Probability and Statistics in the Engineering and Computing Sciences
Probability and Statistics in the Engineering and Computing Sciences
Code red worm propagation modeling and analysis
Proceedings of the 9th ACM conference on Computer and communications security
Data Mining by Means of Binary Representation: A Model for Similarity and Clustering
Information Systems Frontiers
Recent worms: a survey and trends
Proceedings of the 2003 ACM workshop on Rapid malcode
Phishing: Cutting the Identity Theft Line
Phishing: Cutting the Identity Theft Line
Quantifying the benefits of investing in information security
Communications of the ACM - Scratch Programming for All
Towards controlling virus propagation in information systems with point-to-group information sharing
Decision Support Systems
Performance analysis of email systems under three types of attacks
Performance Evaluation
Effective immunization of online networks: a self-similar selection approach
Information Technology and Management
| Hi-index | 0.00 |
This paper develops a methodology for analyzing and predicting the impact category of malicious code, particularly email worms. The current paper develops two frameworks to classify email worms based on their detrimental impact. The first framework, the Total Life Impact (TLI) framework is a descriptive model or classifier to categorize worms in terms of their impact, after the worm has run its course. The second framework, the Short Term Impact (STI) framework, allows for prediction of the impact of the worm utilizing the data available during the early stages in the life of a worm. Given the classification, this study identifies the issue of how well the STI framework allows for prediction of the worm into its final impact category based on data that are available in early stages as well as whether the predicted value from Short Term Impact framework valid statistically and practically.