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Rajeswari, R.
- Malware Clearance for Secure Commitment of OS-Level Virtual Machines
Authors
1 Masters Degree Program in Computer Science Engineering, MPNMJ Engineering College, Anna University, IN
2 Computer Science Department, MPNMJ Engineering College, Anna University, IN
Source
Automation and Autonomous Systems, Vol 6, No 4 (2014), Pagination: 107-110Abstract
The number and complexity of attacks on computer systems are increasing. This growth necessitates proper defense mechanisms. Intrusion detection systems play an important role in detecting and disrupting attacks before they can compromise software. The Secom prototype can effectively eliminate malicious state changes while committing a VM with small performance degradation. The Secom prototype has a smaller number of false negatives and thus can more thoroughly clean up malware side effects. In addition, the number of false positives of the Secom prototype is also lower than that achieved by the online behavior-based approach of the commercial tools. Multivariant execution is an intrusion detection mechanism that executes several slightly different versions, called variants, of the same program in lockstep. The variants are built to have identical behavior under normal execution conditions. However, when the variants are under attack, there are detectable differences in their execution behavior. At runtime, a monitor compares the behavior of the variants at certain synchronization points and raises an alarm when a discrepancy is detected. The project presents a monitoring mechanism that does not need any kernel privileges to supervise the variants. Many sources of inconsistencies, including asynchronous signals and scheduling of multithreaded or multiprocess applications, can cause divergence in behavior of variants. These divergences cause false alarms.Keywords
False Positives, Kernel Privileges, Malicious State Changes, Multivariant Execution.
- Performance Analysis of LFC of Two Area System Using Intelligent Controllers
Authors
1 Department of Electrical Engineering, GCT, Coimbatore, IN
2 Department of Electrical Engineering, Government College of Technology, Coimbatore, IN
Source
Automation and Autonomous Systems, Vol 4, No 4 (2012), Pagination: 126-129Abstract
The main aim of LFC in a power system is to maintain the system frequency at its scheduled value during normal period and whenever there is a change in load demand. Larger frequency deviation for change in load will lead to system collapse. Thus a fast and accurate controller is required to maintain the system at nominal frequency. Various Intelligent Controllers are employed for performing LFC in a power system for obtaining better dynamic performance. This paper represents the analysis of Load Frequency Control of Two Area Thermal-Thermal System using Intelligent Controllers like Fuzzy Logic Controller (FLC), Artificial Neural Network (ANN) and Adaptive Neuro- Fuzzy Inference System (ANFIS).. The performances of the controllers are examined for 2GW rated control areas interconnected by tie-lines for a step load change of 0.1p.u. Change in frequency and settling time is observed for various controllers using MATLAB SIMULINK. The results obtained shows that ANN gives faster dynamic performance than other controllers.
Keywords
Load Frequency Control (LFC), Area Control Error (ACE), Fuzzy Logic Controller (FLC), Adaptive Neuro Fuzzy based Inference System (ANFIS), Artificial Neural Network (ANN).- Comparative Study of Intelligent Techniques of Controller Design for Nonlinearities in Continuous Stirred Tank Reactor
Authors
1 Department of EEE, Erode Sengunthar Engineering College, IN
2 Department of EEE, Government College of Technology, Coimbatore, IN