We investigate potential simulation artifacts and their effects on the evaluation of network anomaly detection systems in the 1999 DARPA/MIT Lincoln Laboratory off-line intrusion detection evaluation data set. A statistical comparison of the simulated background and training traffic with real traffic collected from a university departmental server suggests the presence of artifacts that could a...

| Detection of incipient (slowly developing) faults is crucial in automated maintenance problems where early detection of worn equipment is required. In this note, a general framework for model-based fault detection and diagnosis of a class of incipient faults is developed. The changes in the system dynamics due to the fault are modeled as nonlinear functions of the state and input variables, w...

This paper deals with a software modification strategy allowing on-line detection of transient errors. Being based on a set of rules for introducing redundancy in the highlevel code, the method can be completely automated, and is therefore particularly suited for low-cost safety-critical microprocessor-based applications. Experimental results are presented and discussed, demonstrating the effec...

This paper presents a new technique for on-line consistency checking of embedded DRAMs. The basic idea is to use the periodic refresh operation for concurrently computing a test characteristic of the memory contents and compare it to a precomputed reference characteristic. Experiments show that the proposed technique significantly reduces the time between the occurrence of an error and its dete...

This paper deals with condition-based maintenance and non-stationary degradation process due to sudden changes. This is an attempt to propose an adaptive maintenance policy based on the on-line change detection procedure which can help to detect switches from a nominal mode to an accelerated mode in a non informative context about the change mode time.

The DARPA/MIT Lincoln Laboratory off-line intrusion detection evaluation data set is the most widely used public benchmark for testing intrusion detection systems. But the presence of simulation artifacts attributes would cause many attacks in this dataset to be easily detected. In order to eliminate their influence on intrusion detection, we simply omit these attributes in the processes of bot...

Intrusion detection is an active research field in the development of reliable web-based information systems, where many artificial intelligence techniques are exploited to fit the specific application. Although some detection algorithms have been developed, they lack the adaptability to the frequently changing network environments, since they are mostly trained in batch mode. In this paper, we...

Data mining technology is applied to fraud detection to establish the fraud detection model, describe the process of creating the fraud detection model, then establish data model with ID3 decision tree, and establish example of fraud detection model by using this model. As e-commerce sales continue to grow, the associated online fraud remains an attractive source of revenue for fraudsters. Thes...

Online consumers must burrow through vast piles of product information to find the best match to their preferences. This has boosted the popularity of recommendation agents promising to decrease consumers' search costs. Most recent work has focused on refining methods to find the best products for a consumer. The question of how many of these products the consumer actually wants to see, however...