Fundamentals of computer security technology

By E. Amoroso. 1994

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

The Limitations of Deep Learning in Adversarial Settings (2015, methodology): “nclude by studying human perception of distorted samples. II. TAXONOMY OF THREAT MODELS IN DEEP LEARNING Classical threat models enumerate the goals and capabilities of adversaries in a target domain [1]. This section taxonimizes threat models in deep learning systems and positions several previous ”
A taxonomy of network and computer attacks (2005, background): “A number of requirements have been compiled from various sources in Lough (2001) and are listed below: Accepted (Amoroso, 1994; Howard, 1997): The taxonomy should be structured so that it can become generally approved.”
DAG-based attack and defense modeling: Don't miss the forest for the attack trees (2013, methodology): “Inspired by research in the reliability area, Weiss [286] in 1991 and Amoroso [9] in 1994 proposed to adopt a tree-based concept of visual system reliability engineering to security.”
Addressing privacy requirements in system design: the PriS method (2008, methodology): “Moreover, the activity of privacy goal elicitation could benefit from a number of other techniques such as: threat trees [ 41 ], attack trees [42], abuse cases [43], misuse cases [44‐ 46], security use cases [45] and abuse frames [48].”
Fuzzing for Software Security Testing and Quality Assurance (2008, background): “7Edward Amoroso. (1994). Fundamentals of Computer Security Technology.”
Concepts, Techniques, and Models of Computer Programming (2004, background): “What is the output? Is the result any different from the result of the sequential call {ForAll [1 2 3 4] Browse}? What is the effect of using ForAll in a concurrent setting?”