Browsing by Author "Ayalew, Tadele"

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    Developing a Detection Method for Interconnect Bypass Frauds Using Fuzzy Logic
    (Addis Ababa University, 2021-07-12) Ayalew, Tadele; Lemma, Dagmawi (PhD)
    An interconnect bypass fraud is a telecom fraud that manipulates technological advancements and realized over the existing cellular networks with the intention of gaining illegal benefits. It results a degraded quality of service and financial loss. Existing prevention mechanisms collect call detail records to detect the fraud by analyzing various predefined behaviors. Hence, such systems play the role of intrusion detection by recording known behaviors. Thus, illegal accesses of a cellular network would be detected if the activity is similar with previously identified suspicious act, this further is a major concern of having a higher rate of false positive and/or false negative alarms. As interconnect bypass fraudsters are basically attacking the cellular network from a stationed location through a series of fixed network elements, a mobile subscriber, yet stationed is a suspect to be fraudster. In order detect new fraudulent act by studying the activity with respect to the natural set of mobile users (i.e., mobility) and mitigate the false negative and false positive rates, we have introduced a new detection method through a design science approach. We intend to trace mobile subscription but operates from fixed location. Our method gets inputs from home location register and monitors the mobility history of cellular network users by applying a fuzzy logic. We have tested the method by logging the location histories of 1037 randomly selected users. We have detected the fraudulent users with 1.92% up to 5.88% false positive rate and 0.88% up to 5.88% false negative rate.
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    Developing a Detection Method for Interconnect Bypass Frauds Using Fuzzy Logic
    (Addis Ababa University, 7/12/2021) Ayalew, Tadele; Lemma, Dagmawi (PhD)
    An interconnect bypass fraud is a telecom fraud that manipulates technological advancements and realized over the existing cellular networks with the intention of gaining illegal benefits. It results a degraded quality of service and financial loss. Existing prevention mechanisms collect call detail records to detect the fraud by analyzing various predefined behaviors. Hence, such systems play the role of intrusion detection by recording known behaviors. Thus, illegal accesses of a cellular network would be detected if the activity is similar with previously identified suspicious act, this further is a major concern of having a higher rate of false positive and/or false negative alarms. As interconnect bypass fraudsters are basically attacking the cellular network from a stationed location through a series of fixed network elements, a mobile subscriber, yet stationed is a suspect to be fraudster. In order detect new fraudulent act by studying the activity with respect to the natural set of mobile users (i.e., mobility) and mitigate the false negative and false positive rates, we have introduced a new detection method through a design science approach. We intend to trace mobile subscription but operates from fixed location. Our method gets inputs from home location register and monitors the mobility history of cellular network users by applying a fuzzy logic. We have tested the method by logging the location histories of 1037 randomly selected users. We have detected the fraudulent users with 1.92% up to 5.88% false positive rate and 0.88% up to 5.88% false negative rate.