2021 International Conference on Intelligent Technologies (CONIT)最新文献_第3页

Securing Neural Networks Using Homomorphic Encryption 利用同态加密保护神经网络

2021 International Conference on Intelligent Technologies (CONIT) Pub Date : 2021-06-25 DOI: 10.1109/CONIT51480.2021.9498376

A. Dalvi, Apoorva Jain, Smit Moradiya, Riddhisha Nirmal, Jay Sanghavi, Irfan A. Siddavatam

{"title":"Securing Neural Networks Using Homomorphic Encryption","authors":"A. Dalvi, Apoorva Jain, Smit Moradiya, Riddhisha Nirmal, Jay Sanghavi, Irfan A. Siddavatam","doi":"10.1109/CONIT51480.2021.9498376","DOIUrl":"https://doi.org/10.1109/CONIT51480.2021.9498376","url":null,"abstract":"Neural networks are becoming increasingly popular within the modern world, and they are often implemented without much consideration of their potential flaws, which makes them vulnerable and are easily being hacked by hackers. One of such vulnerabilities, namely, a backdoor attack is studied in this paper. A backdoor attacked neural network involves inducing unique misclassification rules or patterns as triggers in the neural network such that, upon encountering the trigger, the neural network will only predict the output based upon the misclassification rules, giving the attacker control over the output of the neural network. To prevent such a vulnerability, we propose to employ homomorphic encryption as a solution. Homomorphic Encrypted Data has a special property where certain operations can be performed on encrypted data to in-turn directly perform the operations on the plain-text data itself, without the need of any special mechanism. This ability of homomorphic encryption can be used in conjunction with the vulnerable neural network, to revoke the control of the attacker from the neural network. Thereby, in this paper, we will be securing a vulnerable neural network from backdoor attack using homomorphic encryption.","PeriodicalId":426131,"journal":{"name":"2021 International Conference on Intelligent Technologies (CONIT)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127749203","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: 3

Query-By-Object Based Video Synopsis 基于对象查询的视频摘要

2021 International Conference on Intelligent Technologies (CONIT) Pub Date : 2021-06-25 DOI: 10.1109/CONIT51480.2021.9498311

Shweta S Kakodra, C. Sujatha, P. Desai

引用次数: 2

Logistic and Tent Map Encrypted Image Steganography in Transformation Domain using DWT-LSB Technique 基于DWT-LSB技术的变换域逻辑映射和帐篷映射加密图像隐写

2021 International Conference on Intelligent Technologies (CONIT) Pub Date : 2021-06-25 DOI: 10.1109/CONIT51480.2021.9498497

B. S. Shashikiran, K. Shaila, K. Venugopal

引用次数: 0

Model Predictive Control of a Three Phase Four Leg LC Filtered Inverter: Reduction of Manufacturing Cost and Simplification of Working Processes 三相四腿LC滤波逆变器的模型预测控制:降低制造成本和简化工作流程

2021 International Conference on Intelligent Technologies (CONIT) Pub Date : 2021-06-25 DOI: 10.1109/CONIT51480.2021.9498444

MD Nazmul Hasan, Aninda Dey Arpon

引用次数: 0

Design and Development of Hybrid Feature Selection Method for Classification 混合特征选择分类方法的设计与开发

2021 International Conference on Intelligent Technologies (CONIT) Pub Date : 2021-06-25 DOI: 10.1109/CONIT51480.2021.9498548

M. Sreedevi, G. Manasa, Idupulapati Apurva

{"title":"Design and Development of Hybrid Feature Selection Method for Classification","authors":"M. Sreedevi, G. Manasa, Idupulapati Apurva","doi":"10.1109/CONIT51480.2021.9498548","DOIUrl":"https://doi.org/10.1109/CONIT51480.2021.9498548","url":null,"abstract":"To enhance the capability of the learning model in this research paper we have developed a hybrid feature selection method. To defeat the curse of dimensionality, to speed up the classification process, and to get more accurate results a hybrid feature selection model is developed which is a combination of multiple filter methods and a wrapper method. In this model, we employed two sets of Filter Methods-Basic filter methods, a correlation filter method and two Statistical & Ranking filter methods (ANOVA and ROC-AUC) to generate two different subsets of important features, and a Wrapper method (Recursive Feature Elimination with Cross-Validation) is applied on the combined subset to generate a final subset of important features for better prediction results. Five machine learning algorithms-Logistic Regression (LR), Decision Tree, Random Forest (RF), Support Vector Machine (SVM), and K-Nearest Neighbour are used to evaluate the classification accuracy. The proposed hybrid method is applied over four low and four microarray datasets. Outputs are compared to find out which algorithm works best with the proposed model as the results diverge with the machine learning algorithm. Precision, Sensitivity, and Specificity are calculated for each outcome and they demonstrate that the suggested method improved the accuracy of the algorithms.","PeriodicalId":426131,"journal":{"name":"2021 International Conference on Intelligent Technologies (CONIT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130020199","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

Design & Implementation of Vertical Surface Climbing Cleaner Robot 垂直爬面清扫机器人的设计与实现

2021 International Conference on Intelligent Technologies (CONIT) Pub Date : 2021-06-25 DOI: 10.1109/CONIT51480.2021.9498276

Md Eyasin Rahman, Md Rahat Azad, Md. Touhidul Islam, Md. J. Uddin, Jobayer Inbe Azad

{"title":"Design & Implementation of Vertical Surface Climbing Cleaner Robot","authors":"Md Eyasin Rahman, Md Rahat Azad, Md. Touhidul Islam, Md. J. Uddin, Jobayer Inbe Azad","doi":"10.1109/CONIT51480.2021.9498276","DOIUrl":"https://doi.org/10.1109/CONIT51480.2021.9498276","url":null,"abstract":"This paper presents a vertical surface climbing robot for cleaning of dust from high rise building. Usually, people clean their wall of outer surface of building by human. Often it becomes risky and costly also. A portable robot having the ability to climb on vertical surface has been expected for a long time. To protect human’s life we designed a prototype of vertical surface climbing robot for cleaning and other multipurpose operation. Some combination of technology has been shown such as smart wireless control with all direction moving capability. Four Dc motors are used to move the robot and one Dc motor is used to rotate the cleaning brush. There is one Electric Ducted fan (EDF) which helps the robot to stick to the surface against gravitational force. An Arduino uno is used as a controller for different There is a Bluetooth modular which has been used to connect with smart phone and take command from user. Four motor helps it to move in up, down, right and left direction by the according commands given by smart phone. The full robot is power by using DC battery and AC to DC converted adapter combined. To observe the outcome of the project, we analyzed the performance of the robot by climbing in different surfaces with different nature. The climbing and stick to the surface differ because of grip. Griping is an important issue for this robot. Most of the surface except glass its performance satisfied us.","PeriodicalId":426131,"journal":{"name":"2021 International Conference on Intelligent Technologies (CONIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130089581","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

Method for Nearby Product Marketing using Wi-Fi Aware Technology 基于Wi-Fi感知技术的就近产品营销方法

2021 International Conference on Intelligent Technologies (CONIT) Pub Date : 2021-06-25 DOI: 10.1109/CONIT51480.2021.9498283

Dhaval Prajapati

引用次数: 1

Music Emotion Recognition in Assamese Songs using MFCC Features and MLP Classifier 基于MFCC特征和MLP分类器的阿萨姆语歌曲音乐情感识别

2021 International Conference on Intelligent Technologies (CONIT) Pub Date : 2021-06-25 DOI: 10.1109/CONIT51480.2021.9498345

Jumpi Dutta, D. Chanda

引用次数: 4

Performance Analysis of Pseudo Random Bit Generator Using Modified Dual-Coupled Linear Congruential Generator 基于改进双耦合线性同余发生器的伪随机比特发生器性能分析

2021 International Conference on Intelligent Technologies (CONIT) Pub Date : 2021-06-25 DOI: 10.1109/CONIT51480.2021.9498354

N. Akhila, C. Kumari, K. Swathi, T. Padma, N. Rao

引用次数: 6

A Robust Support Vector Machine Based Auto-Encoder for DoS Attacks Identification in Computer Networks 基于鲁棒支持向量机的DoS攻击识别自编码器

2021 International Conference on Intelligent Technologies (CONIT) Pub Date : 2021-06-25 DOI: 10.1109/CONIT51480.2021.9498284

Shridhar Allagi, R. Rachh, B. Anami

引用次数: 0