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In data analysis, anomaly detection (also referred to as outlier detection and sometimes as novelty detection) is generally understood to be the identification of rare items, events or observations which deviate significantly from the majority of the data and do not conform to a well defined notion of normal behavior. [1]
Network behavior anomaly detection (NBAD) is a security technique that provides network security threat detection. It is a complementary technology to systems that detect security threats based on packet signatures. [1] NBAD is the continuous monitoring of a network for unusual events or trends.
The existence of DOM clobbering has been known since at least 2010, when a paper from researchers from University of California, Berkeley and Carnegie Mellon University demonstrated an attack where an iframe called self could be used to navigate a page to a different page, violating the same-origin policy.
In order to positively identify attack traffic, the system must be taught to recognize normal system activity. The two phases of a majority of anomaly detection systems consist of the training phase (where a profile of normal behaviors is built) and testing phase (where current traffic is compared with the profile created in the training phase ...
In anomaly detection, the local outlier factor (LOF) is an algorithm proposed by Markus M. Breunig, Hans-Peter Kriegel, Raymond T. Ng and Jörg Sander in 2000 for finding anomalous data points by measuring the local deviation of a given data point with respect to its neighbours.
Visualization of a software buffer overflow. Data is written into A, but is too large to fit within A, so it overflows into B.. In programming and information security, a buffer overflow or buffer overrun is an anomaly whereby a program writes data to a buffer beyond the buffer's allocated memory, overwriting adjacent memory locations.
With cognitive change detection, researchers have found that most people overestimate their change detection, when in reality, they are more susceptible to change blindness than they think. [18] Cognitive change detection has many complexities based on external factors, and sensory pathways play a key role in determining one's success in ...
Novelty detection is the mechanism by which an intelligent organism is able to identify an incoming sensory pattern as being hitherto unknown. If the pattern is sufficiently salient or associated with a high positive or strong negative utility , it will be given computational resources for effective future processing.