The Deterministic Dendritic Cell Algorithm

Greensmith, Julie; Aickelin, Uwe

doi:10.1007/978-3-540-85072-4_26

Cited by 122 publications

(108 citation statements)

References 13 publications

(19 reference statements)

Supporting

Mentioning

107

Contrasting

Unclassified

Order By: Relevance

“…For further information regarding the function of natural DCs and the details of the DCA can be found in [8].…”

Section: Dendritic Cell Algorithm (Dca)mentioning

confidence: 99%

Detecting Software Keyloggers with Dendritic Cell Algorithm

Liang

Tan

et al. 2010

2010 International Conference on Communications and Mobile Computing

View full text Add to dashboard Cite

As a kind of invisible spyware that records user's keystrokes, software keyloggers have posed a great threat to user privacy and security. It is difficult to detect keyloggers because they run in a hidden mode. In this paper, an immuneinspired dendritic cell algorithm (DCA) was used to detect the existence of keyloggers on an infected host machine. The basis of the detection is facilitated through the correlation (including the timing relationships) between different behaviors such as keylogging, file access and network communication. The results of the experiments show that it is a successful technique for the detection of keyloggers without responding to normally running programs.

show abstract

“…For further information regarding the function of natural DCs and the details of the DCA can be found in [8].…”

Section: Dendritic Cell Algorithm (Dca)mentioning

confidence: 99%

Detecting Software Keyloggers with Dendritic Cell Algorithm

Liang

Tan

et al. 2010

2010 International Conference on Communications and Mobile Computing

View full text Add to dashboard Cite

show abstract

“…All raw signals are derived using signal collection scripts, with values taken from the/proc filesystem (PAMP-1, DS-1, SS-1, I), the tcpstat linux utility (DS-2, SS-2) and a custom developed packet sniffer (PAMP-2). The system parameters used with the DCA are shown in Table 6 derived as a result of previous DCA sensitivity analysis [24]. Weights for the signal processing of these data are shown in Table 7.…”

Section: Methodsmentioning

confidence: 99%

The DCA: SOMe comparison

2008

Self Cite

View full text Add to dashboard Cite

The dendritic cell algorithm (DCA) is an immune-inspired algorithm, developed for the purpose of anomaly detection. The algorithm performs multi-sensor data fusion and correlation which results in a 'context aware' detection system. Previous applications of the DCA have included the detection of potentially malicious port scanning activity, where it has produced high rates of true positives and low rates of false positives. In this work we aim to compare the performance of the DCA and of a selforganizing map (SOM) when applied to the detection of SYN port scans, through experimental analysis. A SOM is an ideal candidate for comparison as it shares similarities with the DCA in terms of the data fusion method employed. It is shown that the results of the two systems are comparable, and both produce false positives for the same processes. This shows that the DCA can produce anomaly detection results to the same standard as an established technique.

show abstract

“…Artificial neural networks and dendritic cell algorithms, to name a few, have been successfully utilized to aid in the development of tools and/or understanding of robotics [1], finance [2], artificial immunology [3], public opinion [4], differential equations [5,6], and physics education [7]. Here, we demonstrate that dendritic growth model in a confined substrate can be used to capture the empirical features of multilevel marketing (MLM) schemes.…”

Section: Introductionmentioning

confidence: 98%