security solutions

In recent years, in the field of network information security protection, the (intrusion detection) technology can be said to be increasingly valued by everyone. It mainly refers to monitoring whether there are unauthorized illegal intrusions in network systems or computer systems, or some abnormal activities that may cause damage to the system, so as to promptly discover potential security threats. Simply put, it is like installing a pair of "electronic eyes" and "electronic ears" on our network system or computer system, paying attention to the system's every move at all times. Once you find something wrong, like a strange IP address that is secretly connected in, or a program has strange read and write operations, it will issue an alarm to remind the administrator to quickly deal with these potential and possible serious security issues. For enterprises or individuals who need to ensure their own network and data security, understanding and applying technology well can be said to be a very, very important link.

According to different detection methods and working principles, technology can be roughly divided into several main types. The first common type is signature-based intrusion detection . This method, simply put, stores the characteristics and patterns of various known attack behaviors into a feature library in advance, and then constantly compares various activities on the network or system during actual monitoring. Once you find that there are behaviors that are exactly the same or highly similar to an attack feature in the feature library, you will immediately determine that this may be an intrusion behavior and issue an alarm. The advantage of this method is that for those attack methods that have been understood and mastered by everyone, their detection accuracy is quite high, and there will be relatively fewer false alarms; however, the disadvantage is quite obvious. If you encounter some new attack methods that have not been included in the feature library, which is what we often call "zero-day attacks", then it is likely to "not see" these attacks, just like a cat with blindfolded eyes, and cannot detect danger. Another common type is exception-based intrusion detection (-based) . This method is different from usual. It is not to compare known attack characteristics, but to first learn and establish a "baseline configuration file" in the normal operation state of a system. This configuration file contains various normal indicator data such as the normal range of network throughput, the time rules of user login, common modes of data transmission, etc. After that, it will carefully compare the current actual operating status of the system with this "baseline configuration file" day after day. If it finds that the difference between the two exceeds the reasonable range set in advance, it will judge that the system may have been invaded and then issue an alarm signal. The advantage of this method is that it has the ability to detect new unknown attacks that have never occurred before, because no matter what kind of attack it is, as long as it deviates from the normal operation track and becomes "abnormal", it may be detected; however, it also has a headache, that is, sometimes it is easy to report some normal fluctuations in the system under specific circumstances as abnormal intrusion behavior, that is, the false alarm rate will be relatively higher. This requires administrators to spend time and energy to identify and screen those alarms and provide global procurement services for weak current intelligent products! Therefore, in practical applications, these two different types of technologies are often used together, so that their strengths can be taken, their weaknesses can be made up for, and thus better detection results can be achieved.

When actually deploying and applying the system, there are some key steps that must be paid attention to, and none of these steps can be missed, otherwise it may affect the detection effect and operation efficiency of the entire system. The first step is to carefully clarify the scope and target of the inspection. Whether you want to monitor the entire vast internal network of the enterprise, or just monitor a few key and important servers, or a specific application system, only by determining the scope and target first can you choose the appropriate products and technologies based on this and carry out various subsequent configuration work. The second step is to choose the appropriate system type based on the detection range and target determined earlier. For example, if the network scale is relatively large and the structure is relatively complex, it may be necessary to deploy a network-based intrusion detection system (NIDS – -based) that can monitor the entire network traffic; if you pay more attention to local security conditions such as the operating system and file system of a single host, then the host-based intrusion detection system (HIDS – Host-based) may be more suitable. The third step is to carefully configure the system, such as setting up those detection rules reasonably, and not setting them too loosely. If they are too loose, many real attacks may be missed; nor should they be set too strict, as if they are too strict, it will lead to a large number of false alarms, making it difficult to distinguish between true and false. At the same time, appropriate alarm thresholds and alarm methods must be set according to the actual network environment and security needs. It can be sent by email, or a conspicuous alarm window pops up on the management console, or send alarm notifications through text messages, etc., to ensure that the administrator can receive alarm information quickly and accurately. The fourth step, which is also a very critical step, is to regularly update the system and optimize the policy, because cyber attack technology is constantly developing and changing yesterday, which may still be effective detection rules. Today, it may become less effective due to the emergence of new attack methods. Therefore, the feature library and detection rules must be updated in time, and the detection strategies must be continuously adjusted and optimized according to the actual alarm situation and false alarm situations generated during the operation of the system. Only in this way can the system be ensured that the system always maintains a relatively high detection sensitivity and accuracy level.

When using the system in actual use, you often ask some questions. I will answer them below, hoping to help you better understand and use this technology. The first common question is: Can the intrusion detection system detect all intrusion behaviors 100%. This is really a big problem for many people. The answer is actually a pity. No. Although the system can effectively detect many known or even unknown intrusion behaviors and plays a very important role in network security protection, no security technology in the world is perfect and impeccable. There will always be some very advanced and hidden attack methods that can find ways to avoid – system monitoring. Some may specifically encrypt the attack packets, so that the detection system can't understand the contents of the packets; some may adjust the frequency and mode of the attack to make it look similar to normal network traffic and difficult to distinguish; some may even use some vulnerabilities in the system itself to attack and interfere with the system itself, making it invalid. Therefore, in order to comprehensively and effectively ensure the security of the network and data, it is also necessary to use other security technologies such as systems and firewalls, vulnerability scanning, data backup, access control, etc., as if several horses were pulling a car, everyone worked together to build a solid and reliable in-depth security defense system. The second common problem may be: in actual operation, how should administrators deal with so many alarm information to be more efficient? This is indeed a difficult problem that you often encounter in actual work. Faced with a large amount of alarm information, it takes too much time and energy to read it carefully one by one. At this time, the administrator can divide all alarm information into different levels according to their severity, such as divided into different levels of emergency alarms, important alarms, general alarms, prompt alarms, etc., and then prioritize those alarms with higher severity. For those emergency alarms that have clearly pointed to the system being attacked and may cause serious losses, they must be processed immediately and immediately; for those alarms with lower severity, they can be arranged to be processed after handling emergency affairs. At the same time, some automated security incident response platforms can also be used to conduct preliminary screening and analysis of alarm information to automatically filter out false alarm information that is as annoying as summer flies, which can greatly improve the efficiency of administrators in processing alarm information

With the rapid development of network technology and the continuous renovation of cyber attack methods, future technologies will inevitably develop in a direction of more intelligent, automated, and closer integration with other security technologies. For example, integrating advanced technologies such as artificial intelligence (AI) and machine learning (ML) into the system allows it to continuously improve its ability to detect various new and unknown attack behaviors by independently learning and analyzing a large amount of security data like an experienced security expert, and can automatically generate some new detection rules and strategies without relying entirely on manual updates. In addition, the system will integrate more deeply and closely with the threat intelligence platform, and use real-time updated global threat intelligence data to enrich its "brain", and can detect targeted advanced security threats from all over the world earlier and faster. Of course, when developing these new technologies, we should still pay attention to reasonably balancing the detection performance and resource consumption of the system. We should not consume a large amount of the system's processor resources, memory resources and network bandwidth resources because of the pursuit of excessive detection capabilities, thereby affecting the normal and stable operation of the entire system.