2. Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/1/7

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    Monitoring and Management of Service Level Agreements in Cloud Computing
    (2015) Anithakumari, S.; Chandrasekaran, K.
    Cloud computing environment consists of various interactive entities like cloud service providers, cloud service brokers, cloud customers and end-users with different objectives and expectations. Service Level Agreements (SLAs) manage the relationship among cloud service providers and cloud consumers by defining the terms of the agreement for the participating entities and provide the basic ground for interactions among both the parties. In this work we proposed a framework to efficiently monitor and analyze the SLA parameters and tried to find out the possibility of occurrence of SLA violations. Also we implemented an adaptive resource allocation system by utilizing the results of predicted SLA violations. Our adaptive resource allocation system allocates computing resources to cloud applications and tries to reduce the occurrence of SLA violations, by allocating additional resources on the detection of possibility of occurrence of a violation. The experimental studies show that our proposed system works well in private cloud computing environment and gives more efficient results. � 2015 IEEE.
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    Remote Surveillance Robot System-A Robust Framework Using Cloud
    (2016) Sundaram, A.; Gupta, M.; Rathod, V.; Chandrasekaran, K.
    Today's technology provides a rather convenient way for developer community to develop an integrated network environment for the diversified applications of various robotic systems. Internet based robotic systems have been gaining importance of late and we explore one such application in the field of remote surveillance. Even though direct control has potential difficulties due to unpredictable delay, recent technological advances have reduced this to a large extent. This paper describes a direct model of robot control. The system uses standard protocol and a machine-human interface. Using a Web browser (thin client), a remote user can control the mobile robot to navigate in an enclosure with visual feedback via the Internet. The use of an intuitive user interface permits Internet users to access and control the mobile robot and perform useful tasks remotely, from a different location. The direct mode is implemented with the help of event driven methods which provide complete control over the robot. This paper proposes a model architecture for direct control and discusses an implementation and performance of a networked robot system with the help of Cloud computing. � 2015 IEEE.
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    Reducing DNS cache poisoning attacks
    (2015) Mohan, J.; Puranik, S.; Chandrasekaran, K.
    The increasing attacks on The Domain Name System (DNS) and the problems faced in deploying Domain Name System Security Extensions (DNSSEC) on a large scale, result in the need of a simple, and a practical approach to safeguard the DNS. In this paper, we present an efficient approach to significantly reduce the success rate of DNS cache poisoning attacks. The proposed Shift Key(S-Key) based domain name encoding scheme considerably raises the entropy of the DNS packet by encoding the domain name, using the randomly generated 4 bit S-Keys. To successfully poison a DNS cache, the attacker must now guess the 4 bit S-key as well as the encoded domain name, in addition to the port number and the transaction ID. The Bi-Query scheme captures the malicious reply packets by initiating a re-query or pairing up two consecutive requests to resolve the same domain name, thereby validating the Internet Protocol (IP) address retrieved for each domain name, before caching it. The first method proposed makes it difficult for the attacker to guess the DNS packet fields, while the latter detects and discards any packet that has been forged. � 2015 IEEE.
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    Recursive Harmony Search Based Classifier Ensemble Reduction
    (2019) Kailas, P.; Chandrasekaran, K.
    In recent times classifier ensembles have become a mainstay in data mining and machine learning. The combination of several classifiers generally results in better performance and accuracy as compared to a single classifier. There are many different methods and techniques for constructing ensembles. Most of the time however, when these ensemble classifiers are constructed, the data used in the construction of ensemble classifiers becomes redundant. This redundant data results in a loss of accuracy and an increase in memory and system overhead. Therefore by removing this redundant data we can reduce the memory and system overhead as well as obtain an increase in accuracy. The redundant data can be eliminated by using a technique called feature selection. Feature selection is used to select the most relevant features while performing any task. There are many different feature selection algorithms such as memetic algorithms, sub-modular feature selection, etc. The feature selection technique can be used to choose the relevant data and eliminate the redundant data. The way to eliminate redundant data in ensemble classifiers is to perform classifier ensemble reduction. This paper discusses using feature selection and in particular employing recursive harmony search to perform classifier ensemble reduction via feature selection. The final ensemble classifier will be a reduced set of the original ensemble classifier, while maintaining diversity and accuracy of the original one. � 2018 IEEE.
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    Paving the way for autonomic clouds: State-of-the-art and future directions
    (2018) Joseph, C.T.; Chandrasekaran, K.
    Cloud Computing is the core technology that helps in catering to the computing needs of the current generation. As the customers increase, data center providers are looking for efficient mechanisms to handle the management of the large reservoir of resources involved in the Cloud environment. In order to support efficient managing, it is the need of the day to adopt the concept of Autonomic Computing into Cloud. Several researchers have been attempted to improve the managing capability of the Cloud, by encorporating autonomic capabilities for resources in the Cloud. Most of the researches attempt to automate some aspects while the remaining portion of the Cloud does not have autonomic functionalities. An autonomic Cloud is one where all the operations can be handled without human intervention. There is a long way to go to achieve this vision. In our study, we first categorize the various existing approaches on the basis of the methodology employed and analyze the different self-*properties considered by the different approaches. It is observed that in each approach, researchers focus on one or at most two self-*properties. Based on our analysis, we suggest some of the future directions that can be paved on by researchers working in this domain. � 2018, Springer Nature Singapore Pte Ltd.
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    Optimization-Aware scheduling in cloud computing
    (2016) Binu, A.; George, N.; Chandrasekaran, K.
    Cloud computing allows delivery of computational resources via internet. Some of the computational resources include signals, codes and physical resources. Cloud users require computational resources for execution of their tasks. The computational elements, when thoroughly assigned to the cloud users according to requirement facilitate an efficient scheduling mechanism. The efficiency is dependent on the parameters chosen to promote the assignment of task to resources. Here, computational cost is chosen as the optimization factor, and the solution with the least cost is selected as the best assignment. A Cuckoo Search inspired technique is used, and task assignment to resources is done by validating the solution with the least value of cost. � 2016 ACM.
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    Optimized cryptographic algorithm for embedded systems
    (2016) Deshmukh, A.A.; Jothish, M.; Chandrasekaran, K.
    Cryptographic hash algorithms have gained widespread popularity over its algorithmic complexity and the impossibility of recreation of the original input from the message digest. Embedded systems employ such algorithms for its security after substantial modifications in order to meet the hardware specifications due to the parsimonious capacity of such systems. Efficacious hashing algorithms lucidly adhere to all performance constraints and therein lies its popularity. We propose an optimization of the Secure Hashing Algorithm 1 (SHA-1) in memory requirements to suit the environment of an embedded system. We explore the idea of simplifying SHA-1's complicated set of steps to quicken its execution through loop reduction and lookup buffers stored in the main memory. � 2015 IEEE.
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    Ontologies to Model User Profiles in Personalized Job Recommendation
    (2019) Rimitha, S.R.; Abburu, V.; Kiranmai, A.; Chandrasekaran, K.
    Personalized recommendation aims to provide results that are likely to be of interest to a particular user. Personalized recommendation is useful in the domain of job search in order to provide individuals more personalized recommendations of job listings based on their preferences. User profiles a re thus constructed based on the individual users preferences. On the other hand, user profiles a re helpful in improving the recommendations. In general, user profiles are structured based on the individual's preferences. User profiles can be represented in various ways, one such way is ontology which is the systematic categorization and representation of relationships between various entities within a domain. Ontologies has been widely used in the domain of e-commerce and medicine. In this paper, we use ontologies in the domain of personalized job recommendation, to model user profiles. The major objective of this paper is to provide an ontology based user profile for the domain of job recommendation. In particular, we identified suitable classes, attributes and relations that are specific to job recommendation system. In addition, we presented OWL representation of the proposed ontological model such that it can be reused by domain experts. � 2018 IEEE.
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    On-the-Fly Encryption Security in Remote Storage
    (2016) Prabhakar, A.; Savin, P.S.; Chandrasekaran, K.
    Development of distributed storage, cell phones, furthermore, removable hard drives have expanded the versatility of usage of information. On the other hand, there emerges a few issues of how to figure out if information may be so delicate it would be impossible leave a clients gadget, and, how to secure it from unauthorized access. Information Leakage Prevention applications perform this assignment, commonly by diverting possibly vulnerable documents to a protected distant repository, examining them, and at that point doing a last duplicate to remote storage if the output meets the constraints defined in the policy enforced, at that point the output is copied to distant repository. The extra work needed to basically serially write the document twice, once to local repository and lastly to the distant repository is the main issue with local repository isolation. This paper introduces a substitute technique for Information Leakage Prevention is introduced in this paper utilizing a transient cryptographic key. By utilizing a transient key, encoded information can be securely checked on distant repository and safely deleted in case it fails the policy while scanning. This direct procedure brings about better productivity and reduces the time delay than a local repository isolation. � 2015 IEEE.
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    Negotiation and monitoring of service level agreements in cloud computing services
    (2017) Anithakumari, S.; Chandrasekaran, K.
    SLAs are so significant in cloud computing because it establishes agreements between the cloud service providers and cloud consumers, about the quality of the providing service. SLA monitoring is the only available provision to check whether the agreed parties are following the agreement terms or not. A multistep SLA negotiation, which contains the selection of apt cloud service provider and the negotiation with the selected provider, is proposed here. An efficient SLA negotiation algorithm is also included in this negotiation method. Experimental evaluation shows that the proposed method is more efficient in resource allocation and it gives more revenue to the cloud providers. � Springer Science+Business Media Singapore 2017.