Abstract
Distributed Denial of Service attacks (DDoS) overwhelm network resources with useless or harmful packets and prevent normal users from accessing these network resources. These attacks jeopardize the confidentiality, privacy and integrity of information on the internet. Since it is very difficult to set any predefined rules to correctly identify genuine network traffic, an anomaly-based Intrusion Detection System (IDS) for network security is commonly used to detect and prevent new DDoS attacks. Data mining methods can be used in intrusion detection systems, such as clustering k-means, artificial neural network. Since the clustering methods can be used to aggregate similar objects, they can detect DDoS attacks to reduce false-positive rates. In this study, a review of DDoS attacks using clustering data mining techniques is presented. A review illustrates the most recent, state-of-the art science for clustering techniques to detect DDoS attacks.
Highlights
Information has become an organization’s most precious asset upon which they have increasingly become dependent
Distributed Denial of Service attacks (DDoS) attacks have become a hot research topic, because they can lead to a loss of confidence and privacy and could lead to illegal actions taken against an organization
In the network misbehavior DDoS detection packets using statistical method, (Maryam et al, 2011) exploits some statistical method features for the incoming traffic and design a system based on statistic-based method using entropy to decide whether the attack is occurred
Summary
Business for the organization assets such as loss customer confidence, contract damages, regulatory. Misuse detection is based on the pattern matching to unavailable for normal operations (Jieren et al, 2009) This attack is one of the main threats that the internet is facing which causes corrupted for information and loss of data integrity, confidentiallity hunt for signature detection from known attacks. The DDoS attack makes use of many compromised hosts to send a lot of useless packets to the target in short time of invalid access which will consume the target's resources and causes outage of server operation (Junaid et al, 2013). These kinds of attacks have posed an immense threat to the internet. In addition to all steps, the DDoS attack is easier to carry out with genuine packets, more harmful, hard to be traced due to attacker spoofed IP and difficult to prevent and its threat is more serious (Keunsoo et al, 2007)
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