Infrequent Pattern Detection for Reliable Network Traffic Analysis Using Robust Evolutionary Computation

analysis of ruin probability for insurance companies using markov chain

در این پایان نامه نشان داده ایم که چگونه می توان مدل ریسک بیمه ای اسپیرر اندرسون را به کمک زنجیره های مارکوف تعریف کرد. سپس به کمک روش های آنالیز ماتریسی احتمال برشکستگی ، میزان مازاد در هنگام برشکستگی و میزان کسری بودجه در زمان وقوع برشکستگی را محاسبه کرده ایم. هدف ما در این پایان نامه بسیار محاسباتی و کاربردی تر از روش های است که در گذشته برای محاسبه این احتمال ارائه شده است. در ابتدا ما نشا...

Robust Network Computation

In this thesis, we present various models of distributed computation and algorithms for these models. The underlying theme is to come up with fast algorithms that can tolerate faults in the underlying network. We begin with the classical message-passing model of computation, surveying many known results. We give a new, universally optimal, edge-biconnectivity algorithm for the classical model. ...

Behavioral Analysis of Traffic Flow for an Effective Network Traffic Identification

Fast and accurate network traffic identification is becoming essential for network management, high quality of service control and early detection of network traffic abnormalities. Techniques based on statistical features of packet flows have recently become popular for network classification due to the limitations of traditional port and payload based methods. In this paper, we propose a metho...

Hybrid Network Anomaly Detection – Learning HMMs Through Evolutionary Computation

DP Matching Approach for Streaming Contents Detection Using Traffic Pattern

Since the video streaming technology has become widespread, the security of video contents has gained more importance. Our research group previously envisioned a video leakage detection method for streaming contents that makes use of traffic patterns extracted from only traffic volume information obtained from routers. However, as the background traffic increases, packet delay and jitter increa...