In this paper, we provide a structured and contemporary, wide-ranging study on intrusion detection system in terms of techniques and datasets and also highlight challenges of the techniques and then make recommendations.ĭuring the last few years, a number of surveys on intrusion detection have been published. Prior studies such as (Sadotra & Sharma, 2016 Buczak & Guven, 2016) have not completely reviewed IDSs in term of the datasets, challenges and techniques. Compared to previous survey publications (Patel et al., 2013 Liao et al., 2013a), this paper presents a discussion on IDS dataset problems which are of main concern to the research community in the area of network intrusion detection systems (NIDS).
Challenges for the current IDSs are also discussed. The complexity of different AIDS methods and their evaluation techniques are discussed, followed by a set of suggestions identifying the best methods, depending on the nature of the intrusion. The signature-based and anomaly-based methods (i.e., SIDS and AIDS) are described, along with several techniques used in each method. This paper also provides a survey of data-mining techniques applied to design intrusion detection systems. It provides a structured and comprehensive overview of the existing IDSs so that a researcher can become quickly familiar with the key aspects of anomaly detection.
This paper provides an up to date taxonomy, together with a review of the significant research works on IDSs up to the present time and a classification of the proposed systems according to the taxonomy. Secondly, the time taken for building IDS is not considered in the evaluation of some IDSs techniques, despite being a critical factor for the effectiveness of ‘on-line’ IDSs. There are a large number of related studies using either the KDD-Cup 99 or DARPA 1999 dataset to validate the development of IDSs however there is no clear answer to the question of which data mining techniques are more effective. In the last few decades, machine learning has been used to improve intrusion detection, and currently there is a need for an up-to-date, thorough taxonomy and survey of this recent work. With the increasing volume of computer malware, the development of improved IDSs has become extremely important. The aim of an IDS is to identify different kinds of malware as early as possible, which cannot be achieved by a traditional firewall. So there is a need to develop an efficient IDS to detect novel, sophisticated malware. In 2017, the Australian Cyber Security Centre (ACSC) critically examined the different levels of sophistication employed by the attackers (Australian, 2017).
Malware is intentionally created to compromise computer systems and take advantage of any weakness in intrusion detection systems. There are a large number of cybercriminals around the world motivated to steal information, illegitimately receive revenues, and find new targets. High profile incidents of cybercrime have demonstrated the ease with which cyber threats can spread internationally, as a simple compromise can disrupt a business’ essential services or facilities. For that reason, the detection of zero-day attacks has become the highest priority. However, the new generation of malware has become more ambitious and is targeting the banks themselves, sometimes trying to take millions of dollars in one attack (Symantec, 2017). In the past, cybercriminals primarily focused on bank customers, robbing bank accounts or stealing credit cards (Symantec, 2017). A Symantec report found that the number of security breach incidents is on the rise. As highlighted in the Data Breach Statistics in 2017, approximately nine billion data records were lost or stolen by hackers since 2013 (Breach_LeveL_Index, 2017). According to the 2017 Symantec Internet Security Threat Report, more than three billion zero-day attacks were reported in 2016, and the volume and intensity of the zero-day attacks were substantially greater than previously (Symantec, 2017). As a result, various countries such as Australia and the US have been significantly impacted by the zero-day attacks. Therefore, computer security has become essential as the use of information technology has become part of our daily lives. In addition, there has been an increase in security threats such as zero-day attacks designed to target internet users. Malicious attacks have become more sophisticated and the foremost challenge is to identify unknown and obfuscated malware, as the malware authors use different evasion techniques for information concealing to prevent detection by an IDS.
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The evolution of malicious software (malware) poses a critical challenge to the design of intrusion detection systems (IDS).
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