Information security-conscious managers of organizations have the responsibility to advise their senior management of the level of risks faced by the information systems. This requires managers to conduct vulnerability assessment as the first step of a risk analysis approach. However, a lack of real world data classification of security threats and develops a three-axis view of the threat space. It develops a scheme for probabilistic evaluation of impact of the security threats and proposes a risk management system consisting of a five-step approach. The goal is to assess the expected damages due to attacks, and managing the risk of attacks.

Understanding network traffic from operational networks is critical to the design and evaluation of network protocols. We present analysis of a data set comprised of eight months of RADIUS authentication data taken from a large national dial-up Internet Service Provider (ISP). We present basic statistics, including session counts based on time-of-day, session length distribution, session inter-arrival times, and growth in the customer base over the measurement period. We investigate more deeply several properties of the data. We use area code information to correlate account location with basic statistics. For example, we find that United States west coast accounts tend to have earlier-than-average mean session start time. We find that 40% of sampled accounts exhibit concurrent sessions (two or more sessions active at the same time), while 20% show multiple originating phone numbers. Both phenomenon are likely to increase as users become more mobile and sophisticated. Finally, we offer evidence of significant session activity due to hypothesized automated processes, characterized by periodic interarrival times and/or constant session durations. Our results provide important data for the simulation and modeling of access network protocols and applications. They may also form the basis for creating a workload model of access networks.

Integrated schemes of routing, flow control, and congestion control in packet-switched networks are investigated for performance optimization. After the control parameters and objective function are introduced, an efficient method is derived to compute the gradient vector and Hessian matrix of such an objective function. The method, used with a general nonlinear programming strategy, solves this nonlinear optimization problem. Several examples which showed efficient and stable behavior were investigated. The results obtained by the proposed method are compared with exact values and are shown to be accurate.>