The airport checkpoint security screening system is an important line of defense against the introduction of dangerous objects into the U.S. air transport system. Recently, there has been much interest in modeling these systems and to derive operating parameters which optimize performance. In general there are two performance measures of interest (i) the waiting time of the arriving entities, and (ii) the allocated screening resources and its utilization. Clearly, the traveling public would like a zero waiting time, while airports are limited both in terms of space and resource capital. The arrival and exit entity in the system are passengers. On arrival, passengers split into two sub-entities (i) bags or other carry-on items and (ii) passenger body and the two must rejoin prior to exit. There is a 1:M ratio between passengers and carry-on items with M≥0. The existing knowledge base related to the operating characteristics of ACSS processes is very limited. Almost all screening systems have a human interpretive component, as a result the screening behavior is highly variant and difficult to predict. This research studies the operating characteristics of the security screening process to develop proven relationships between inspection times and clearance rates. A descriptive model of the screening system, which identifies the design variables, operational parameters and performance measures, is defined. Screening data was collected from 18 U.S. airports (10 high volume, 5 medium volume, and 3 low volume). The data sets captured (i) passenger arrival times, (ii) X-ray inspection times, (iii) clearance decision, (iv) passenger physical inspection times, and (v) secondary carry-on item inspection times. An empirical analysis was used to generate a speed of inspection operating characteristic (SIOC) curve for each of the inspection processes. Mean inspection times are found to be much larger than what is frequently assumed in the literature. The findings showed that the inspection rate increases linearly with inspection time until the 7 second point, after which it describes a negative growth. The behavior of these relationships under different operating conditions was studied using a set of hypothesis. These include performance differences between airport types, between checkpoints within an airport, as well as the effect of increased passenger arrival rates.