Advantages And Disadvantages Of Intrusion Prevention System

Advantages And Disadvantages Of Intrusion Prevention System – Cybersecurity solutions are becoming a necessity for small and medium-sized businesses. Due to COVID-19, remote work has become more common in the last few months, increasing the risk areas.

Businesses should implement network intrusion detection systems (IDS) to monitor network security incidents. They detect and mitigate network threats and attack malware using hardware and software.

Advantages And Disadvantages Of Intrusion Prevention System

The primary purpose of an intrusion detection system is to monitor network traffic for suspicious activity and issue alerts when such activity is detected. But most intrusion detection systems are smart enough to detect malicious activity and take action when it happens. Suspicious Internet Protocol (IP) addresses are blocked from that network.

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Unlike an IDS, an intrusion prevention system (IPS) monitors network packets for malicious network traffic, the primary goal being to prevent threats rather than detect them.

IDS monitors all traffic between devices on the network. The system acts as a secondary firewall behind the primary firewall that detects malicious packets based on two suspicious parameters:

An intrusion detection system detects threats by analyzing patterns. Using this technology, IDSs can compare network packets to databases of cyberattack signatures.

If an error is detected, the IDS will detect it and raise an alarm. This can be any type of audit, be it a note in the ledger or a quick message to the IT manager. The team then analyzes the problem and finds the root cause.

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For this project, we will be using the Python programming language along with two other libraries, OpenCV and NumPy.

We’ll start by importing the libraries. If you haven’t installed these libraries, you can install them using the pip command. Open your command prompt, type the following command, press Enter, and wait for the libraries to install.

You can use a laptop or video camera for this purpose. The first step is to find the video file or start the video if you are using a laptop camera. Now we need to define the area we want to protect.

For this we will create a Click_even function. This function will allow you to select a rectangular area in the frame. The user must first left click at the start of L1 and drag the pointer to the end of the L2 section. By default, we will capture the entire frame, so if you want to press any button to continue, you can leave this parameter as is.

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From the snippet above, you can see that we have used OpenCV mouse events to create the interface. We used the flag object “draw” which sets the position of the mouse pointer. When the status is 1, it means that the user is creating an attraction, and when it is done, the status returns to 0, allowing the user to create an attraction. We have assigned the coordinates of the region of interest as a global variable so that we can use these values ​​in the next part of our code.

As you can see in the following code snippet, we will start counting the frames of the video. We will take two consecutive frames of video and focus on the part of the frame or region of interest that we selected in Step 1.

Using an RGB image may not be very useful for this problem and will reduce performance. Therefore, we will convert these frames into grayscale images. Next, we check if there is any change in two consecutive frames. We can calculate these changes using OpenCV’s absdiff() function.

The Abdiff() function will return the difference between two frames. The next step is to extract the hidden image of this discrete image, which consists of white or black pixels. To do this, we can use a picture frame. The white pixel represents the frame transition, and the black part of the image represents the similarity between the two frames. These changes can be very rapid and there can be many periods between them, so in some cases they can be difficult to detect. Therefore, we will use some image editing methods to fix the problem.

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We will use the Gaussian blur method to smooth the image and expand the image to fill the gaps between the white protected images. After image processing, our protected image looks like below.

Next, we calculate the area of ​​these white parts of the image. To calculate the area of ​​these white areas, we will use OpenCV’s trace contour method. This method will extract the border details. You can visualize these shapes using OpenCV’s draw contour function. We can also pass this information to the contour area function, which will return the area of ​​each contour. We can ignore small changes because they might just be noise.

For this we will set a limit. If the contour size is below this threshold (900 in our case), we will ignore that contour. To show that we have noticed the interference, we can circle the queue with a green box.

We can also use a buzzer to scare the owner. In this project, consider the buzzer alarm implementation as a function. There are many libraries that can be used for this, such as Win Sound and Sound.

Intrusion Detection Systems

The deployment of intrusion detection systems varies by environment. The new generation of IDS, like other cybersecurity solutions, can be based on hosts or networks.

In particular, a host IDS is used in a specific environment to improve security against external and internal threats.

The visibility of a host-based IDS is limited to the host machine, which reduces the complexity of decision-making. However, it provides a deeper understanding of the host’s inner state.

IDS solutions that monitor the internet can generally be called web-based solutions. As a result, it can see all the details of a packet and make decisions based on the content and metadata of each packet.

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Therefore, these systems are able to detect common threats, but they are not visible in the results they protect.

Because of the different levels of visibility, implementing HIDS or NIDS separately does not fully protect an organization’s systems. Integrated security management solutions provide comprehensive security because they combine multiple technologies into a single package.

The system checks all packets passing through the network against an internal attack signature database. This database contains known malware. In other words, this system works like an anti-virus software.

This includes networks, protocols, ports, etc. It analyzes network traffic against a defined baseline for different networks. This type of security strategy is based on machine learning.

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Alerts the IT team when suspicious behavior or a breach is detected. Random detection uses a broad pattern instead of individual signatures and attributes to overcome the limitations of signature-based detection.

In this age of information, there is no such thing as an impenetrable firewall or network. Attackers are constantly developing new actions and attacks to defeat your defenses. There are different methods of malware or social engineering, and they are used by attackers to gain access to your network and data.

Maintaining network security requires an intrusion detection system (IDS) that detects and responds to malicious traffic. Intrusion detection systems are responsible for alerting IT staff of a potential attack or network intrusion. Inbound and outbound traffic, including data traffic between systems in a network, is monitored by an intrusion detection system (IDS).

IDSs monitor network traffic and generate alerts when suspicious activity or known threats are detected. This allows IT staff to investigate further and take action to prevent attacks.

What Are The Advantages Of Next Generation Firewall Over Traditional Firewall?

An intrusion detection system (IDS) can be an important part of a company’s security strategy. Here are some of the benefits of IDS that you can take advantage of.

While a firewall can provide information about the ports and IP addresses used between two hosts, NIDS can provide information about the characteristics inside the packet. For example, botnets and exploit attacks can be detected by analyzing compromised endpoints.

As part of protocol analysis, NIDS examines TCP and UDP packets. Sensors can detect suspicious activity because they know how the protocol is supposed to work.

The purpose of IDS is to analyze the volume and nature of attacks. Using this information, you can implement new and more effective security systems or modify your security systems. It can also be used to diagnose configuration problems or network device errors. Metrics can be used to assess future risks.

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Data helps ensure your security system is compliant because it is visible on your network. Depending on your needs, IDS records may be useful for documentation.

With IDS sensors, you can find out which operating systems and services are being used by your network by examining packet data. By doing this yourself you will save a lot of time. Again

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