Running window entropy is a useful tool for malware analysis, network anomaly detection, and other cybersecurity topics. An optimized version of this algorithm would allow for inspection of more data in less time, thereby reducing wasted time and costs for an organization. This research presents a novel, non-trivial optimization of the running window entropy algorithm that, on average, requires less than 2% of the time of the original algorithm used in prior research. This savings can equate to days and months of computation time for average scenarios when applied to prior research
Sample Entropy is the most popular definition of entropy and is widely used as a measure of the regu...
This paper discusses data-based operating windows as a tool for process management and development. ...
Today, the Internet allows virtually anytime, anywhere access to a seemingly unlimited supply of inf...
The security of many cryptographic constructions depends on random number generators for providing u...
Using entropy of traffic distributions has been shown to aid a wide variety of network monitoring ap...
While monitoring, instrumented long running parallel applications generate huge amount of instrument...
This paper concentrates on the entropy estimation of time series. Two new algorithms are introduced:...
The metric of entropy provides a measure about the randomness of data and a measure of information g...
Approximate Entropy and especially Sample Entropy are recently frequently used algorithms for calcul...
Malware creators have been getting their way for too long now. String-based similarity measures can ...
Abstract- Many detection techniques against worms, denial of service attacks and botnets on the Inte...
In the diagnosis of neurological diseases and assessment of brain function, entropy measures for qua...
This paper describes a version of the fast optimization method (FOM) used to estimate the Hurst para...
EntropyMax is a new 32-bit Windows-based software that groups large matrices of grain-size distribut...
This dissertation explores functional malware classification using running window entropy and machin...
Sample Entropy is the most popular definition of entropy and is widely used as a measure of the regu...
This paper discusses data-based operating windows as a tool for process management and development. ...
Today, the Internet allows virtually anytime, anywhere access to a seemingly unlimited supply of inf...
The security of many cryptographic constructions depends on random number generators for providing u...
Using entropy of traffic distributions has been shown to aid a wide variety of network monitoring ap...
While monitoring, instrumented long running parallel applications generate huge amount of instrument...
This paper concentrates on the entropy estimation of time series. Two new algorithms are introduced:...
The metric of entropy provides a measure about the randomness of data and a measure of information g...
Approximate Entropy and especially Sample Entropy are recently frequently used algorithms for calcul...
Malware creators have been getting their way for too long now. String-based similarity measures can ...
Abstract- Many detection techniques against worms, denial of service attacks and botnets on the Inte...
In the diagnosis of neurological diseases and assessment of brain function, entropy measures for qua...
This paper describes a version of the fast optimization method (FOM) used to estimate the Hurst para...
EntropyMax is a new 32-bit Windows-based software that groups large matrices of grain-size distribut...
This dissertation explores functional malware classification using running window entropy and machin...
Sample Entropy is the most popular definition of entropy and is widely used as a measure of the regu...
This paper discusses data-based operating windows as a tool for process management and development. ...
Today, the Internet allows virtually anytime, anywhere access to a seemingly unlimited supply of inf...