2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS)最新文献_第10页

Deep Learning Framework and Visualization for Malware Classification 恶意软件分类的深度学习框架和可视化

2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS) Pub Date : 2019-03-01 DOI: 10.1109/ICACCS.2019.8728471

A. S, S. K, P. Poornachandran, V. Menon, S. P.

{"title":"Deep Learning Framework and Visualization for Malware Classification","authors":"A. S, S. K, P. Poornachandran, V. Menon, S. P.","doi":"10.1109/ICACCS.2019.8728471","DOIUrl":"https://doi.org/10.1109/ICACCS.2019.8728471","url":null,"abstract":"In this paper we propose a deep learning framework for classification of malware. There has been an enormous increase in the volume of malware generated lately which represents a genuine security danger to organizations and people. So as to battle the expansion of malwares, new strategies are needed to quickly identify and classify malware. Malimg dataset, a publicly available benchmark data set was used for the experimentation. The architecture used in this work is a hybrid cost-sensitive network of one-dimensional Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) network which obtained an accuracy of 94.4%, an increase in performance compared to work done by [1] which got 84.9%. Hyper parameter tuning is done on deep learning architecture to set the parameters. A learning rate of 0.01 was taken for all experiments. Train-test split of 70-30% was done during experimentation. This facilitates to find how well the models perform on imbalanced data sets. Usual methods like disassembly, decompiling, de-obfuscation or execution of the binary need not be done in this proposed method. The source code and the trained models are made publicly available for further research.","PeriodicalId":249139,"journal":{"name":"2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127109817","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: 21

An Overview Of Dynamic CMOS Comparators 动态CMOS比较器概述

2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS) Pub Date : 2019-03-01 DOI: 10.1109/ICACCS.2019.8728470

R. Sangeetha, A. Vidhyashri, M. Reena, R. Sudharshan, Sangeetha Govindan, J. Ajayan

引用次数: 11

Sign Language Recognition System Using Deep Neural Network 基于深度神经网络的手语识别系统

2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS) Pub Date : 2019-03-01 DOI: 10.1109/ICACCS.2019.8728411

Surejya Suresh, M. T. P., Supriya M.H

引用次数: 15

Road Sign Recognition System for Autonomous Vehicle using Raspberry Pi 基于树莓派的自动驾驶汽车路标识别系统

2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS) Pub Date : 2019-03-01 DOI: 10.1109/ICACCS.2019.8728463

K. Vinothini, S. Jayanthy

引用次数: 4

Voice Operated Intelligent Fire Extinguishing Vehicle 语音操作智能灭火车

2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS) Pub Date : 2019-03-01 DOI: 10.1109/ICACCS.2019.8728326

R. Karthik, T. Divagar, M. Karthikeyan, D. Kumar

引用次数: 2

An Approach to Classify Lung Nodules for Detection of Cancer Cells 一种用于检测癌细胞的肺结节分类方法

2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS) Pub Date : 2019-03-01 DOI: 10.1109/ICACCS.2019.8728332

Jayshree Talukdar, P. Sarma

引用次数: 1

A Trend Analysis of Diffusion Energy Effective Clustering Techniques in Wireless Sensor Networks 无线传感器网络中扩散能量有效聚类技术的趋势分析

2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS) Pub Date : 2019-03-01 DOI: 10.1109/ICACCS.2019.8728513

S. Manikandan, M. Jeyakarthic

引用次数: 0

Segmentation and Classification of Lung Nodules using Split Bregman and SVM Classifier 使用 Split Bregman 和 SVM 分类器对肺结节进行分割和分类

2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS) Pub Date : 2019-03-01 DOI: 10.1109/ICACCS.2019.8728481

S. Pattar

{"title":"Segmentation and Classification of Lung Nodules using Split Bregman and SVM Classifier","authors":"S. Pattar","doi":"10.1109/ICACCS.2019.8728481","DOIUrl":"https://doi.org/10.1109/ICACCS.2019.8728481","url":null,"abstract":"Lung nodules are a commonly occurring problem in the society. This problem is more prevalent in populations that expose themselves to risk factors such as smoking, pollution, etc. The current techniques used for segmentation of lung nodules from CT images have the following drawbacks: Most segmentation algorithms use Local Fitting Models that need re-initialization for the sign distance function. The inhomogeneity in the CT images make the algorithms to settle at local minima and lead to wrong segmentation. Re-initialization increases the time required and makes the algorithm slow. Region-based active contour models are powerful and flexible methods which can able to segment real and synthetic images. In the proposed method Global Convex Segmentation (GCS) and Split Bregman technique is incorporated into a region based active contour model such as Chan-Vese (CV) with Region-Scalable Fitting (RSF) scheme to segment the Lung nodules region. Local Binary Pattern descriptor (LBP) is used to extract the tumor features. The extracted features are used to classify the nodules as tumor or non-tumor with the help of Support Vector Machine (SVM). The classification accuracy obtained is enhanced compared to other existing methods. Experimental results are demonstrated by using Lung CT images.","PeriodicalId":249139,"journal":{"name":"2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128473208","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

PUF Authentication using Visual Secret Sharing Scheme 基于可视化秘密共享方案的PUF认证

2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS) Pub Date : 2019-03-01 DOI: 10.1109/ICACCS.2019.8728504

D. Naveen, K. Praveen

引用次数: 3

Energy Efficient Hierarchical Key Management Protocol 节能分层密钥管理协议

2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS) Pub Date : 2019-03-01 DOI: 10.1109/ICACCS.2019.8728343

T. Kavitha, Rajadurai Kaliyaperumal

{"title":"Energy Efficient Hierarchical Key Management Protocol","authors":"T. Kavitha, Rajadurai Kaliyaperumal","doi":"10.1109/ICACCS.2019.8728343","DOIUrl":"https://doi.org/10.1109/ICACCS.2019.8728343","url":null,"abstract":"A wireless sensor network (WSN) is a group of resource-constrained, inexpensive, tiny, and homogeneous or heterogeneous sensor nodes. The inherent nature of WSNs such that it makes them deployable in a variety of circumstances, which increases the interest towards them but at the same time poses tremendous challenges such as resource-constrained nodes, unattended operations, unknown topology and wireless communication links. Security in WSNs can be achieved with the help of various cryptographic operations. The strength of cryptographic system depends on the secrecy of the key it uses. So, a solid strong key management frame work is the prerequisite for the cryptographic primitive upon which other security primitives are built.To improve the energy efficiency and increase the resilience more effectively, an Energy Efficient Hierarchical Key management Protocol (EEHKMP) for hierarchical homogeneous WSN is proposed. In this protocol, a Differentiated random KPD (DKPD) process is employed for randomly deployed distributed WSN. Its main objective is to distribute different number of keys which are chosen randomly to different sensors in order to enhance the resilience of certain links such that the nodes can route through those links with higher resilience. This DKPD process divides the sensor nodes into different classes and pre-distributes the keys according to each class. Nodes with maximum residual energy and minimum distance are elected as cluster heads (CHs). The CH sets up the intra-cluster and inter-cluster routes with nodes having more shared keys. CH generates multiple random key shares to generate pair-wise key and transmits each key share to source and destination on each hop route, which is selected based on the cost function. Key shares are hop-by-hop encrypted / decrypted by a combination of all shared pre-distributed keys on that hop. Finally, a key update mechanism is presented to update the keys.","PeriodicalId":249139,"journal":{"name":"2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS)","volume":"572 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116292398","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