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Author: search.filters.author.A, Kavitha

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    DEFENDING AGAINST COLLABORATIVE ATTACKS BY MALICIOUS NODES IN MANETS: A COOPERATIVE BAIT DETECTION APPROACH
    (KSG college of Arts and Science, 2019) A, Kavitha
    A Mobile Adhoc NETwork (MANET) is a type of ad hoc network that can change locations and configure itself on the fly. Because MANETS are mobile, they use wireless connections to connect to various networks. However the flexibility of these characteristic creates the security threats. Security is an important issue for mobile ad hoc networks, due to the vulnerable nature of MANETs. This flexibility comes at a price and introduces new security threats. Furthermore, many conventional security solutions used for wired networks are ineffective and inefficient for the highly dynamic and resource-constrained environments where MANET use might be expected. To develop suitable security solutions for such new environments, must first understand how MANETs can be attacked. The nodes in the network can be easily affected by collaborative attacks such as blackhole attack, grayhole attack and jellyfish attacks. A cooperative bait detection approach is proposed against the collaborative attacks. The comparison was made between the different techniques that have been listed. The performance evaluation conducted was proved that the each and every method has unique advantage and disadvantages among each other.
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    AN ANALYSIS OF DEEP LEARNING APPROACH IN WIRELESS NETWORK
    (KSG College of Arts and Science, 2018) A, Kavitha; L, Sheeba
    Intrusion detection has attracted a considerable interest from researchers and industries. The community, after many years of research, still faces the problem of building reliable and efficient IDS that are capable of handling large quantities of data, with changing patterns in real time situations. The work presented in this manuscript classifies intrusion detection systems (IDS). Moreover, a taxonomy and survey of shallow and deep networks intrusion detection systems is presented based on previous and current works. This taxonomy and survey reviews machine learning techniques and their performance in detecting anomalies. Feature selection which influences the effectiveness of machine learning (ML) IDS is discussed to explain the role of feature selection in the classification and training phase of ML IDS.. Deep learning, as one of the most currently remarkable machine learning techniques, has achieved great success in many applications such as image analysis, speech recognition and text understanding. It uses supervised and unsupervised strategies to learn multi-level representations and features in hierarchical architectures for the tasks of classification and pattern recognition. In this paper, we review the emerging researches of deep learning models for NIDS feature learning. Furthermore, we point out the remaining challenges of Intrusion detection system deep learning and discuss the future topics.
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    SURVEY ON MANET ROUTING PROTOCOLS FOR SECURED DATA TRANSMISSION
    (Sri Ramakrishna College of Arts and Science, 2017) A, Kavitha; V S, Meenakshi
    MANET is a Ad Hoc network in which a large number of nodes are connected wirelessly. It is used in different areas like military, disaster recovery etc. The nodes present in this network are openness and decentralized. MANET is frequently changing its topologies to transfer the data quickly, because nodes in this network are moving always (mobility) and data transfer has been done by finding the efficient routing path between source and destination. Due to the mobility there is a lot of chance to involve malicious node and the network will become more vulnerable to attacks like gray hole and black hole attack etc. These types of attacks affect the MANET routing path and it hence it is necessary to secure routing. To overcome the security problem, single or multilayer security algorithm is needed to link with protocol. In this paper, a survey is made of various kinds of existing protocols and algorithms involved are discussed.