To ensure network security, you have to remember this 6 aspects!

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Protect your digital asset is a clear need for any business and individual, whether you want to protect your personal photos, company intellectual property, customer sensitive data, or any other may affect your reputation or business any thing.

Even if the consumption of network security has been charged with billions of dollars, the number of reports reported only increased. The predictive capabilities of AI can be applied to many areas, which can be applied to security vendors, all users, and businesses. Yakir Golan summarizes the six key areas of network defense innovation for readers.

1. Detection and block the Internet of Things (IoT) equipment is hacked

Cisco company professional analyst tells (QQ public number: hacking) prediction results, the number of global networking equipment It will rise from the current 15 billion part to 50 billion in 2020. Due to hardware and software resources, many devices do not have basic security measures. Recently, the Internet of Things (IOT) equipment in the hacker invaded Kerbsonsecurity, making Kerbsonsecurity suffered a large-scale distributed denial of service attack. More terrible is that after the source code for Mirai malware, the source code of Mirai malware, using Mirai, using Mirai, network attacks can be attacked.

Internet Security is one of the most prominent areas of AI technology. The Internet of Things provides predictive models for AI, can independently reside and operate on devices of low computing power, and can discover and block suspicious behaviors of the device or network range.

Second, prevent malware and file attack

Based on file-based attack is still one of the most important network attacks. The file type of the most common network attack is the executable file (.exe), Acrobat Reader (.pdf), and Microsoft Office files. Minor changes in a single line of code can generate new malicious files. The new file has the same malicious intent, but has different signatures. Small changes in single-line code triggers the anti-virus program and launch more advanced advanced endpoint detection and EDR or even network systems to solve malicious cybers.

Some startups use AI to solve this problem. The company uses AI’s huge feature to see millions of features in each suspicious file, and even detect the most minimal code change.

III, Improve the operational efficiency of the safety operation center

The security team faces a key issue, and too many security alerts will bring alert fatigue. According to statistics, North American companies have averaged nearly 10,000 security alerts per day. In many cases, although the malware that is marked as suspicious may become a fish.

Artificial intelligence can integrate the internal logs between multiple information sources and information on monitoring systems with external threat information, automatic classification . This network defense is the nearest hotspot because it solves the network security problem of large-scale companies with their own security operations (SOC).

4, quantitative risks

Quantify the network risk facing enterprise is challenging. It is mainly due to lack of historical data, and a large number of variables are required. Nowadays, companies that are interested in being able to face risks and wish to assess third parties of these companies, such as network insurance companies, must experience cumbersome network risk assessment processes. The risk assessment is mainly through the questionnaire, and the respondment is in line with the measures taken by the enterprise, as well as the corporate governance and risk awareness. But in fact, this method is not enough to actually represent the network risk status of the company.

AI technology can handle millions of data points and generate prediction, which has the most accurate network risk estimation for enterprises and network insurance companies.

5. Detect network traffic is abnormal.

detects abnormal traffic that may indicate malicious activity, which is undoubtedly a huge challenge because each company has special traffic behavior. Through cross-protocol correlation, it is necessary to analyze the correlation between endless metadata in the internal and external network traffic in the invasive depth package detection.

6. Detecting malicious mobile app

The current smartphone has exceeded 2.5 billion devices worldwide, and the internal people of Ericsson Corporation (QQ public number: hack alliance Say: From 2020, it will reach 6 billion. By viewing popular 100 iOS and Android applications, ARXAN’s research shows that 56% of iOS applications and 100% of Android applications have been attacked.

In fact, according to (QQ public number: hacker alliance) learned: Google Play and Apple App Store These two leading app stores, their applications have across 2 million markings. These mobile applications need to be accurately classified. This classification method must be sensitive to the slight confusion technology, distinguish between malicious and benign applications, and can effectively classify by using advanced AI technology.

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