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Table 9 phishGILLNET and competing methods characteristics

From: phishGILLNET—phishing detection methodology using probabilistic latent semantic analysis, AdaBoost, and co-training

Method

Year of publication

Corpus (public/private/mix

Max data

Year when data source used generated

3-class classification

Can handle unlabelled?

Chan et al. [65]

2004

Public

2.8 K

NA

No

Yes

PILFER [10]

2007

Public

7.8 K

2002-2006

No

No

Abu-Nimeh et al. [11]

2007

Private

2.8 K

2005-2006

No

No

Bergholz et al. [16]

2008

Public

8 K

2004-2007

No

No

Abu-Nimeh et al. [12]

2009

Mix

6.5 K

2006-2007

No

No

Gansterer and Pölz [15]

2009

Mix

15 K

2007

Yes

No

Toolan and Carthy [19]

2010

Public

8.3 K

2004-2007

No

No

Bergholz et al. [17]

2010

Private

40 K

2007

No

No

Khonji et al. [20]

2011

Public

8.2 K

2003-2007

No

No

Al-Momani et al. [21]

2011

Public

8.7 K

2003-2007

No

No

phishGILLNET1

-

Public

8.7 K

2003-2007

No

No

phishGILLNET2

-

Public

400 K

2011 (phish-40 K, spam 320 K)

Yes

No

    

2001 (good-40 K)

  

phiahGILLNET3

-

Public

400 K

2011 (phish-40 K, spam-320 K)

No

Yes

    

2001 (good-40 K)