With the changes in technology, the need for more advanced cyber security measures is on the increase. Businesses have to hire security teams that utilize analytics to spot anomalies in the data and detect possible threats.
Cybersecurity analytics is the process of gathering data, grouping them, and analyzing them for patterns to spot anomalies and improve an underlying cybersecurity strategy. This type of analytics has continued to develop, and newer mechanisms are solving issues in the existing infrastructure such as the possibility of errors. Traditional systems tend to carry out tests at a point in a day, which may lead to errors, as it is not a reflection of the state of security on a day. Newer models, on the other hand, are designed to continuously monitor the changes in the architecture, analyze the data, and notify the security team when an anomaly is spotted. This is a better means of cybersecurity analytics, as the system is always on the watch, reducing the probability of errors.
The core purpose of cybersecurity analytics is to offer the security team firm access to the intricacies of their digital system. They can see what is happening at different points in time, and spot anomalies early enough to reduce the risks of them worsening.
Security analytics tools are designed to monitor the operations of a firm’s IT system and spot issues in real-time.
Security analytics platform explained
The security analytics platform is a platform that allows clients to access a library of existing security threat patterns, and strategies to solve them. Vendors usually offer these services, while allowing their clients to customize their threat models. They are also permitted to create new threat scenarios and possible solutions to mitigate the effects. In a typical cybersecurity analytics platform, security admins of different companies can study attacks, analyze them and create strategies to curb them. There is a possibility of partnership among multiple firms to solve potential threat scenarios. Usually, the results are structured in an easy-to-understand manner for clients to understand the different aspects.
An example is Chainalysis. Some security analytics platforms are available for usage by both small and large firms.
A typical cybersecurity analytics firm offers its services to different sectors in society, from governments bodies down to cryptocurrency companies. The tools and infrastructure offered by these firms are designed to solve cyber-criminal issues and make it easy for businesses and financial structures to operate effectively.
Key security analytics tools
Generally, security analytics tools gather event data, filter and analyze them in real-time to offer an overview of the security of the IT infrastructure of a company. As long as a company utilizes digital devices from as little as smartphones to as complex as a database, it is crucial that they have access to security analytics tools.
Regularly, innovations are being introduced into the security analytics market because the security risks are advancing. Though these changes are available, the underlying risks that businesses and governments face as regards their architecture are similar. They need to gather information, analyze data, spot anomalies and get notifications concerning a possible attack.
The needs of a small firm may be different from the demand in the security analytics tools of a big firm.
Smaller firms
Usually, a smaller firm may not offer a huge payday for hackers, but they are seen as an easy target. Some attackers may bypass its security system to train for advanced attacks on bigger firms. Different industries have varying security requirements for the companies in that sector. Some demand a higher level of security controls, not minding the size of the firm.
The cybersecurity analytics tools used by smaller firms are designed to reduce the possibility of attacks but may be restricted because of the size of the company. Frequently, the deployment mechanisms used are designed to reduce administrative overhead.
A typical cybersecurity analytics tool for a small-scale business has a single management dashboard, where the firm’s IT team monitors the state of the network, servers, and applications. This tends to act as a cloud service, meaning that it may not need an elaborate hardware device to function. It may come with machine learning abilities that detect possible anomalies, find trends and notify the necessary personnel to handle the issue. The company can track KPIs on the management dashboard and make alterations if necessary.
For those firms that may not prefer cloud services, on-premises security analytics software exists. They usually come as a pre-configured appliance or virtual machine. Customization is possible in both the cloud and on-premises security analytics tools.
Larger firms
Larger firms are known to splurge money and other resources in achieving a high level of security. Their security analytics platform tends to be more advanced than what is obtainable in smaller organizations. Administration overhead is not an important criterion as compared to a high-performance analytics system.
The system used by larger firms and the government is highly scalable and oversees a larger scope and depth. Some organizations have custom-made security analytics tools designed to their needs.
In some cases, the organization may want to build its system from scratch, while others may need a system that allows them to plug in their existing infrastructure. The latter means that the cybersecurity analytics platform will solve the issues in the firm’s existing infrastructure. Some analytics platforms offer both analytics services and infrastructure support.
Modules are deployed based on the needs of the clients and usually come with decoders that collect packets and log data in real-time. The collected data can be aggregated and analyzed by other tools in the cybersecurity analytics platform.
The need for security analytics
Security threats are common in any organization, including blockchain platforms. Crypto platforms have been victims to hackers that take away millions of dollars. Some companies may end up filing for bankruptcy and closing up shop after an attack. An example is Mt. Gox.
With the security risks and attacks that firms face regularly, there is the need for security analytics tools to analyze the state of the IT architecture, while looking for anomalies to spot possible breaches. Companies also use these tools to learn about existing security threats in their industry and possible ways to checkmate them.
Security analytics allows firms to spot security risks and attacks in real-time, reducing the extent of damage that may befall the firm.
Benefits of security analytics to cryptocurrencies
The crypto world has faced different types of security risks. It may come from external attackers hacking into a liquidity program or a decentralized finance platform and making away millions of dollars worth of cryptocurrencies. News of hacking of a blockchain-based platform has become a regular occurrence. Security analytics will benefit the sector in different ways, reducing the losses and risks attached to an external attack.
- Gathering of threat intelligence
When cybersecurity analytics tools are incorporated into a crypto platform, it benefits from automated threat intelligence, which reduces the resources expended on carrying out manual security tasks. Apart from the aforementioned, it reduces the probability of errors and identifies anomalies in real-time.
- Forensic incident investigation
When a crypto platform is attacked, it can use forensic investigations to spot the vulnerability in its security architecture that made the breach possible. The security analytics system tends to spot the origin of the threat and the site of the breach. With the data gathered during the forensic investigations done using security analytics, the team can create strategies to prevent the situation from occurring in the future.
- Possible attack detection
Security analytics platforms like Chainalysis allow blockchain firms to study previous attacks in the industry, as well as possible attacks and create strategies to prevent them. They find the patterns in a network and detect a possible attack based on the trend. This is a proactive way of responding to threats.
Security analytics use cases
Security analytics systems have incredible use cases that can improve the operations of the ecosystems. Companies can incorporate this system to detect possible patterns that point to suspicious activities, monitor the usage of the IT infrastructure by employees, detect possible insider threats, and investigate events.
Sometimes, these tools may be used in pinpointing trends that predict a future attack, detect data breaches by attackers, and spot possibly compromised accounts. In the crypto space, security analytics tools can be utilized in detecting possible rug pulls by insiders.
Possible data security threats
Cybersecurity threats come in different forms and may vary according to the industry. Typically, it may be malware, where malicious software is introduced into the system or it could be a denial of service that floods the system with requests preventing it from functioning effectively.
An attacker may use the man in the middle strategy to insert themselves in a transaction that occurs between two parties. Phishing may be used to steal important details by sending a fake email. In the crypto space, hackers may steal private keys through browser extensions, create fake apps, and much more. Usually, attacks target the hot wallets of blockchain platforms to drain the cryptocurrencies that they hold.
In Conclusion,
- Cybersecurity analytics is the process of gathering data, grouping them, and analyzing them for patterns to spot anomalies and improve an underlying cybersecurity strategy.
- Cybersecurity analytics is important for every organization, not minding their size.
- Security analytics can help to detect possible attacks through patterns.
- Blockchain platforms need the services of a security analytics platform to reduce the risks of attacks.
- The features in a security analytics architecture used by a small company may be different from what is needed in a large firm.
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