International Journals

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Author: search.filters.author.Radha NHas files: Yes

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    A STUDY OF TECHNIQUES ON SECURING PATIENT CONFIDENTIAL INFORMATION USING ECG STEGANOGRAPHY
    (International Journal of Engineering Research and Applications, 2018-10) Radha N; Rehana Banu H
    Plants play an important role in the earth’s ecology. Without plants, human lives cannot exist in this world. But in the recent days, people are not having knowledge about many types of valuable plants. They are at the risk of extinction. So, it is necessary to protect plants and to catalogue various types of flora diversities and it is important to maintain plant databases which pave a way towards conservation of earth’s biosphere. In the world wide, there are a huge number of plant species available. To handle such volumes of information, development of a quick and efficient classification tool using machine learning algorithms is needed. In addition to the conservation aspect, recognition of plants paves a way to use those plants as an alternative energy source. In this paper, various techniques used to classify the leaf images using machine learning algorithms are studied.
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    A SURVEY ON WORMHOLE AND SINKHOLE ATTACK DETECTION AND PREVENTION TECHNIQUES IN MANET
    (International Journal of engineering research and application, 2017-11) Sasirekha D; Radha N
    Nowadays with the wide range of applications in wireless networks, there is an increasing need for security of these networks. Specifically, the Mobile Ad-hoc networks are very easy to vulnerable due to many security threats and attacks. These networks have been subjected to numerous attacks among which Sinkhole and wormhole attack are the prominent attacks. In the network routing these attacks should be identified earlier and recovered soon. In the wormhole attack, the data transferred to more routes or the malicious node abused the received data into many ways. In the Sinkhole attack the attacker seeks the data transferred by attracting the node in various ways. Various solutions are found to detect these network attacks. In this paper, a comparative analysis of those techniques is performed. This study finds the impact and suitable methods to prevent and detect wormhole and sinkhole attacks in Mobile ad-hoc networks.
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    AN IMPROVED TRUST BASED APPROACH FOR DETECTING MALICIOUS NODES IN MANET
    (International Journal of Computer Trends and Technology, 2016-11) Nachammai M; Radha N
    Mobile ad hoc network (MANET) is an infrastructure-less network of mobile devices connected wirelessly. MANET is used widely today because of its nature as self-configuring, easy to move independently in any directions. MANET acts like a router and therefore changes its links to other devices frequently. Due to its nature MANET has been used in various applications like Military applications, Wireless Sensor Network and so on. As its infrastructure-less and dynamic nature, it is highly affected by various attacks like black hole attack, gray hole attack, DoS attack and many collaborative attacks. Hence security is the main challenge in MANET. Many existing works has done on the basis of detecting attacks by using various approaches like Intrusion Detection, Bait detection, Cooperative malicious detection and so on. But this Trust based approach mainly focuses on detecting the malicious nodes on the trusted path than the shortest path as discovered by using DSR mechanism
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    A STUDY OF CANCELLABLE FINGERPRINT TEMPLATE GENERATION TECHNIQUES USING CRYPTOGRAPHY
    (International Research Journal of Engineering and Technology (IRJET), 2016-07) Partheeba R; Radha N
    Secure Transmission of data needs ensured cryptographic technique with most effective solution. Network Security has become a great threat to the Network Accessible Resources that consists of the policies to prevent and monitor unauthorized access, modification, misuse of a computer network and network-accessible resources. Several numbers of algorithms and techniques were proposed for the secure transmission of data and to protect user’s privacy. Secret-key cryptography and public-key cryptography are the two major cryptographic architectures that are defined for the protection of security issues. Secrecy of the cryptographic key holds the security of the system. Thus, key management is the main issue in the cryptography. Hence several key generation methods were developed and ensured for privacy over communication. This work brings a study of various techniques used for network security and how biometrics was used for the authentication, key generation purposes and security purposes in the network. The proposed techniques are compared on the basis of the parameters to prove its efficiency.
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    SURVEY ON BLACK HOLE AND GRAY HOLE ATTACKS IN MANET
    (International Journal of Computer Sciences and Engineering, 2016-05) Nachammai M; Radha N
    Mobile Ad hoc Network (MANET) is one of the most promising technologies in the recent years. In MANET, a wireless network is quickly formed using mobile nodes. Because of its characteristics such as open and undefined medium, limited resources, offering a secure data transmission in presence of malicious nodes in the network is main issues of the MANET. The black hole and gray hole attacks are major security threats in MANET, in which the packets are dropped in intermediate nodes. The main objective of this paper is to study the techniques used to eliminate the packet drop in intermediate nodes using malicious node detection techniques. In this paper, various malicious node detection methods such as Local anomaly detection and Cooperative anomaly detection, Fuzzy and wavelet transform based IDS system, Modified DSR protocol , Kullback-Leibler divergence approach, FireCol , hash function based method and cooperative bait detection scheme (CBDS) are studied and analyzed. The findings of this work proved that the cooperative bait detection achieves better results than the other approaches in terms of packet delivery ratio and end-to-end delay.
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    DIAGNOSIS OF CHRONIC KIDNEY DISEASE USING MACHINE LEARNING ALGORITHMS
    (International Journal of Innovative Research in Computer and Communication Engineering, 2016-01) Radha N; Ramya S
    Chronic Kidney Disease (CKD) is a gradual decrease in renal function over a period of several months or years. Diabetes and high blood pressure are the most common causes of chronic kidney disease. The main objective of this work is to determine the kidney function failure by applying the classification algorithm on the test result obtained from the patient medical report. The aim of this work is to reduce the diagnosis time and to improve the diagnosis accuracy using classification algorithms. The proposed work deals with classification of different stages in chronic kidney disease according to its severity. The experiment is performed on different algorithms like Backpropagation Neural Network, Radial Basis Function and Random Forest. The experimental results show that the Radial basis function algorithm gives better result than the other classification algorithms and produces 85.3% accuracy
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    CANCELABLE MULTIMODAL BIOMETRIC AUTHENTICATION SYSTEM WITH DISTORTION ALGORITHM
    (International Journal for Research in Technological Studies, 2015-08) Janani B; Radha N
    Biometrics refers to authentication techniques that rely on humans physical and behavioral characteristics that can be automatically checked. Biometric based authentication system provides robust security and ease of use than conventional methods of verification system. Multimodal biometric system is one of the major areas of study identified with large applications in recognition system. Unimodal biometric systems challenge with a wide variety of problems such as noisy data, Intra-class variations, non-universality, and spoof attacks. Some of these limitations can be solved in multimodal biometric system. In proposed work, face and fingerprint biometric traits are used for multimodal biometric authentication system. Biometric traits are transformed using distortion algorithm. After the transformation processes pre-processing of images are done to improve the clear visibility of images. The extractions of minutiae feature from fingerprint are achieved using Crossing Number concept and the face features are extracted using the Local Binary Pattern algorithm. To combine both the face and fingerprint features feature level fusion is used. In order to provide additional security to the proposed work the fuzzy vault is introduced by adding duplicate values and having a secret key to lock and unlock the system. Fuzzy vault and distortion acts as an additional layer of security in multimodal biometric user authentication system.
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    CANCELABLE TEMPLATE GENERATION BASED ON IMPROVED QUALITY FINGERPRINT IMAGE FOR PERSON AUTHENTICATION
    (International Journal of Computer Sciences & Engineering, 2015-01) Janani B; Radha N
    Biometric based authentication system provides robust security and ease of use than conventional methods of verification system. Among various biometrics namely iris, face and gait recognition, Fingerprint recognition has been extensively used by several organizations for recognition and authentication purpose because of its low cost, usability and reliable performance. However, the performance of fingerprint identification techniques is extensively depending on the quality of the input fingerprint images. Due to the context of the image-acquisition process, most of the fingerprint images are found to be low or lack in quality. By concerning privacy issues, these types of low-quality fingerprint templates are easily accessible by intruders, thereby lacks the security. To address this issue, the present work proposes quality enhanced, secured biometric template which simultaneously combines the quality enhancement and cancellable template generation techniques for robust authentication purpose. The fingerprint quality can be improved by means of two-phase enhancement technique, learns the acquired input image by enhancing spatial and frequency domain of image respectively. After that, the cancellable fingerprint templates are generated by means of transforming the quality enhanced fingerprint minutiae distortedly by using Distortion Transformation. Experimental results show that the proposed algorithm efficiently holds various input image contexts and attains improved results in terms of quality and security when compared with some state-of-the-art methods, and thus improves the fingerprint-authentication systems performance.
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    PERFORMANCE ANALYSIS OF MACHINE LEARNING ALGORITHMS FOR PREDICTING CHRONIC KIDNEY DISEASE
    (International Journal of Computer Sciences &Engineering, 2015-07) Radha N; Ramya S
    chronic kidney disease refers to the condition of kidneys caused by conditions, diabetes, glomerulonephritis or high blood pressure. These problems may happen gently for a long period of time, often without any symptoms. It may eventually lead to kidney failure requiring dialysis or a kidney transplant to preserve survival time. So, the primary detection and treatment can prevent or delay of these complications. The aim of this work is to reduce the diagnosis time and to improve the diagnosis accuracy through classification algorithms. The proposed work deals with classification of different stages in chronic kidney diseases using machine learning algorithms. The experimental results performed on different algorithms like Naive Bayes, Decision Tree, K-Nearest Neighbor and Support Vector Machine. The experimental result shows that the K-Nearest Neighbor algorithm gives better result than the other classification algorithms and produces 98% accuracy
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    A SURVEY ON VISUAL CRYPTOGRAPHY SHARES
    (INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY, 2015-03) Radha N; Nandhinipreetha A
    Visual cryptography is used to keep the information secure from unauthorized person by encrypting it. The performance of the visual cryptography is measured in different ways such as pixel expansion, security, contrast, number of secret images, and the type of share generated. The main intent of this paper is to study and examine the visual cryptographic shares (i.e.) meaningless or meaningful share for binary and color images