10-04-2017, 08:22 PM
Where we are today in the intrusion detection?
In today's world, where almost every company depends on the Internet is to survive, it is not surprising that the role of the network intrusion detection has grown so fast. While it still may be some argument as to what is the best way to protect firms network (i.e. firewalls, patches, intrusion detection, training, etc.) it is certain that the intrusion detection system (IDS) is likely to maintain an important role in providing a secure network architecture.
That being said, what modern intrusion detection technology to provide us? For the analyst, who sits in front of the IDS, the ideal system would identify all the invasion (or attempted burglary), and take or recommend appropriate action to stop the attack.
Unfortunately, the market for IDS is still quite young and "silver bullet" solution to detect all attacks do not seem to be on the horizon, or necessarily even believable. So what is the "next step", while the "next step" for intrusion detection? a strong case can be made for the use of data mining techniques to improve the current state of intrusion detection.
What is data mining?
By RL Grossman in the "data mining: challenges and opportunities for data mining within the next decade," he defines data mining as it relates to the open models, associations, changes, anomalies, and statistically significant structures and developments in data. "simply put, the ability to accept data and pull out of the samples or abnormalities that may not be easily seen with the naked eye. Another term sometimes used to identify knowledge.
Although they will not be discussed in detail in this report, there are many different types of data mining algorithms to enable page link analysis, clustering, association rules, kidnapping, variance analysis and sequence analysis.
Currently IDS Intrusion detection?
In order for us to determine how data mining can help advance intrusion detection, it is important to understand how the current IDS Intrusion detection work. There are two different approaches to intrusion detection: incorrect identification and detection of anomalies. Detection of abuse is the ability to detect the invasion on the basis of the famous model for malicious activity. These famous structures are called signatures. the second approach, detecting anomalies, is to attempt to identify malicious traffic based on deviations from the normal patterns of network traffic. Most, if not all, of the IDS that can be purchased today are based on the detection of child abuse. Current IDS products are supplied with a large set of signatures, that have been identified as unique to the particular vulnerabilities or exploitation. Most manufacturers also provide regular IDS signature updates in an attempt to keep pace with the rapid emergence of new vulnerabilities and exploits.
Shortcomings with current IDS.
While the ability to develop and use a signature for attack detection is a useful and effective approach has drawbacks with this approach, you should pay attention to.
Options. As previously mentioned signatures, developed in response to new vulnerabilities or exploits that were placed or released. An integral part of the success of the label, it must be sufficiently unique to just warn about malicious traffic and rarely on reliable network traffic. the difficulty here is that malicious code can often be easily changed. It is not uncommon for a tool that will be released and then its default changed soon after the hacking community.
The overall false positive complaint number of false positives generated IDS. Development of unique signatures, is a difficult task and often sellers will err on the side of warnings too often, rather than not enough. This is similar to the story of the boy who cried wolf. It's much harder to select the right to the invasion if the signature is also regularly warns of the real network activity. the complexity of the problem that arises from this, it can be filtered without using potentially there is no attack.
False Negative. .. Detection of attacks, for which no known signatures. This leads to another concept of false negatives, where IDS do not generate a notification when an invasion is going on. Simply put, if the signature was not written for each vulnerability, there is a very good chance that the IDS does not detect it.
Data overload. Another aspect that is specific to that discovery abuse, but it is essential that as much data can effectively analyze analyst.