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Sabitha, R.
- Steganalysis:Multi-Class Classification of Images Using Linear Support Vector Machine
Abstract Views :196 |
PDF Views:3
Authors
B. Yamini
1,
R. Sabitha
2
Affiliations
1 Department of CSE, Sathyabama University, Chennai -119, TamilNadu, IN
2 Department of IT, Jeppiaar Engineering College, Chennai-119, TamilNadu, IN
1 Department of CSE, Sathyabama University, Chennai -119, TamilNadu, IN
2 Department of IT, Jeppiaar Engineering College, Chennai-119, TamilNadu, IN
Source
Artificial Intelligent Systems and Machine Learning, Vol 6, No 6 (2014), Pagination: 234-236Abstract
Steganographic techniques have been used to embed covert messages inside a piece of unsuspicious media and sending it without anyone’s knowledge about the survival of the covert message. Steganalysis is the process of detecting the presence of concealed information from the stego image and it can lead to the prevention of terrible security incidents. Steganalysis consist of two stages, the first stage is to identify the existence of the hidden message and the second stage is to retrieve the content of the message. In the existing method, for identifying the existence of the message, two-class classification using Support Vector Machine is used to differentiate the cover and stego images. In this paper, a new technique called multi-class classification using Linear Support Vector Machine is used to differentiate the cover and different type’s stego images.
Keywords
Steganography, Steganalysis, Stego Image, Two-Class Classification, Multi-Class Classisification and Linear Support Vector Machine.
- Adaptive Image Steganalysis for LSB Embedding Technique using Enhanced Canny Operator
Abstract Views :215 |
PDF Views:0
Authors
B. Yamini
1,
R. Sabitha
2
Affiliations
1 Department of Computer Science and Engineering, Sathyabama University, Jeppiaar Nagar, Chennai – 600119, Tamil Nadu, IN
2 Department of Information Technology, Jeppiaar Engineering College, Chennai – 600119, Tamil Nadu, IN
1 Department of Computer Science and Engineering, Sathyabama University, Jeppiaar Nagar, Chennai – 600119, Tamil Nadu, IN
2 Department of Information Technology, Jeppiaar Engineering College, Chennai – 600119, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 10 (2016), Pagination:Abstract
Objectives: Adaptive image steg analysis retrieves concealed content from the adaptable regions of cover image. To identify adaptive regions, Enhanced canny operator is used and which identifies the false edges accurately. Method/Analysis: Adaptive image steganography is the method of hiding the content, based on the adaptable regions of the colour image. The edges in the cover image are used for hiding the secret information by considering two LSB (Least Significant Bit) bits. In the existing method, canny edge detectors were used to extract the features of the image but it fails to identify the false edges and smoothes the boundaries with noise. Findings: In the proposed method, Adaptive regions are identified using enhanced canny operator which identifies the false edges accurately and thus reduces the overhead in payload location identification and content retrieval. This enhanced canny operator outperforms the other edge detectors for the retrieval of content which are embedded using LSB embedding method during steganography. The performance of the operator is measured using Positive Predictive Value (Precision).The precision is calculated after identifying the adaptive region with its payload location and hidden content using ensemble classifier. Applications/Improvements: The performance of the method can be improved by using different classifier combinations as ensemble classifier for multi class classification.Keywords
Adaptive Steganography, Enhanced Canny Operator, Ensemble Classifier, Least Significant Bit, Positive Predictive RateFull Text
- Multi-Level Queue based Resource Allocation in Downlink of OFDMA Wireless Cellular Networks
Abstract Views :183 |
PDF Views:0
Authors
S. Gayathri
1,
R. Sabitha
2
Affiliations
1 Department of Computer Science and Engineering, Sathyabama University, Rajiv Gandhi Road, Jeppiaar Nagar, Chennai - 600119, Tamil Nadu, IN
2 Department of Information Technology, Jeppiaar Engineering College, Rajiv Gandhi Salai, Old Mahabalipuram Road, Semmancheri, Chennai - 600119, Tamil Nadu, IN
1 Department of Computer Science and Engineering, Sathyabama University, Rajiv Gandhi Road, Jeppiaar Nagar, Chennai - 600119, Tamil Nadu, IN
2 Department of Information Technology, Jeppiaar Engineering College, Rajiv Gandhi Salai, Old Mahabalipuram Road, Semmancheri, Chennai - 600119, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 10 (2016), Pagination:Abstract
Objectives: Optimizing the resource allocation to improve throughput in the downlink of OFDMA based wireless cellular networks. Method/Statistical Analysis: In the proposed method, a multi-level queue based resource allocation is proposed where different classes of users will be assigned different queues and different algorithms can be applied to them. The algorithm is implemented and its performance is analyzed and the results are collected and compared with the existing solutions to evaluate the algorithm behavior under different channel conditions. Findings: The algorithm improves the performance and ensures the fairness among the various classes of users based upon the chosen parameters. Also, the algorithm can be configured to either improve the throughput or ensure the fairness depending on the requirements. Applications/Improvement: The algorithm improves the performance and provides a way for different classes of users to be assigned different priorities.Keywords
Channel Quality Information, OFDMA, Resource Allocation, Transfer Rate, Wireless Cellular NetworksFull Text
- An Efficient Integral Power-Elector Method with Enhanced AODV to Avoid Sleep Deprivation in Manet
Abstract Views :146 |
PDF Views:0
Authors
S. Madhurikkha
1,
R. Sabitha
2
Affiliations
1 Sathyabama University, Chennai - 600119, Tamil Nadu, IN
2 Jeppiaar Engineering College, Chennai - 600119, Tamil Nadu, IN
1 Sathyabama University, Chennai - 600119, Tamil Nadu, IN
2 Jeppiaar Engineering College, Chennai - 600119, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 21 (2016), Pagination:Abstract
Objectives: To Enhance Ad hoc On-demand Distance Vector routing (AODV) mechanism with Integral power-elector algorithm and power neural technique to manage node from sleep deprivation attack in Mobile Ad hoc Network (MANET). Methods: Sleep deprivation Attack in MANETs make frequent request to the nodes and deplete the battery level. Colony formation technique implemented using power - elector algorithm with power consumption value of mobile nodes as a key value. A group of wireless devices such as Colonies with Processing head and transmission head avoid the sleep deprivation attack by forwarding the packets to the intended destination. Results are simulated through ns-2 tool. Findings: An efficient power-elector method with power consumption value as a key is introduced. The enhanced AODV protocol with extra two fields added helps to know about the Size of packets to be transmitted and also identifies the number of packets to be transmitted to destination. The algorithm imports colony formation technique and adds up with colony chaining method with optimal value checks for each colony nodes for successful transmission of packets by avoiding the sleep deprivation Attack. The Power value of nodes compared and the proposed methodology shows an improvement. Results are simulated through ns 2.34. Improvement: The proposed method has shown improvement on the power values of node. The existing protocol without proposed method decreases the power value while the proposed method improves it and results are shown.Keywords
AODV, Colony, MANET, Power Consumption, Sleep Deprivation Attack.Full Text
- Yoking of Algorithms for Effective Clustering
Abstract Views :146 |
PDF Views:0
Authors
Affiliations
1 Department of CSE, Sathyabama University, Chennai - 600119, Tamil Nadu, IN
2 Department of IT, Jeppiaar Engineering College, Chennai - 600119, Tamil Nadu, IN
1 Department of CSE, Sathyabama University, Chennai - 600119, Tamil Nadu, IN
2 Department of IT, Jeppiaar Engineering College, Chennai - 600119, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 8, No 22 (2015), Pagination:Abstract
Cluster plays a vital and very important in data mining. Cluster is a main and absolute part of real time applications. Grouping an object with its own class is known as Cluster. It has two different segments, Similar and Dissimilar objects. K Mean (KM) is one of the exclusive clustering algorithms. K Mean algorithm is introduced by cluster, which forms an easier and simpler way of classifying a given set of data. This paper is clearly based on Gravitational Search Algorithm (GSA) and KM algorithm. The main advantage of GSA and KM algorithm is to escape local optima and make convergence motions in rapid progression. A main five data sets in an UCI repository is used to bring the results and solutions in an excellent way using these algorithms. This paper aims to bring an exclusive and efficient result from both the algorithms compared to other algorithm and also gives perfect solution for the existing set of data.Keywords
GSA, K Mean, UCI RepositoryFull Text
- Implementation of Smartphone Activated Doorlock System Using Wireless Fidelity [WiFi] and CCTV Camera
Abstract Views :205 |
PDF Views:1
Authors
R. Sabitha
1,
S. Sridhar
1
Affiliations
1 Department of Master of Computer Application, S. A. Engineering College, Chennai-600 077, IN
1 Department of Master of Computer Application, S. A. Engineering College, Chennai-600 077, IN
Source
Wireless Communication, Vol 10, No 9 (2018), Pagination: 173-177Abstract
WiFi system plays a major role in this smart world now-a-days. As internet connects a wide range of people together, here WiFi is used to share those networks with each other. Smartphone with WiFi involves in many aspects of monitoring. In this paper, the Smartphone activated door lock system is implemented using wireless fidelity technology and CCTV camera. Now-a-days the door lock system is used to secure our private places like home, apartments etc.. The CCTV camera will be set in front of the home. If any person arrives, the camera will capture the photo of the visitor. Immediately the camera transfers it wirelessly to the Smartphone that has been connected to the camera via WiFi. So now the owner of the home can check the photo that has been received through WiFi and if he/she is willing to open the door, he/she can press the push button specified in the Smartphone, so that door will open automatically. As the distance between the owner and the specific place (home, apartment etc..) increases, the opening time of the door also increases as well.
Keywords
WiFi Router, Smartphone, Microcontroller, CCTV Camera, Solenoid Door Lock.References
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- Plant Disease Recognition and Clustering Using Fuzzy Algorithm on Data Mining
Abstract Views :185 |
PDF Views:2
Authors
R. Sabitha
1,
G. Kiruthiga
2
Affiliations
1 Department of Electronics and Communication Engineering, Hindustan College of Engineering and Technology, IN
2 Department of Computer Science and Engineering, IES College of Engineering, IN
1 Department of Electronics and Communication Engineering, Hindustan College of Engineering and Technology, IN
2 Department of Computer Science and Engineering, IES College of Engineering, IN
Source
ICTACT Journal on Soft Computing, Vol 11, No 4 (2021), Pagination: 2429-2432Abstract
Due to large size and intensive processing needs, deep learning models are not suited for mobile and handheld devices. Our goal is to develop a process that begins with pre-processing, diagnoses diseased leaf areas, uses the GLCM to choose and classify features, and culminates in a conclusion. We developed fuzzy decision methods for assigning photos of common rust to various severity levels, using data on diseased leaf regions isolated by threshold segmentation. The outcomes of these experiments were determined by six different colour and texture attributes. In plant disease clustering, the Fuzzy Algorithm is utilised. The test results demonstrate that the new method is more efficient than the conventional approaches and ranks first for feature extraction techniques. This appears to say that plant disease diagnosis using leaves should be utilised. Additional disease classifications or crop/disease classifications can be added to define these capabilities.Keywords
Plant Disease, Plant Leaf, Recognition, Clustering.References
- N.V. Kousik, M. Sivaram and R. Mahaveerakannan, “Improved Density-Based Learning to Cluster for User Web Log in Data Mining”, Proceedings of International Conference on Inventive Computation and Information Technologies, pp. 813-830, 2021.
- H. Azath, M. Mohanapriya and S. Rajalakshmi, “Software Effort Estimation using Modified Fuzzy C Means Clustering and Hybrid ABC-MCS Optimization in Neural Network”, Journal of Intelligent Systems, Vol. 29, No. 1, pp. 251-263, 2018.
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- N.V. Kousik, “Privacy Preservation between Privacy and Utility using ECC-based PSO Algorithm”, Proceedings of International Conference on Intelligent Computing and Applications, pp. 567-573, 2021.
- S. Karthick and P.A. Rajakumari, “Ensemble Similarity Clustering Frame work for Categorical Dataset Clustering Using Swarm Intelligence”, Proceedings of International Conference on Intelligent Computing and Applications, pp. 549-557, 2021.
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- A Service Package Identifier Based Security Verification Algorithm For Wireless Mobile AD-HOC Network
Abstract Views :199 |
PDF Views:0
Authors
R. Sabitha
1,
G. Kiruthiga
2
Affiliations
1 Department of Electronics and Communication Engineering, Hindustan College of Engineering and Technology, IN
2 Department of Computer Science and Engineering, IES College of Engineering, IN
1 Department of Electronics and Communication Engineering, Hindustan College of Engineering and Technology, IN
2 Department of Computer Science and Engineering, IES College of Engineering, IN
Source
ICTACT Journal on Communication Technology, Vol 13, No 1 (2022), Pagination: 2650-2655Abstract
In general, the biggest problem with a mobile ad-hoc network is the threat to its security. This is because the mobile ad-hoc network is dismantled after a certain period of time, which spends a lot of time calculating its stability and greatly wastes its security dimensions. Thus, the security features on these temporary networks need to be strengthened as they pose the most threats. In this paper, a security algorithm designed in SID mode is proposed to fix security vulnerabilities in the wireless mobile ad-hoc network module. Its main feature is that its security definitions are defined according to the number of Service Package Identification assigned to it. The definition of numbers based on its importance is to make a list of related devices in order and, accordingly, bring those devices into the security module. Its security features have been improved so that the security modules remain active as long as the network is active.Keywords
Service Package Identification, Ad-hoc Networks, MANET, Security, StabilityReferences
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