Fuzzy Intrusion Detection System Research Articles

An intruder defense model for the detection of power grid disturbances in wireless network

Cyber security has to gain a high level of awareness in the Network and Computer pasture due to the large spread of information transmission technology. A powerful False Data Injection (FDI) Intruder monitors the network activities and injects the malicious data thereby causing failure in the power system. To overcome this defense, the “Conviction based Intruder Defense Model” is proposed to identify and isolate it from the network by providing secure transmission. This scheme operates in three phases. In the first phase, the data are analyzed with the library files to identify the conviction values. Based on the conviction values the resulting factors are analyzed with different iterations and the suspicious drafts are identified and classified using Fuzzy Intrusion Detection System (FIDS) divider. In the second phase, three algorithms are used to organize the drafts categorized. In the third phase, abnormal nodes are isolated from the network. Experimental results show higher accuracy and detection rates with low false positives.

FUZZY AIDED APPLICATION LAYER SEMANTIC INTRUSION DETECTION SYSTEM - FASIDS

The objective of this is to develop a Fuzzy aided Application layer Semantic Intrusion Detection System (FASIDS) which works in the application layer of the network stack. FASIDS consist of semantic IDS and Fuzzy based IDS. Rule based IDS looks for the specific pattern which is defined as malicious. A non-intrusive regular pattern can be malicious if it occurs several times with a short time interval. For detecting such malicious activities, FASIDS is proposed in this paper. At application layer, HTTP traffic's header and payload are analyzed for possible intrusion. In the proposed misuse detection module, the semantic intrusion detection system works on the basis of rules that define various application layer misuses that are found in the network. An attack identified by the IDS is based on a corresponding rule in the rule-base. An event that doesn't make a 'hit' on the rule-base is given to a Fuzzy Intrusion Detection System (FIDS) for further analysis.

Novel model for intrusion detection

It’s very difficult that the traditional intrusion detection methods based on accurate match adapt to the blur and uncertainty of user information and expert knowledge, it results in failing to report the variations of attack signature. In addition security itself includes fuzziness, the judgment standard of confidentiality, integrity and availability of system resource is uncertain. In this paper fuzzy intrusion detection based on partial match is presented to detect some types of attacks availably and alleviate some of the difficulties of above approaches, the architecture of fuzzy intrusion detection system (FIDS) is introduced and its performance is analyzed.