Circulation in the indian ocean in relation to the monsoon circulation of the atmosphere

The present thesis is an attempt by the researcher to Investigate the surface circulation of the Indian Ocean, north of 2095 in relation to the atmospheric circulation over the ocean. The aim is achieved by working out the circu1ation pattern and correlating it with the computed wind stress and its vorticity. The month wise surface circulation is arrived by drawing the streamlines, using freshand method with superimposed isotache. The zonal ad meridional componance of the wind stress and the curl of the wind stress are computed for each month over 2° latitude longitude quadrangle from the bulk aerodynamic formula, using a computer program. The data for drawing the surface circu1ation and for computing the wind stress and its curl have come from the Dutch Atlas.

An Alternative Approach To Computer System Security Monitoring And Enhancement Through System Call Sequence Analysis

Modern computer systems are plagued with stability and security problems: applications lose data, web servers are hacked, and systems crash under heavy load. Many of these problems or anomalies arise from rare program behavior caused by attacks or errors. A substantial percentage of the web-based attacks are due to buffer overflows. Many methods have been devised to detect and prevent anomalous situations that arise from buffer overflows. The current state-of-art of anomaly detection systems is relatively primitive and mainly depend on static code checking to take care of buffer overflow attacks. For protection, Stack Guards and I-leap Guards are also used in wide varieties.This dissertation proposes an anomaly detection system, based on frequencies of system calls in the system call trace. System call traces represented as frequency sequences are profiled using sequence sets. A sequence set is identified by the starting sequence and frequencies of specific system calls. The deviations of the current input sequence from the corresponding normal profile in the frequency pattern of system calls is computed and expressed as an anomaly score. A simple Bayesian model is used for an accurate detection.Experimental results are reported which show that frequency of system calls represented using sequence sets, captures the normal behavior of programs under normal conditions of usage. This captured behavior allows the system to detect anomalies with a low rate of false positives. Data are presented which show that Bayesian Network on frequency variations responds effectively to induced buffer overflows. It can also help administrators to detect deviations in program flow introduced due to errors.