classification, data mining and object recognition and proven to be effective for removing irrelevant and redundant features from the original data set. In this paper, a new design of distributed intrusion detection system using a combination feature selection model based on bees and decision tree. Bees algorithm is used as the search strategy to find the optimal subset of features, whereas decision tree is used as a judgment for the selected features. Both the produced features and the generated rules are used by Decision Making Mobile Agent to decide whether there is an attack or not in the networks. Decision Making Mobile Agent will migrate through the networks, moving from node to another, if it found that there is an attack on one of the nodes, it then alerts the user through User Interface Agent or takes some action through Action Mobile Agent. The KDD Cup 99 data set is used to test the effectiveness of the proposed system. The results show that even if only four features are used, the proposed system gives a better performance when it is compared with the obtained results using all 41 features.

Keywords: distributed intrusion detection system, mobile agent, feature selection, bees algorithm, decision tree

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Authors: Antoifi Abdoulhalik, Ashraf Ahmed

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Saltwater intrusion (SWI) in coastal aquifers has become a growing threat for many countries around the world. While various control measures have been suggested to mitigate SWI, the construction of subsurface physical barriers remains one of the most effective solutions for this problem. In this work, we used laboratory experiments and numerical simulations to investigate the effectiveness of subsurface dams in heterogeneous layered coastal aquifer with different layering patterns. Four different cases were investigated, including a homogeneous (case H), and three heterogeneous cases in which a low permeability (K) layer was set in the top part of the system (case LH), in the middle part of the system (case HLH) and the bottom part of the system (case HL). Automated image analysis technique was implemented to quantify the main SWI parameters under high spatial and temporal resolution. The method also provides transient salt concentration maps, allowing for the first time clear visualization of the spillage of saline water over the dam (advancing wedge condition) as well as the flushing of residual saline water from the freshwater area (receding wedge condition). The SEAWAT code was adopted for the numerical simulations. The results show that the presence of an overlying layer of low permeability enhanced the ability of the dam to retain the saline water. In such conditions, the rate of saline water spillage and inland extension may considerably be reduced. Conversely, the presence of an underlying low K layer led to a faster increase of saltwater volume on the seaward side of the wall, therefore considerably facilitating the spillage. The results showed that a complete removal of the residual saline water eventually occurred in all the investigated scenarios, with a rate of removal strongly affected by the hydraulic conductivity of the lower part of the aquifer. The data showed that the addition of the underlying low K layer in case HL caused the complete flushing to be almost twice longer than in the homogeneous scenario.

Keywords: heterogeneous coastal aquifers, laboratory experiments, physical barriers, seawater intrusion control

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Authors: Zhiwen Pan, Jesus Pacheco, Salim Hariri, Yiqiang Chen, Bozhi Liu

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The Internet of Things (IoT) will lead to the development of advanced Smart Home services that are pervasive, cost-effective, and can be accessed by home occupants from anywhere and at any time. However, advanced smart home applications will introduce grand security challenges due to the increase in the attack surface. Current approaches do not handle cybersecurity from a holistic point of view; hence, a systematic cybersecurity mechanism needs to be adopted when designing smart home applications. In this paper, we present a generic intrusion detection methodology to detect and mitigate the anomaly behaviors happened in Smart Home Systems (SHS). By utilizing our Smart Home Context Data Structure, the heterogeneous information and services acquired from SHS are mapped in context attributes which can describe the context of smart home operation precisely and accurately. Runtime models for describing usage patterns of home assets are developed based on characterization functions. A threat-aware action management methodology, used to efficiently mitigate anomaly behaviors, is proposed at the end. Our preliminary experimental results show that our methodology can be used to detect and mitigate known and unknown threats, as well as to protect SHS premises and services.

Keywords: Internet of Things, network security, context awareness, intrusion detection

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Authors: Ali Ait Boughrous, Said Benyoussef, Hossain El Ouarghi, Moulay Abdelazize Aboulhassan, Samah Aitbnichou, Said Benguamra

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The Rhiss-Nekor aquifer represents a primary water source for the central Rif region. Many operating structures were built for irrigation and drinking water supply. Because of the vulnerability of this aquifer, a thorough knowledge of the environment is needed to evaluate and protect resources. This work aims at the quality assessment of the water table of the plain Ghiss-Nekor and determination of pollution sources in order to establish a map of the web. The plain-Rhiss Nekor, with an area of 100 km2, is located on the Mediterranean coast of Morocco. It has a particular geological structure resulting from the opening of a graben at the end of the Tertiary, which is filled by the accumulation of hundreds of meters of sediment, generating considerable heterogeneity in deposits. This heterogeneity gives various hydrodynamic properties within the aquifer of the plain. The analysis of the water quality of twenty water points, well distributed over the plain, showed high natural salinity linked to the geological nature of the area. This salinity increases in the littoral area by the seawater intrusion phenomenon. This is accentuated by overexploitation of the ground water due to the growing demand. Some wells, located inland, are characterized by organic pollution caused by wastewater seepage from septic tanks and lost wells widespread in the region.

Keywords: anthropogenic factors, groundwater quality, marine intrusion, Rhiss-Nekor aquifer

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Authors: Charuvan Kasemsap

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This research was studied in Bangnampriao District, Chachernsao Province, Thailand. The primary data relating to flooding, drought, and saline intrusion problem on agriculture were collected by surveying, focus group, and in-depth interview with agricultural officers, technical officers of irrigation department, and local government leader of Bangnampriao District. The likelihood and consequence of risk were determined the risk index by risk assessment matrix. In addition, the risk index and the total coping capacity scores were investigated the vulnerability index by vulnerability matrix. It was found that the high-risk drought and saline intrusion was dramatically along Bang Pakong River owing to the end destination of Chao Phraya Irrigation system of Central Thailand. This leads yearly the damage of rice paddy, mango tree, orchard, and fish pond. Therefore, some agriculture avoids rice growing during January to May, and also pumps fresh water from a canal into individual storage pond. However, Bangnampriao District will be strongly affected by the impacts of climate change. Monthly precipitations are expected to decrease in number; dry seasons are expected to be more in number and longer in duration. Thus, the risk and vulnerability of agriculture are also increasing. Adaptation strategies need to be put in place in order to enhance the resilience of the agriculture.

Keywords: agriculture, bangnampriao, climate change, risk assessment

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Authors: Elli Karampela

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In Specters of Marx (1993), Jacques Derrida refers to the ghost as an Other presence that occupies the space of the self and emanates from there, haunting in its shadowy pastness and threatening/striving to break free. In times of change, ghosts both reflect the dissolution of set principles and voice traumas of the past that create a sense of fear and instability. This paper observes the way female ghosts create connections with the living in the poetry of Joanna Baillie and Anne Bannerman, both integral, albeit under-researched in different ways, writers of the English Romantic period working in the aftermath of the French Revolution. Especially at the beginning of the nineteenth century, when ghost narratives were devoured by readers and enjoyed as stories that re-awakened sensation in times of revolution, there was at the same time fear of intrusion by terror’s unruly forces that threatened to turn the readers restless. The ghost was particularly dangerous because it was associated with memory and the intrusion of past trauma in the here and now. As will be seen, both Baillie and Bannerman explore the idea of the female ghost’s ‘return’ (a Freudian term that will be approached) which breaks both time and space boundaries to raise the suppressed female voice, threaten stability, and correct wrongs. As a result, the varied manifestations of female ghosts render Baillie and Bannerman active in the contemporary discourse about human rights and the reclamation of the agency.

Keywords: poetry, romanticism, spectrality, trauma, women

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Authors: Muhammad Ali

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Cyber-attacks and anomaly detection on the Internet of Things (IoT) infrastructure is emerging concern in the domain of data-driven intrusion. Rapidly increasing IoT risk is now making headlines around the world. denial of service, malicious control, data type probing, malicious operation, DDos, scan, spying, and wrong setup are attacks and anomalies that can affect an IoT system failure. Everyone talks about cyber security, connectivity, smart devices, and real-time data extraction. IoT devices expose a wide variety of new cyber security attack vectors in network traffic. For further than IoT development, and mainly for smart and IoT applications, there is a necessity for intelligent processing and analysis of data. So, our approach is too secure. We train several machine learning models that have been compared to accurately predicting attacks and anomalies on IoT systems, considering IoT applications, with ANOVA-based feature selection with fewer prediction models to evaluate network traffic to help prevent IoT devices. The machine learning (ML) algorithms that have been used here are KNN, SVM, NB, D.T., and R.F., with the most satisfactory test accuracy with fast detection. The evaluation of ML metrics includes precision, recall, F1 score, FPR, NPV, G.M., MCC, and AUC & ROC. The Random Forest algorithm achieved the best results with less prediction time, with an accuracy of 99.98%.

Keywords: machine learning, analysis of variance, Internet of Thing, network security, intrusion detection

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Authors: Mehrshad Khosraviani, Faramarz Abbaspour Leyl Abadi

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The fundamental component of the computer network of modern information society will be considered. These networks are connected to the network of the internet generally. Due to the fact that the primary purpose of the Internet is not designed for, in recent decades, none of these networks in many of the attacks has been very important. Today, for the provision of security, different security tools and systems, including intrusion detection systems are used in the network. A common diagnosis system based on artificial immunity, the designer, the Adhasaz Foundation has been evaluated. The idea of using artificial safety methods in the diagnosis of abnormalities in computer networks it has been stimulated in the direction of their specificity, there are safety systems are similar to the common needs of m, that is non-diagnostic. For example, such methods can be used to detect any abnormalities, a variety of attacks, being memory, learning ability, and Khodtnzimi method of artificial immune algorithm pointed out. Diagnosis of the common system of education offered in this paper using only the normal samples is required for network and any additional data about the type of attacks is not. In the proposed system of positive selection and negative selection processes, selection of samples to create a distinction between the colony of normal attack is used. Copa real data collection on the evaluation of ij indicates the proposed system in the false alarm rate is often low compared to other ir methods and the detection rate is in the variations.

Keywords: artificial immune system, abnormality detection, intrusion detection, computer networks

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Authors: Syed Ahsan, Saleh Alshomrani, Ishtiaq Rasool, Ali Hassan

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In this oral presentation, we will provide an overview of the technical and semantic architecture of a desert border security and critical infrastructure protection security system. Modern border security systems are designed to reduce the dependability and intrusion of human operators. To achieve this, different types of sensors are use along with video surveillance technologies. Application of these technologies in a harsh desert environment of Saudi Arabia poses unique challenges. Environmental and geographical factors including high temperatures, desert storms, temperature variations and remoteness adversely affect the reliability of surveillance systems. To successfully implement a reliable, effective system in a harsh desert environment, the following must be achieved: i) Selection of technology including sensors, video cameras, and communication infrastructure that suit desert environments. ii) Reduced power consumption and efficient usage of equipment to increase the battery life of the equipment. iii) A reliable and robust communication network with efficient usage of bandwidth. Also, to reduce the expert bottleneck, an ontology-based intelligent information systems needs to be developed. Domain knowledge unique and peculiar to Saudi Arabia needs to be formalized to develop an expert system that can detect abnormal activities and any intrusion.

Keywords: border security, sensors, abnormal activity detection, ontologies

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Authors: Vivek Mahadev, Manoj Kumar, Neelu Mathur, Brahm Dutt Pandey

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Perimeter guarding and protection of critical installations require prompt intrusion detection and assessment to take effective countermeasures. Currently, visual and electronic surveillance are the primary methods used for perimeter guarding. These methods can be costly and complicated, requiring careful planning according to the location and terrain. Moreover, these methods often struggle to detect stealthy and camouflaged insurgents. The object of the present work is to devise a surveillance technique using seismic sensors that overcomes the limitations of existing systems. The aim is to improve intrusion detection, assessment, and characterization by utilizing seismic sensors. Most of the similar systems have only two types of intrusion detection capability viz., human or vehicle. In our work we could even categorize further to identify types of intrusion activity such as walking, running, group walking, fence jumping, tunnel digging and vehicular movements. A virtual fence of 60 meters at GCNEP, Bahadurgarh, Haryana, India, was created by installing four underground geophones at a distance of 15 meters each. The signals received from these geophones are then processed to find unique seismic signatures called features. Various feature optimization and selection methodologies, such as LightGBM, Boruta, Random Forest, Logistics, Recursive Feature Elimination, Chi-2 and Pearson Ratio were used to identify the best features for training the machine learning models. The trained models were developed using algorithms such as supervised support vector machine (SVM) classifier, kNN, Decision Tree, Logistic Regression, Naïve Bayes, and Artificial Neural Networks. These models were then used to predict the category of events, employing weighted ensemble voting to analyze and combine their results. The models were trained with 1940 training events and results were evaluated with 831 test events. It was observed that using the weighted ensemble voting increased the efficiency of predictions. In this study we successfully developed and deployed the virtual fence using geophones. Since these sensors are passive, do not radiate any energy and are installed underground, it is impossible for intruders to locate and nullify them. Their flexibility, quick and easy installation, low costs, hidden deployment and unattended surveillance make such systems especially suitable for critical installations and remote facilities with difficult terrain. This work demonstrates the potential of utilizing seismic sensors for creating better perimeter guarding and protection systems using multiple machine learning models in weighted ensemble voting. In this study the virtual fence achieved an intruder detection efficiency of over 97%.

Keywords: geophone, seismic perimeter surveillance, machine learning, weighted ensemble method

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Authors: Yousef Farhaoui

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An IDS is a tool which is used to improve the level of security.In this paper we present different architectures of IDS. We will also discuss measures that define the effectiveness of IDS and the very recent works of standardization and homogenization of IDS. At the end, we propose a new model of IDS called BiIDS (IDS Based on the two principles of detection).

Keywords: intrusion detection, architectures, characteristic, tools, security

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Authors: Adamu Abdullahi, On Francisca, Saidu Isah Rambo, G. N. Obunadike, D. T. Chinyio

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The paper discusses the potential threat of Denial of Service (DoS) attacks in the Internet of Things (IoT) networks on constrained application protocols (CoAP). As billions of IoT devices are expected to be connected to the internet in the coming years, the security of these devices is vulnerable to attacks, disrupting their functioning. This research aims to tackle this issue by applying mixed methods of qualitative and quantitative for feature selection, extraction, and cluster algorithms to detect DoS attacks in the Constrained Application Protocol (CoAP) using the Machine Learning Algorithm (MLA). The main objective of the research is to enhance the security scheme for CoAP in the IoT environment by analyzing the nature of DoS attacks and identifying a new set of features for detecting them in the IoT network environment. The aim is to demonstrate the effectiveness of the MLA in detecting DoS attacks and compare it with conventional intrusion detection systems for securing the CoAP in the IoT environment. Findings: The research identifies the appropriate node to detect DoS attacks in the IoT network environment and demonstrates how to detect the attacks through the MLA. The accuracy detection in both classification and network simulation environments shows that the k-means algorithm scored the highest percentage in the training and testing of the evaluation. The network simulation platform also achieved the highest percentage of 99.93% in overall accuracy. This work reviews conventional intrusion detection systems for securing the CoAP in the IoT environment. The DoS security issues associated with the CoAP are discussed.

Keywords: algorithm, CoAP, DoS, IoT, machine learning

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Authors: Faiza Babur Khan, Sohail Asghar

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With an emergence of distributed environment, cloud computing is proving to be the most stimulating computing paradigm shift in computer technology, resulting in spectacular expansion in IT industry. Many companies have augmented their technical infrastructure by adopting cloud resource sharing architecture. Cloud computing has opened doors to unlimited opportunities from application to platform availability, expandable storage and provision of computing environment. However, from a security viewpoint, an added risk level is introduced from clouds, weakening the protection mechanisms, and hardening the availability of privacy, data security and on demand service. Issues of trust, confidentiality, and integrity are elevated due to multitenant resource sharing architecture of cloud. Trust or reliability of cloud refers to its capability of providing the needed services precisely and unfailingly. Confidentiality is the ability of the architecture to ensure authorization of the relevant party to access its private data. It also guarantees integrity to protect the data from being fabricated by an unauthorized user. So in order to assure provision of secured cloud, a roadmap or model is obligatory to analyze a security problem, design mitigation strategies, and evaluate solutions. The aim of the paper is twofold; first to enlighten the factors which make cloud security critical along with alleviation strategies and secondly to propose an intrusion detection model that identifies the attackers in a preventive way using machine learning Random Forest classifier with an accuracy of 99.8%. This model uses less number of features. A comparison with other classifiers is also presented.

Keywords: cloud security, threats, machine learning, random forest, classification

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Authors: Bambang Antoro, Lasito Soebari, Geoffrey de Jong, Fernandy Meiriyanto, Michael Siahaan, Eko Wibowo, Pormando Silalahi, Ruswanto, Adi Budirumantyo

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The Ertsberg East Skarn System (EESS) is located in the Ertsberg Mining District, Papua, Indonesia. EESS is a sub-vertical zone of copper-gold mineralization hosted in both diorite (vein-style mineralization) and skarn (disseminated and vein style mineralization). Deep Mill Level Zone (DMLZ) is a mining zone in the lower part of East Ertsberg Skarn System (EESS) that product copper and gold. The Deep Mill Level Zone deposit is located below the Deep Ore Zone deposit between the 3125m to 2590m elevation, measures roughly 1,200m in length and is between 350 and 500m in width. DMLZ planned start mined on Q2-2015, being mined at an ore extraction rate about 60,000 tpd by the block cave mine method (the block cave contain 516 Mt). Mineralization and associated hydrothermal alteration in the DMLZ is hosted and enclosed by a large stock (The Main Ertsberg Intrusion) that is barren on all sides and above the DMLZ. Late porphyry dikes that cut through the Main Ertsberg Intrusion are spatially associated with the center of the DMLZ hydrothermal system. DMLZ orebody hosted in diorite and skarn, both dominantly by vein style mineralization. Percentage Material Mined at DMLZ compare with current Reserves are diorite 46% (with 0.46% Cu; 0.56 ppm Au; and 0.83% EqCu); Skarn is 39% (with 1.4% Cu; 0.95 ppm Au; and 2.05% EqCu); Hornfels is 8% (with 0.84% Cu; 0.82 ppm Au; and 1.39% EqCu); and Marble 7 % possible mined waste. Correlation between Ertsberg intrusion, major structure, and vein style mineralization is important to determine characteristic orebody in DMLZ Mine. Generally Deep Mill Level Zone has 2 type of vein filling mineralization from both hosted (diorite and skarn), in diorite hosted the vein system filled by chalcopyrite-bornite-quartz and pyrite, in skarn hosted the vein filled by chalcopyrite-bornite-pyrite and magnetite without quartz. Based on orientation the stockwork vein at diorite hosted and shallow vein in skarn hosted was generally NW-SE trending and NE-SW trending with shallow-moderate dipping. Deep Mill Level Zone control by two main major faults, geologist founded and verified local structure between major structure with NW-SE trending and NE-SW trending with characteristics slickenside, shearing, gauge, water-gas channel, and some has been re-healed.

Keywords: copper-gold, DMLZ, skarn, structure

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Authors: Khawla Askri, Mohamed Haythem Msaddek, AbdelAziz Sebei

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Climate change combined with the increase in anthropogenic activities will affect coastal groundwater systems around the world and, more particularly, the Cap Bon region in the North East of Tunisia. This study aims to study the impact of climate change and human stress on the salinization and quantification of groundwater in the Wadi Chiba watershed. In this regard, a hydro-climatological study and a hydrogeological study were carried out based on the characterization of the aquifer system of the eastern coast at the level of the watershed of Wadi Chiba in order to seek to identify, first of all, the degradation of the state of the aquifer on the quantitative level by the study of the piezometric and its evolution over time. Secondly, we sought to identify the degradation of the state of the aquifer qualitatively by using the geochemical method, in particular the major elements, to assess the mineralization of the aquifer water and understand its hydrogeochemical functioning. The study of the Na + / Cl- and Ca2 + / Mg2 + chemical relationships confirmed the presence of a marine intrusion downstream of the Wadi Chiba watershed northeast of Cap-Bon accompanied by a piezometric depression. For this purpose, we proceeded to: 1) Mapping of both piezometric data and salinity. 2) The interpretation of the mapping results. 3)Identification of the origin of the localized deterioration in the quality of the aquifer water. Finally, the analysis of the results showed that the scarcity of water is already forcing human actions in the Chiba watershed due to the irrigation of agricultural lands and the overexploitation of the water table in the study area.

Keywords: climate change, human activities, water table, Wadi Chiba watershed, piezometric depression, marine intrusion

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Authors: Afnan Al-Romi, Iman Al-Momani

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The urge of applying the Software Engineering (SE) processes is both of vital importance and a key feature in critical, complex large-scale systems, for example, safety systems, security service systems, and network systems. Inevitably, associated with this are risks, such as system vulnerabilities and security threats. The probability of those risks increases in unsecured environments, such as wireless networks in general and in Wireless Sensor Networks (WSNs) in particular. WSN is a self-organizing network of sensor nodes connected by wireless links. WSNs consist of hundreds to thousands of low-power, low-cost, multi-function sensor nodes that are small in size and communicate over short-ranges. The distribution of sensor nodes in an open environment that could be unattended in addition to the resource constraints in terms of processing, storage and power, make such networks in stringent limitations such as lifetime (i.e. period of operation) and security. The importance of WSN applications that could be found in many militaries and civilian aspects has drawn the attention of many researchers to consider its security. To address this important issue and overcome one of the main challenges of WSNs, security solution systems have been developed by researchers. Those solutions are software-based network Intrusion Detection Systems (IDSs). However, it has been witnessed, that those developed IDSs are neither secure enough nor accurate to detect all malicious behaviours of attacks. Thus, the problem is the lack of coverage of all malicious behaviours in proposed IDSs, leading to unpleasant results, such as delays in the detection process, low detection accuracy, or even worse, leading to detection failure, as illustrated in the previous studies. Also, another problem is energy consumption in WSNs caused by IDS. So, in other words, not all requirements are implemented then traced. Moreover, neither all requirements are identified nor satisfied, as for some requirements have been compromised. The drawbacks in the current IDS are due to not following structured software development processes by researches and developers when developing IDS. Consequently, they resulted in inadequate requirement management, process, validation, and verification of requirements quality. Unfortunately, WSN and SE research communities have been mostly impermeable to each other. Integrating SE and WSNs is a real subject that will be expanded as technology evolves and spreads in industrial applications. Therefore, this paper will study the importance of Requirement Engineering when developing IDSs. Also, it will study a set of existed IDSs and illustrate the absence of Requirement Engineering and its effect. Then conclusions are drawn in regard of applying requirement engineering to systems to deliver the required functionalities, with respect to operational constraints, within an acceptable level of performance, accuracy and reliability.

Keywords: software engineering, requirement engineering, Intrusion Detection System, IDS, Wireless Sensor Networks, WSN

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Authors: Debashis Nath

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Drawn from multiple reanalysis datasets, an increasing trend and westward shift in the number of Potential Vorticity (PV) intrusion events over the Pacific are evident. The increased frequency can be linked to a long-term trend in upper tropospheric (UT, 200 hPa) equatorial westerly wind and subtropical jets (STJ) during boreal winter to spring. These may be resulting from anomalous warming and cooling over the western Pacific warm pool and the tropical eastern Pacific, respectively. The intrusions brought dry and ozone rich air of stratospheric origin deep into the tropics. In the tropical UT, interannual ozone variability is mainly related to convection associated with El Niño/Southern Oscillation. Zonal mean stratospheric overturning circulation organizes the transport of ozone rich air poleward and downward to the high and midlatitudes leading there to higher ozone concentration. In addition to these well described mechanisms, we observe a long-term increasing trend in ozone flux over the northern hemispheric outer tropical (10–25°N) central Pacific that results from equatorward transport and downward mixing from the midlatitude UT and lower stratosphere (LS) during PV intrusions. This increase in tropospheric ozone flux over the Pacific Ocean may affect the radiative processes and changes the budget of atmospheric hydroxyl radicals. The results demonstrate a long-term increase in outer tropical Pacific PV intrusions linked with the strengthening of the upper tropospheric equatorial westerlies and weakening of the STJ. Zonal variation in SST, characterized by gradual warming in the western Pacific–warm pool and cooling in the central–eastern Pacific, is associated with the strengthening of the Pacific Walker circulation. In the Western Pacific enhanced convective activity leads to precipitation, and the latent heat released in the process strengthens the Pacific Walker circulation. However, it is linked with the trend in global mean temperature, which is related to the emerging anthropogenic greenhouse signal and negative phase of PDO. On the other hand, the central-eastern Pacific cooling trend is linked to the weakening of the central–eastern Pacific Hadley circulation. It suppresses the convective activity due to sinking air motion and imports less angular momentum to the STJ leading to a weakened STJ. While, more PV intrusions result from this weaker STJ on its equatorward side; significantly increase the stratosphere-troposphere exchange processes on the longer timescale. This plays an important role in determining the atmospheric composition, particularly of tropospheric ozone, in the northern outer tropical central Pacific. It may lead to more ozone of stratospheric origin in the LT and even in the marine boundary, which may act as harmful pollutants and affect the radiative processes by changing the global budgets of atmospheric hydroxyl radicals.

Keywords: PV intrusion, westerly duct, ozone, Central Pacific

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Authors: M. Schapira, S. Françoise, F. Maheux, O. Pierre-Duplessix, E. Rabiller, B. Simon, R. Le Gendre

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Pico- and nano-phytoplankton are abundant and ecologically critical components of the autotrophic communities in the pelagic realm. While the role of physical forcing related to tidal cycle, water mass intrusion, nutrient availability, mixing and stratification on microphytoplankton blooms have been widely investigated, these are often overlooked for pico- and nano-phytoplankton especially in estuarine waters. This study investigates changes in abundances and community composition of pico- and nano-phytoplankton under different estuarine tidal conditions in the mouth of the Seine River in relation to nutrient availability, water column stratification and spatially localized currents. Samples were collected each day at high tide, over spring tide to neap tide cycle, from 21 stations homogeneously distributed in the Seine river month in May 2011. Vertical profiles of temperature, salinity and fluorescence were realized at each sampling station. Sub-surface water samples (i.e. 1 m depth) were collected for nutrients (i.e. N, P and Si), phytoplankton biomass (i.e. Chl a) and pico- and nano-phytoplankton enumeration and identification. Pico- and nano-phytoplankton populations were identified and quantified using flow cytometry. Total abundances tend to decrease from spring tide to neap tide. Samples were characterized by high abundances of Synechococcus and Cryptophyceae. The composition of the pico- and nano-phytoplankton varied greatly under the different estuarine tidal conditions. Moreover, at the scale of the river mouth, the pico- and nano-phytoplankton population exhibited patchy distribution patterns that were closely controlled by water mass intrusion from the Sea, freshwater inputs from the Seine River and the geomorphology of the river mouth. This study highlights the importance of physical forcing to the community composition of pico- and nano-phytoplankton that may be critical for the structure of the pelagic food webs in estuarine and adjacent coastal seas.

Keywords: nanophytoplancton, picophytoplankton, physical forcing, river mouth, tidal cycle

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Authors: Radmila Maksimovic, Sonja Ketin, Rade Biocanin, Jelena Maksimovic

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The abnormal conditions of life and work genetic factors often play a major role in incidence of diabetes-diabetes, heart disease and vascular disease, jaundice, and post traumatic stress. Trauma and post traumatic stress are most common in the displaced persons,and the focus of this paper is to shed light on this issue in former Yugoslavia, Yugoslavia and now in our country. This is caused by increased beta-cell sensitivity to viruses, the development of autoimmune antibodies against its own pancreascells, degenerative changes in cells that r esult in change of structure and insulin. In this paper, we dealt with traumatic events and long-term psycho social consequences for internally displaced persons, several years after displacement, and found a high level of PTSD symptoms. This stress is present in almost 1/3 of internally displaced persons, and every sixth person is suffering from PTSD in the past. Respondents generally suffer from symptoms of intrusion, but there was a large number of symptoms, avoidance and increased arousal. We also found that gender, age andeducation related to the symptoms. Females, and older respondents and internally displaced persons with lower levels of education how a higher level of PTSD symptoms, especially symptoms of intrusion and increase darousal. It is a highly traumatized sample in which more than 1/2 of respondents experienced more than three traumatic events in life,although the number of traumas experienced before, during and after the conflict varies.We found that during the war, internally displaced persons haveexperienced more traumatic events compared with the periodbefore and after the conflict. Trauma are different in type. No significant correlation between the number of experienced trauma and PTSD, suggesting that it is necessary to further study the structure of past traumas and the intermediary effects of certain risk factors and protective factors.

Keywords: living environment, displaced persons, jaundice, diabetes, trauma, diabetic hypertension, post-traumatic stress (PTSD), treatment

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Authors: Dewan Ali Ahsan

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Hilsa (Tenualosa ilisha) is one of the most important anadromous fish species of the trans-boundary ecosystem of Bangladesh, India and Myanmar. Hilsa is not only an economically important species specially for Bangladesh and India, but also for the integral part of the culture of the Bangladesh and India. This flag-ship species in Bangladesh contributed alone of 10.82% of the total fish production of the country and about 75% of world’s total catch of hilsa comes from Bangladesh alone. As hilsa is an anadromous fish, it migrates from the Bay of Bengal to rivers for spawning, nursing and growing and for all of these purposes hilsa needs freshwaters. Ripe broods prefer turbid, fast flowing freshwater for spawning but young prefer clear and slow flowing freshwater. Climate change (salinity intrusion, sea level rise, temperature rise, impact of fresh water flow), unplanned developmental activities and other anthropogenic activities all together are severely damaging the hilsa stock and its habitats. So, climate change and human interferences are predicted to have a range of direct and indirect impacts on marine and freshwater hilsa fishery, with implications for fisheries-dependent economies, coastal communities and fisherfolk. The present study identified that salinity intrusion, siltation in river bed, decrease water flow from upstream, fragmentation of river in dry season, over exploitation, use of small mesh nets are the major reasons to affect the upstream migration of hilsa and its sustainable management. It has been also noticed that Bangladesh government has taken some actions for hilsa management. Government is trying to increase hilsa production not only by conserving jatka (juvenile hilsa) but also protecting the brood hilsa during the breeding seasons by imposing seasonal ban on fishing, restricted mesh size etc. Unfortunately, no such management plans are available for Indian and Myanmar territory. As hilsa is a highly migratory trans-boundary fish in the Bay of Bengal (and all of these countries share the same stock), it is essential to adopt a joint management policy (by Bangladesh-India-Myanmar) for the sustainable management for the hilsa stock.

Keywords: hilsa, climate change, south-east Asia, fishery management

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Authors: Hafiz Gulfam Ahmad, Chuangdong Li, Zeeshan Ahmad

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In this paper, we proposed a parallel IDS and honeypot based approach to detect and analyze the unknown and known attack taxonomy for improving the IDS performance and protecting the network from intruders. The main theme of our approach is to record and analyze the intruder activities by using both the low and high interaction honeypots. Our architecture aims to achieve the required goals by combing signature based IDS, honeypots and generate the new signatures. The paper describes the basic component, design and implementation of this approach and also demonstrates the effectiveness of this approach reducing the probability of network attacks.

Keywords: network security, intrusion detection, honeypot, snort, nmap

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Authors: Yunyong Guo, Man Wang, Bryan Guo, Nathan Guo

Abstract:

This paper introduces an advanced security and privacy model tailored for Telehealth systems, emphasizing end-to-end protection across IoT, Fog, and Cloud components. The proposed model integrates encryption, key management, intrusion detection, and privacy-preserving measures to safeguard patient data. A comprehensive simulation study evaluates the model's effectiveness in scenarios such as unauthorized access, physical breaches, and insider threats. Results indicate notable success in detecting and mitigating threats yet underscore areas for refinement. The study contributes insights into the intricate balance between security and usability in Telehealth environments, setting the stage for continued advancements.

Keywords: cloud, enhancing security, fog, IoT, telehealth

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Authors: Tertia Delia Nova, Masaji Watanabge

Abstract:

Infection of bird flu within a poultry farm involves hosts, virus, and medium. Intrusion of bird flu into a poultry farm divides the population into two groups; healthy and susceptible chickens and infected chickens. A healthy and susceptible bird is infected to become an infected bird. Bird flu viruses spread among chickens through medium such as air and droppings, and increase in hosts. A model for an infection process of bird flu within a poultry farm is described, numerical techniques are illustrated, and numerical results are introduced.

Keywords: bird flu, poultry farm, model for an infection process, flu viruses

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Authors: Hadj Mohamed Nacera, Boutaleb Abdelhak

Abstract:

The Hercynian granite in Western Algeria, has a typical high-K calc-alkaline evolution, with peraluminous trend U-Pb zircon geochronology yielded the minimum emplacement age of 297 ± 1 Ma. It shows dark microgranular enclaves, veins of pegmatite, aplite, tourmaline and quartz. The granite plutons selected for this study are formed during the late Variscian phase and intrudes the Lower Silurian metasediments which were affected by the major Hercynian folding phases. An important Quartz vein field cross-cutting metasedimentary and granitic rocks. Invisible gold occurs in a very small arsenopyrite minerals. The purpose of this study is to highlight the relationship between the gold mineralisation and the intrusion by combining petrographic and geochemic studies.

Keywords: Algeria, basement, geochemestry, granite

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Authors: Ji-Hoon Hong, Dong-Hee Kim, Nam-Uk Kim, Tai-Myoung Chung

Abstract:

Smartphone users are increasing rapidly. Accordingly, many companies are running BYOD (Bring Your Own Device: Policies to bring private-smartphones to the company) policy to increase work efficiency. However, smartphones are always under the threat of malware, thus the company network that is connected smartphone is exposed to serious risks. Most smartphone malware detection techniques are to perform an independent detection (perform the detection of a single target application). In this paper, we analyzed a variety of intrusion detection techniques. Based on the results of analysis propose an agent using the network IDS.

Keywords: android malware detection, software-defined network, interaction environment, android malware detection, software-defined network, interaction environment

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Authors: Bala Adamu Malami

Abstract:

The necessity of low-cost electronic vehicle/car security designed in coordination with other security measures is always there in our society to reduce the risk of vehicle intrusion. Keeping this problem in mind, we are designing an automatic GPS system which is technology to build an integrated and fully customized vehicle to detect the movement of the vehicle and also serve as a security system at a reasonable cost. Users can locate the vehicle's position via GPS by using the Google Maps application to show vehicle coordinates on a smartphone. The tracking system uses a Global System for Mobile Communication (GSM) modem for communication between the mobile station and the microcontroller to send and receive commands. Further design can be improved to capture the vehicle movement range and alert the vehicle owner when the vehicle is out of range.

Keywords: electronic, GPS, GSM modem, communication, vehicle

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Authors: Edward Guillén, Jhordany Rodriguez, Rafael Páez

Abstract:

Anomaly detection techniques have been focused on two main components: data extraction and selection and the second one is the analysis performed over the obtained data. The goal of this paper is to analyze the influence that each of these components has over the system performance by evaluating detection over network scenarios with different setups. The independent variables are as follows: the number of system inputs, the way the inputs are codified and the complexity of the analysis techniques. For the analysis, some approaches of artificial neural networks are implemented with different number of layers. The obtained results show the influence that each of these variables has in the system performance.

Keywords: network intrusion detection, machine learning, artificial neural network, anomaly detection module

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Authors: Jorge Maestre Vidal, Ana Lucila Sandoval Orozco, Luis Javier García Villalba

Abstract:

With the increase in popularity of mobile devices, new and varied forms of malware have emerged. Consequently, the organizations for cyberdefense have echoed the need to deploy more effective defensive schemes adapted to the challenges posed by these recent monitoring environments. In order to contribute to their development, this paper presents a malware detection strategy for mobile devices based on sequence alignment algorithms. Unlike the previous proposals, only the system calls performed during the startup of applications are studied. In this way, it is possible to efficiently study in depth, the sequences of system calls executed by the applications just downloaded from app stores, and initialize them in a secure and isolated environment. As demonstrated in the performed experimentation, most of the analyzed malicious activities were successfully identified in their boot processes.

Keywords: android, information security, intrusion detection systems, malware, mobile devices

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Authors: Sanchai Ratthanakwan

Abstract:

This research aims to study situations and characteristics of the problems facing the urban poor. The data and information are collected by focus group and in-depth interview leader and members of Four Regions Slum Network, community representatives and the social welfare officer. The research can be concluded that the problems of the urban poor faced with three major problems: Firstly, the shortage of housing and stability issues in housing; secondly, the problem of substandard quality of life; and thirdly, the debt problem. The study found that a solution will be found in two ways: First way is the creation of housing for the urban poor in slums or community intrusion by the state. Second way is the stability in the housing and subsistence provided by the community center called “housing stability”.

Keywords: urban poor, social welfare, Bangkok metropolis, housing stability

Procedia PDF Downloads 394

Authors: Dhanesh Sing Das, Bharat Tadikonda Venkata

Abstract:

Collapsible soils undergo significant volume reduction upon wetting under the pre-existing mechanically applied normal stress (inundation pressure). These soils exhibit a very high strength in air-dried conditions and can carry up to a considerable magnitude of normal stress without undergoing significant volume change. The soil strength is, however, lost upon saturation and results in a sudden collapse of the soil structure under the existing mechanical stress condition. The intrusion of water into the dry deposits of such soil causes ground subsidence leading to damages in the overlying buildings/structures. A study on the wetting-induced volume change behavior of collapsible soils is essential in dealing with the ground subsidence problems in various geotechnical engineering practices. The collapse of loosely compacted Kaolin soil upon wetting under various inundation pressures has been reported in recent studies. The collapse in the Kaolin soil is attributed to the alteration in the soil particle-particle association (fabric) resulting due to the changes in the various inter-particle (microscale) forces induced by the water saturation. The inundation pressure plays a significant role in the fabric evolution during the wetting process, thus controls the collapse potential of the compacted soil. A microstructural study is useful to understand the collapse mechanisms at various pore-fabric levels under different inundation pressure. Kaolin soil compacted to a dry density of 1.25 g/cc was used in this work to study the wetting-induced volume change behavior under different inundation pressures in the range of 10-1600 kPa. The compacted specimen of Kaolin soil exhibited a consistent collapse under all the studied inundation pressure. The collapse potential was observed to be increasing with an increase in the inundation pressure up to a maximum value of 13.85% under 800 kPa and then decreased to 11.7% under 1600 kPa. Microstructural analysis was carried out based on the fabric images and the pore size distributions (PSDs) obtained from FESEM analysis and mercury intrusion porosimetry (MIP), respectively. The PSDs and the soil fabric images of ‘as-compacted’ specimen and post-collapse specimen under 400 kPa were analyzed to understand the changes in the soil fabric and pores due to wetting. The pore size density curve for the post-collapse specimen was found to be on the finer side with respect to the ‘as-compacted’ specimen, indicating the reduction of the larger pores during the collapse. The inter-aggregate pores in the range of 0.1-0.5μm were identified as the major contributing pore size classes to the macroscopic volume change. Wetting under an inundation pressure results in the reduction of these pore sizes and lead to an increase in the finer pore sizes. The magnitude of inundation pressure influences the amount of reduction of these pores during the wetting process. The collapse potential was directly related to the degree of reduction in the pore volume contributed by these pore sizes.

Keywords: collapse behavior, inundation pressure, kaolin, microstructure

Procedia PDF Downloads 114