You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: A Survey of Outlier Detection Methods in Network Anomaly Identification 
Chapter Title:  Definition 5: RMF (rough membership function)- 
1. Abstract of Cited Paper (BIB001):  “One person's noise is another person's signal” (Knorr and Ng 1998). In recent years, much attention has been given to the problem of outlier detection, whose aim is to detect outliers—objects who behave in an unexpected way or have abnormal properties. Detecting such outliers is important for many applications such as criminal activities in electronic commerce, computer intrusion attacks, terrorist threats, agricultural pest infestations. In this paper, we suggest to exploit the framework of rough sets for detecting outliers. We propose a novel definition of outliers—RMF (rough membership function)-based outliers, by virtue of the notion of rough membership function in rough set theory. An algorithm to find such outliers is also given. And the effectiveness of RMF-based method is demonstrated on two publicly available data sets.

Literature Review:
based outliers BIB001 BIB002 . A RMF is defined as follows. Let IS=(U, A, V, f ) be an information system, X ⊆ U and X = Φ. U is a non-empty finite set of objects, A a set of attributes, V the union of attribute domains, and f : U × A → V a function such that for any X ∈ U and a ∈ A, f (x, a) ∈ V a . Let ν be a given threshold value. For any x ∈ X, if ROF X (x) > ν, x is called a rough membership f unction (RM F )-based outlier with respect to X in IS, where ROF X (x) is the rough outlier factor of x with respect to X in IS. The rough outlier f actor is defined as The RMF is µ where