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An Autoencoder and LSTM based Intrusion Detection approach against Denial of service attacks 基于自编码器和LSTM的拒绝服务入侵检测方法
2019 1st International Conference on Advances in Information Technology (ICAIT) Pub Date : 2019-07-01 DOI: 10.1109/ICAIT47043.2019.8987336
R. A. Shaikh, S. Shashikala
{"title":"An Autoencoder and LSTM based Intrusion Detection approach against Denial of service attacks","authors":"R. A. Shaikh, S. Shashikala","doi":"10.1109/ICAIT47043.2019.8987336","DOIUrl":"https://doi.org/10.1109/ICAIT47043.2019.8987336","url":null,"abstract":"The advent of technology made the nations to grow in a rapid phase but most of the nation are not ready to defend the critical infrastructure cyber-attacks on government databases and many organizations. Several cyber-attacks, in recent days Denial of Service (DoS) attacks are popular because of their severe impact on the network and its resources. Anomaly detection has been a field of intense research over the years as it poses many challenging problems. Machine learning and Deep Learning techniques have proven to be useful in identifying the anomalous patterns with least number of false positives. In this paper we present an Intelligent IDS built using advanced artificial neural network algorithms such as Autoencoders and Long Shor-Term Memory (LSTM). The proposed model is a novel approach which eliminates the challenges with time recurrent neural network architecture such as the response time in backpropagation. The LSTM algorithm is derived from the deep learning, which has shown promising results to learn and detect novel attacks.","PeriodicalId":221994,"journal":{"name":"2019 1st International Conference on Advances in Information Technology (ICAIT)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132155623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
Segmentation of Arecanut Bunches using YCgCr Color Model 用YCgCr颜色模型分割槟榔束
2019 1st International Conference on Advances in Information Technology (ICAIT) Pub Date : 2019-07-01 DOI: 10.1109/ICAIT47043.2019.8987431
R. Dhanesha, C. L. Shrinivasa Naika, Y. Kantharaj
{"title":"Segmentation of Arecanut Bunches using YCgCr Color Model","authors":"R. Dhanesha, C. L. Shrinivasa Naika, Y. Kantharaj","doi":"10.1109/ICAIT47043.2019.8987431","DOIUrl":"https://doi.org/10.1109/ICAIT47043.2019.8987431","url":null,"abstract":"Arecanut is profit-oriented crop of south India. In the market maturity level decides the price of Arecanut. To enhance the profitability identifying maturity level of Arecanut before harvesting is indispensable. Farmer need expertise to determine maturity level otherwise they get less profit for their crops. In recent times Computer Vision and Image Processing techniques are used in Precision Agriculture to identify the matured fruits and vegetables before harvesting. This paper proposes YCgCr color model to automatically segment the Arecanut bunch from a given image. Further, the segmented image could be used to determine Arecanut maturity level. Experiments were conducted to evaluate the efficacy of the segmentation method and found that the average Volumetric Overlap Error (VOE) is - 0.30 and Dice Similarity Coefficient (DSC) is 0.81.","PeriodicalId":221994,"journal":{"name":"2019 1st International Conference on Advances in Information Technology (ICAIT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125128490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
A reversible steganography using prediction value coding and histogram shifting 使用预测值编码和直方图移位的可逆隐写
2019 1st International Conference on Advances in Information Technology (ICAIT) Pub Date : 2019-07-01 DOI: 10.1109/ICAIT47043.2019.8987322
Chaithra I. V, S. R, Vivekananda Vivekananda
{"title":"A reversible steganography using prediction value coding and histogram shifting","authors":"Chaithra I. V, S. R, Vivekananda Vivekananda","doi":"10.1109/ICAIT47043.2019.8987322","DOIUrl":"https://doi.org/10.1109/ICAIT47043.2019.8987322","url":null,"abstract":"Steganography aims to embed the secret information in digital media for the purpose of secret communication, so that embedded data is not visible. The reversible steganography ensures that image is completely recovered to its original form after the secret data is extracted out. We are implementing reversible steganography that combines linear prediction error value coding and histogram shifting.The cover image is divided into multiple blocks. The above mentioned methods are applied for each block of image. Linear prediction error coding method calculates the prediction error values of cover image using basic pixel by scanning image blocks in inverse S-order. Histogram is generated for prediction error values to find the two peak points and two zero points. Histogram shifting method embeds the secret data in peak points of histogram of image. The reverse linear prediction error calculated to obtain stego image. The extraction and recovery procedure are done to extract secret message and recover the cover image. In the experimental results the better hiding capacity is obtained for smaller block size with fractional improvement to image quality. Keywords: Steganography, Reversible data hiding, Inverse S-order, Histogram shifting.","PeriodicalId":221994,"journal":{"name":"2019 1st International Conference on Advances in Information Technology (ICAIT)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127007831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
An Efficient Graph Eccentric Approach to find Influential Nodes in Social Network 一种寻找社会网络中影响节点的高效图偏心方法
2019 1st International Conference on Advances in Information Technology (ICAIT) Pub Date : 2019-07-01 DOI: 10.1109/ICAIT47043.2019.8987427
Chaithra K.N, Mohan Kumar K. N, Jayanna T M
{"title":"An Efficient Graph Eccentric Approach to find Influential Nodes in Social Network","authors":"Chaithra K.N, Mohan Kumar K. N, Jayanna T M","doi":"10.1109/ICAIT47043.2019.8987427","DOIUrl":"https://doi.org/10.1109/ICAIT47043.2019.8987427","url":null,"abstract":"The advent of technology has enhanced the marketing approaches. Today the best platform for marketing is social network, but the question arises, to whom we should share the content to spread it across. Our work focuses, to find the most influential member (node) in a social network. The societal needs have made network centric computing significant. The internet research community such as promoting sales, viral marketing and campaigning has focused their attention on effective utilization of social network platforms. In marketing era it is difficult to find the influential member to introduce any product. In this paper we propose a better solution to find top-k nodes by using the concept of graph theory. Our method gives the solution to 1) Finding the centrality based on number of connections. 2) To find the minimal count of nodes to traverse maximum network. 3) λ-coverage problem to calculate maximum number of nodes needed to cover λ percentage of area. The result shows our method gives significant output.","PeriodicalId":221994,"journal":{"name":"2019 1st International Conference on Advances in Information Technology (ICAIT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117024513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
A Novel Approach for Static RWA based PLI Evaluation of WDM Networks in "WDM-NetSoft" 一种基于静态RWA的WDM网络PLI评估新方法
2019 1st International Conference on Advances in Information Technology (ICAIT) Pub Date : 2019-07-01 DOI: 10.1109/ICAIT47043.2019.8987250
Sting Salvador Gonsalis, Triveni C L
{"title":"A Novel Approach for Static RWA based PLI Evaluation of WDM Networks in \"WDM-NetSoft\"","authors":"Sting Salvador Gonsalis, Triveni C L","doi":"10.1109/ICAIT47043.2019.8987250","DOIUrl":"https://doi.org/10.1109/ICAIT47043.2019.8987250","url":null,"abstract":"In recent years, network simulators [1] - [5] have become accustomed to the analysis and design of optical fiber communication networks in the academy and industry. In this work we present the new network software WDM-NetSoft for planning, analyzing and designing wavelength routed optic networks. The software analyzes network for IndiaNet topology as a long haul network. In addition, the software considers different modulation formats along with physical layer impairments for the networks performance evaluation.Traffic in long haul networks has become versatile and supports different service requirements. The current 10 Gbps network needs to be upgraded to 40/112 Gbps to meet the demand for different services (s). Mixed line rate (MLR) wavelength-division multiplexed (WDM) optical networks are a low cost alternative for future networks. MLR networks support various line rates on various wavelengths within a fiber. The physical impairments include accumulated ASE(amplified spontaneous emission) noise, chromatic dispersion, switch crosstalk, PMD(Polarization Mode Dispersion) effects, & fiber nonlinearities. Therefore, this paper demonstrates the functionality of our software to analyze a variety of practical WDM networks.","PeriodicalId":221994,"journal":{"name":"2019 1st International Conference on Advances in Information Technology (ICAIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131812779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Moving objects Path Tracking based on Entropy Background Subtraction and CAMShift 基于熵背景减法和CAMShift的运动目标路径跟踪
2019 1st International Conference on Advances in Information Technology (ICAIT) Pub Date : 2019-07-01 DOI: 10.1109/ICAIT47043.2019.8987253
C. Arpitha, M. R. Sunitha
{"title":"Moving objects Path Tracking based on Entropy Background Subtraction and CAMShift","authors":"C. Arpitha, M. R. Sunitha","doi":"10.1109/ICAIT47043.2019.8987253","DOIUrl":"https://doi.org/10.1109/ICAIT47043.2019.8987253","url":null,"abstract":"For multiple object path tracking we integrate entropy background subtraction method and CAMShift algorithm. Initially claussius entropy theory is used to transform each pixel in the image domain into entropy domain and obtain its energy level. Later we use entropy background subtraction algorithm to detect moving object region in each frame. To improve robustness in the condition where objects are of different color, object colors are same as to background’s colors. localization of object is obtained by choosing each objective region. This approach can automatically calibrate moving vehicles in traffic video and achieve multi-target tracking by using a multi-tracker of CAMShift algorithm. The proposed system is also capable of tracing paths of moving vehicles. The results and analysis demonstrates that the methods used in the paper finds solution for automatic multi-object tracking problems in video sequence efficiently.","PeriodicalId":221994,"journal":{"name":"2019 1st International Conference on Advances in Information Technology (ICAIT)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133375209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Solutions to Achieve Virtual Machine Placement in Cloud Computing Environment 在云计算环境中实现虚拟机放置的解决方案
2019 1st International Conference on Advances in Information Technology (ICAIT) Pub Date : 2019-07-01 DOI: 10.1109/ICAIT47043.2019.8987386
P. Bharti, R. Ranjan
{"title":"Solutions to Achieve Virtual Machine Placement in Cloud Computing Environment","authors":"P. Bharti, R. Ranjan","doi":"10.1109/ICAIT47043.2019.8987386","DOIUrl":"https://doi.org/10.1109/ICAIT47043.2019.8987386","url":null,"abstract":"Cloud providers have enormous expectations in terms of maintaining Quality-of-Service (QoS) to optimize energy efficiency levels, since cloud computing has become very popular. Several mechanisms are discussed in research papers to achieve it. One such mechanism is Virtual Machine Placement (VMP). In this paper, we discuss variants of bin packing algorithms which enhances VMP placements. Further, it summarizes them with different parameters. Additionally, it also points out the challenges involved in bin packing based algorithms.","PeriodicalId":221994,"journal":{"name":"2019 1st International Conference on Advances in Information Technology (ICAIT)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125242039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Automated Detection of White Blood Cells Cancer Disease 白细胞癌疾病的自动检测
2019 1st International Conference on Advances in Information Technology (ICAIT) Pub Date : 2019-07-01 DOI: 10.1109/ICAIT47043.2019.8987352
Lakshmi Kg, N. Manja Naik
{"title":"Automated Detection of White Blood Cells Cancer Disease","authors":"Lakshmi Kg, N. Manja Naik","doi":"10.1109/ICAIT47043.2019.8987352","DOIUrl":"https://doi.org/10.1109/ICAIT47043.2019.8987352","url":null,"abstract":"Leukemia is a blood disease . The pace of cure be dependent upon the kind of Leukemia just as the period of unfortunate casualties. Intense lymphocytic Leukemia, Acute myeloid Leukemia and typical instances of Microscopic pictures of blood marrow spreads at first separated the core by evacuating foundation utilizing division. At that point the impacted cores' shading, GLCM and geometric highlights are separated lastly these cells are named carcinogenic or nonmalignant cell and its subtypes utilizing bolster vector machine (SVM) and KNN classifier. The precision of the classifier assessed up to 94.3%. The trial results demonstrates that proposed calculation could achieve a sufficient exhibition for the analysis of AML, ALL and their sub-types.","PeriodicalId":221994,"journal":{"name":"2019 1st International Conference on Advances in Information Technology (ICAIT)","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116083858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
Survey on Deep Reinforcement Learning Protocol in VANET VANET中深度强化学习协议研究综述
2019 1st International Conference on Advances in Information Technology (ICAIT) Pub Date : 2019-07-01 DOI: 10.1109/ICAIT47043.2019.8987282
Shweta S Doddalinganavar, P. Tergundi, Rudragouda S. Patil
{"title":"Survey on Deep Reinforcement Learning Protocol in VANET","authors":"Shweta S Doddalinganavar, P. Tergundi, Rudragouda S. Patil","doi":"10.1109/ICAIT47043.2019.8987282","DOIUrl":"https://doi.org/10.1109/ICAIT47043.2019.8987282","url":null,"abstract":"Now a day’s numerous application are based on machine learning (M-L) techniques for enhancing performance of data, M-L techniques consist deep learning, reinforcement learning (RL), deep reinforcement learning (DRL), supervised learning (SL), unsupervised learning(UL), deep Q learning (DQL) etc. Vehicular Adhoc Networks (VANETS) most crucial aspect in modern network, which are decentralized over network. Here the challenges of decision making plays vital role for increasing performance, efficiency and minimizing energy consumption for that M-L techniques are utilized. RL unable to address the problem in a large-scale network. Hence RL is combined with DL and is known as deep reinforcement learning (DRL) for addressing challenges in large-scale network. Here we mainly focus VANET, which is the sub type of Mobile Ad-Hoc Network that offers connection between base stations of street– side and vehicles with an objective of giving secure and efficient conveyance. We also discuss different algorithms of M-L technique like KNN, Deep Q learning, SVM.","PeriodicalId":221994,"journal":{"name":"2019 1st International Conference on Advances in Information Technology (ICAIT)","volume":"158 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125991275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
RADAR based Object Detector using Ultrasonic Sensor 基于雷达的超声波目标探测器
2019 1st International Conference on Advances in Information Technology (ICAIT) Pub Date : 2019-07-01 DOI: 10.1109/ICAIT47043.2019.8987259
Akshaya U Kulkarni, Amit M Potdar, Suresh M Hegde, V. Baligar
{"title":"RADAR based Object Detector using Ultrasonic Sensor","authors":"Akshaya U Kulkarni, Amit M Potdar, Suresh M Hegde, V. Baligar","doi":"10.1109/ICAIT47043.2019.8987259","DOIUrl":"https://doi.org/10.1109/ICAIT47043.2019.8987259","url":null,"abstract":"Target/object detection, recognition, position, movement speed, etc. is easy when the object is near or easily visible. But, the same doesn’t stand true especially when the object is far or not visible due to so many factors like weather conditions, day/night cycle, etc. Therefore, Radio Detection And Ranging (RADAR) was invented, which uses radio waves to determine the range, angle, or velocity of objects. But, it uses long time to detect, has short detection range, not target specific because of wide range, oversensitive, costly, etc. A cheaper, easy and effective alternate solution is to use ultrasonic sensor which use sound waves for detection and ranging. Therefore, this paper provides a method in which the Ultrasonic Sensor (HC-SR04) acts as RADAR. The HC-RS04 is connected to Servo Motor (SG90) for the rotation/movement purpose. SIM808 module is also used to notify object detection via message/SMS. These components are connected to Arduino Uno and Raspberry Pi3 for being processed to detect and notify the object. Usually, the range of ultrasonic wave is 20kHz but here the HC-SR04 range is 3cm to 4m as it is smaller in terms of project usage. Advantages are: it is not affected by color or transparency of objects, can be used in dark environments, not highly affected by dust, dirt, or high-moisture environments, etc. The results show the object detected with its range/distance and angle in a java based GUI, different ranges of object in cm at which it is detected and the detection message sent to the admin.","PeriodicalId":221994,"journal":{"name":"2019 1st International Conference on Advances in Information Technology (ICAIT)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121747234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
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