In this article, we will analyze 80 private security companies that have introduced artificial intelligence technology in the current market, and divide them into nine categories according to their respective security fields.
Since last year, the network security start-ups have gradually attracted the attention of the market, followed by a large number of capital injections from investment companies. According to statistics, the transaction activity of network security companies in the first quarter of 2017 (including a series of things such as investment and merger) has far exceeded the average level of the past five years. With the increasing investment in private network security companies, a large number of excellent network security start-ups are emerging in the market. With the continuous development of network security technology and artificial intelligence technology, many security companies have begun to use the advantages of artificial intelligence technology to provide new solutions for new network threats.
According to the statistical results of AI deals tracker of CB insights, network security is the fourth most active industry in the field of AI technology application.
In this article, we will analyze 80 private security companies that adopt AI technology in the field of network security based on the data provided by CB insights, and divide them into nine categories according to their respective fields and operation modes. It is worth noting that two of these companies, with a market value of more than $1 billion, are Tanium, an automatic terminal protection company, and cylance, an intelligent forecasting company.
Domain subdivision
Anti fraud & identity management
Anti fraud and identity management are the most popular fields in the current network security AI market. The start-ups in this field mainly guarantee the security of online transactions by identifying the identity of fraudsters. For example, feedzai uses machine learning algorithms to detect fraud in financial transactions. Similarly, companies like concur use machine learning algorithms to detect fraud in websites and mobile applications.
Mobile Security
In this field, appthority, a start-up company, is quite outstanding. The cloud platform provided by the company can automatically identify the security threat behavior in mobile app, and automatically assess the threat. The detected targets and behaviors include known and unknown malware, new malware used in targeted attacks, enterprise data disclosure and intellectual property exposure Wait. Similarly, the prediction technology developed by skycure uses large-scale crowd knowledge to actively identify security risks and improve the security of mobile devices.
Predictive intelligence
Leaders in security start-ups like cylance hope to use machine learning algorithms and complex mathematical calculations to speculate the attacker's attack purpose and mentality. In order to achieve this goal, the company provides customers with technologies and services that can predict and prevent advanced network threats. Similarly, sentinel one uses predictive execution modeling technology to detect and protect the security of network devices and detect various unknown network threats in real time.
Behavioral analytics / anomaly detection
Darktrace, a start-up in this field, uses advanced mathematical methods and machine learning technology to detect abnormal behaviors in organizational systems and networks, and detect network attacks based on abnormal information. The method adopted by darktrace can not only help enterprises resist external attacks, but also prevent state-level hackers and network criminal groups who have invaded the enterprise network from stealing their own information and intellectual property rights. Companies like behaviosec also offer behavior based biometric systems that create digital fingerprints based on end-user behavior, such as monitoring keyboard records, mouse behavior, and anomaly detection, and then protect it organizations and e-commerce enterprises from digital fingerprints.
Automated security
Tanium, a security start-up, is one of the top companies in the field, using natural language processing AI and some terminal protection technologies to achieve large-scale terminal protection. Tanium will first query the status of each node in the enterprise using easy to understand language, then automatically retrieve the current status and historical status data of these nodes, and improve the overall security of the organization network based on these information. Other companies like demisto provide systems that not only automatically use more than 100 security products to complete automatic security tasks, but also combine manual analysis and workflow and other manual analysis tasks.
Network risk management
Companies in this field include network insurance companies and companies specializing in security policies and security implementation. Cybersaint, for example, has been committed to making the insurance industry fully aware of the impact of cyber risks and the opportunities and possibilities that cyber threats may bring to the insurance industry. Wiretap can help businesses manage the security of corporate social networks and collaboration tools, and prevent the disclosure of intellectual property and confidential data.
App security
Companies in this field are mainly focused on how to ensure the security of enterprise applications, rather than the security of the whole enterprise network. For example, authbase, which provides a framework to help developers improve the security of applications by finding vulnerabilities and monitoring web and mobile devices. On the other hand, cyber 20 / 20 can monitor network data and suspicious behaviors of applications, and automatically upload exceptions to machine learning platform for further analysis.
Internet of things security (IOT)
Spark alignment, a security start-up in this field, has developed an AI driven asset protection software, which can effectively protect the security and stability of IOT devices. While Bastille networks uses machine learning algorithm to protect the security of Internet of things devices in enterprises and campus. The service can identify invisible air threats such as hidden recording devices or signal transmitters, and give a preemptive response to data theft.
Fraud security
The solutions provided by illustrative networks can help users resist advanced persistent threats (APT) by actively spoofing and sabotaging ongoing attacks. Cyberfog company provides customers with a special deception tool, which can detect and resist network fraud and malicious attacks by creating a neural network composed of thousands of false computers, devices and services (the whole network runs under the monitoring of machine learning algorithm).
Market map
In the figure below, each company's business can span multiple categories. If you are interested in a company, you can check the form at the end of the article for more information.
Market classification map of network security AI company
*Reference source: cbinsights, compiled by FB editor alpha? H4ck, reprinted from freebuf.com