Papers by shyamala loganathan
International Journal of Intelligent Engineering and Systems
Distributed Denial of Service attacks are becoming a serious issue for the developers and the use... more Distributed Denial of Service attacks are becoming a serious issue for the developers and the users of the Internet. In recent times, the attackers are targeting the online applications and web services. Detecting such application level attacks are much challenging because the attack traffic mimics the legitimate behaviour. A more sophisticated mechanism is required to detect and mitigate such attacks. In this paper, a novel method for detecting application layer Distributed Denial of Service attack is proposed. Initially, web user behaviour on different perspectives is analyzed using the system log and key dimensions that are highly responsive to attacks are identified using Principal Component Analysis. The extracted key features are analyzed to fix up the appropriate thresholds for differentiating legitimate and illegitimate access. Each incoming session is examined and if found suspicious, the detection mechanism is invoked. The detection mechanism includes a score assignment mechanism which assigns the threat score based on the history and statistical analysis of the current characteristics. The sessions having acceptable score are then scheduled to get service from the server. Remaining sessions are considered malicious and dropped. The real data sets are taken for the simulation and the results are exhibited to show the efficiency of the proposed detection method. The results show that the proposed technique performs effective detection of constant flooding and repeated shot attacks with low false positives and low false negatives.
The Scientific World Journal, 2015
Cloud computing is an on-demand computing model, which uses virtualization technology to provide ... more Cloud computing is an on-demand computing model, which uses virtualization technology to provide cloud resources to users in the form of virtual machines through internet. Being an adaptable technology, cloud computing is an excellent alternative for organizations for forming their own private cloud. Since the resources are limited in these private clouds maximizing the utilization of resources and giving the guaranteed service for the user are the ultimate goal. For that, efficient scheduling is needed. This research reports on an efficient data structure for resource management and resource scheduling technique in a private cloud environment and discusses a cloud model. The proposed scheduling algorithm considers the types of jobs and the resource availability in its scheduling decision. Finally, we conducted simulations using CloudSim and compared our algorithm with other existing methods, like V-MCT and priority scheduling algorithms.
Differentiated Policy Based Job Scheduling with Queue Model and Advanced Reservation Technique in a Private Cloud Environment
Lecture Notes in Computer Science, 2013
Role of Broker in InterCloud Environment
Computer Communications and Networks, 2014
A Comparison of Machine Learning and Deep Learning Methods with Rule Based Features for Mixed Emotion Analysis
International Journal of Intelligent Engineering and Systems
Multi-class classification of sentiments from text data still remains a challenging task to detec... more Multi-class classification of sentiments from text data still remains a challenging task to detect the sentiments hidden behind the sentences because of the probable existence of multiple meanings for some of the texts in the dataset. To overcome this, the proposed rule based modified Convolutional neural network-Global Vectors (RCNN-GloVe) and rule-based modified Support Vector Machine - Global Vectors (RSVM-GloVe) were developed for classifying the twitter complex sentences at twelve different levels focusing on mixed emotions by targeting abstract nouns and adjective emotion words. To execute this, three proposed algorithms were developed such as the optimized abstract noun algorithm (OABNA) to identify the abstract noun emotion words, optimized complex sentences algorithm (OCSA) to extract all the complex sentences in a tweet precisely and adjective searching algorithm (ADJSA) to retrieve all the sentences with adjectives. The results of this study indicates that our proposed RC...
A cloud system uses virtualization technology to provide cloud resources (e.g. CPU, memory) to us... more A cloud system uses virtualization technology to provide cloud resources (e.g. CPU, memory) to users in form of virtual machines. Job requests are assigned on these VMs for execution. Efficient job assignment on VMs will reduce the number of hosts used. Hence, it is essential to achieve energy optimization in cloud computing environments. Therefore, in this paper, a job scheduling mechanism is proposed to assign job to a VM of the existing active hosts itself by considering job classification and preemption. So that minimizing the number of host used in allocation intern reduces the energy consumption in the Cloud datacenter. In our proposed job scheduling algorithm, categorizing the job in to three different types and assigned based on preemption policy with the earliest available time of the resource (VM) which is attached to a host. Thereby, we reduce the energy consumption by making less number of hosts in the active state and increase the utilization of active host. Finally, we conduct simulations using CloudSim and compare our algorithm with other existing methods. Significant energy savings can be obtained depending on system loads. Energy saving is about 2% to 46% with respect to the non-energy aware algorithm, 1% to 7% than the energy aware algorithms.
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Papers by shyamala loganathan