IMPOSTERS ANOMALY DETECTION - Tazerouti, A.; Ikram, A (university of el oued/جامعة الوادي, 2021)
Over the last two decades the world of cyber security has grown immensely, but despite the state-of-the-art security detection systems and intrusion detection systems (IDSs), unwanted malicious users still find their way around these security measures and gain access to secure systems. This study consists of shedding some light on the security issues in the intrusion detection systems, their vulnerabilities and drawbacks. A hypothesis is proposed to help mitigate these issues and obtain a fast and a more precise method for the detection of different malicious intruders and imposters, study their behavior and make a statistical comparison of data from the used IDSs and throughout the process. This study will state the current available technologies of IDSs, site their challenges and implement a new software-based methodology to increase the detection and reduce false alarm rates for the IDS.
Article
Keywords: Cyber Security; Intrusion Detection System; Software-based detection; Keystroke Dynamics; Network-based detection.