Beijing time on November 24th news, according to foreign media reports, with the popularity of the Internet, people's property is also rapidly digitized (private photos, customer sensitive data, intellectual property, etc.), then how to protect them becomes a business and individuals An important lesson.
Although billions of dollars of money are invested in the field every year, cyber attacks continue to emerge, and hackers have made a fortune. However, the emergence of AI can help a lot, it can allow security vendors, enterprises and individuals to take the upper hand in dealing with cyber attacks. Below, we will come together to take stock of the six key areas of AI network security innovation.
Detect and block hackers from infiltrating IoT devices
According to Cisco's forecast, the number of connected devices worldwide will increase from 15 billion today to 50 billion by 2020. However, due to the limitations of hardware and software resources, many networked devices do not have basic security protection measures. Last month's hacker's DDoS attack against the United States was the best proof. The first thing that was broken was an Internet of Things camera, and then half of the US websites were in a state of paralysis.
Even more frightening is that with the disclosure of the Mirai source code that uses the Internet of Things to launch DDoS attacks, such malicious programs are becoming increasingly rampant, and hackers can launch attacks against any business or individual. Internet of Things security is one of the most prominent areas in which AI technology has developed. The lightweight AI predictive model automatically resides and runs on less-performing devices, detecting and blocking suspicious behavior in real time.
Right now, a number of startups are using AI technology to address IoT security challenges, including CyberX, PFP Cybersecurity and Dojo-Labs.
Prevent malware and documentation from running
File-based cyber attacks remain the most important form of cyberattacks. Among the cyber attacks, the most vulnerable files include executables (.exe), Acrobat Reader (.pdf), and Microsoft Office files.
Small changes in a single line of code can produce new malicious files that have the same malicious intent but leave different signatures.
Similarly, minor changes can create signature-level anti-virus programs or other heuristic advanced endpoint detection and response solutions, and today the most deadly is the network and solution sandbox.
Several start-ups are trying to use AI to deal with this problem. They use the enormous capabilities of AI to look at the millions of features of each suspicious file and discover even the slightest code conflict. The leaders in developing this file-based AI security system include companies such as Cylance, Deep InsTInct, and Invincea.
Improve the operational efficiency of the security operations center
One of the most important issues for security teams is the alarm fatigue caused by a security alert overflow every day. For example, companies in North America receive at least 10,000 security alerts a day, which keeps the security team running. In many cases, this may make malware a "missing fish", even though it has been marked as "suspicious target." To be foolproof, multiple sources of information, integrated internal logs, and monitoring systems with external threat intelligence services are needed to automatically categorize all events.
This area has now become a hot spot for network security, and large enterprises can use this technology to protect their own security operations centers. Some startups are using AI technology to address this threat, such as Phantom, Jask, StatusToday, and CyberLyTIc.
Quantitative risk
How to quantify the cyber risks faced by enterprises is a big challenge, and this is mainly because we lack historical data and there are too many variables to consider. For companies eager to quantify their own network risks, they must go through cumbersome cyber risk assessment procedures. The program is mainly based on the questionnaire to see if the various measures taken by the company meet the network security standards. But to deal with real cyber risks, this approach is not enough, then AI technology can come in handy.
With AI's powerful computing power, we can process millions of data points in real time and generate forecasts to help companies and network insurers get the most accurate cyber risk assessments. Several start-ups are participating in such research, including BitSight and Security Scorecard.
Network traffic anomaly detection
How to detect abnormal traffic is a huge challenge for security companies because each company has different ways of consuming traffic. However, by looking for cross-protocol correlation, and relying on intrusive deep packet inspection to analyze the endless metadata correlation between internal and external network traffic, AI technology can check for abnormal network traffic. Startups focused on the field include Vectra Networks, DarkTrace and BluVector.
Malicious mobile app monitoring
Ericsson predicts that the number of smartphones in the world will rise from the current 2.5 billion units to 6 billion units in 2020. Through research on the top 100 most popular apps on Android and iOS, research firm Arxan research found that 56% of apps have been hacked. At the moment, there are more than 2 million apps available in both the Google Play and App Store apps, and we need to categorize them precisely.
To do this work, you must find out the slightest confusion technique to determine if the application has a malicious factor, and AI is the best classification assistant. Companies developing the technology today include Deep InsTInct, Lookout Mobile Security and Checkpoint. (Compile / Lu Jiahui)
Roll Forming Machine
Roll Forming Machine consists of feeding, molding and cutting board after color production appearance tidy and beautiful, high strength, durable, widely used in industrial and civil buildings, such as factories, warehouses, stadiums, exhibition halls, theaters room surface and wall.
Its components including roll forming parts,PLC, computer control system, hydraulic pump station system, automatic cutting system.
Roll Forming Machine must use high pulse input function, high input of excellent performance, choose AB phase interference ability. And by setting interrupt function, ensure accuracy.
Our company is the most powerful manufacturer in cold roll forming machinery in China.
Symple Specification need offered.
1 Coil Width:
2 Cover Width:
3 Rolling Speed:
4 Rolling Thickness:
5Machine Dimension(LXWXH):
There are some popular types of Roll Forming Machine:
1 Corrugated Roofing Roll Forming Machine
2 Glazed Tile Roll Forming Machine
3 Ridge Cap Roll Forming Machine
4 Roof And Wall Panel Roll Forming Machine
5 CZ Purlin Roll Forming Machine
6 Trapezoidal Sheet Roll Forming Machine
7 Light Steel Keel Roll Forming Machine
8 Floor Deck Roll Forming Machine
9 Sandwich Panel Roll Forming Machine
10 Double Deck Roll Forming Machine
Our product was passed strict quality inspection. We have testing department to make sure quality of machine are trustworthy. The quality of the Roll Forming Machine is very reliable.
If you have any questions, please contact with us directly, and welcome to visit our factory.
Roll Forming Machine,Cold Roll Forming Machine,Roll Forming Machine Design,Sheet Metal Roll Forming Machines
HEBEI HANMAC MACHINE CO., LTD. , https://www.chinahanmac.com