The term endpoint security is related to how to protect devices such as laptops, smartphones and other wireless devices used as storage devices to access our business network. Many would argue that these devices are the gateway to security breaches, but conclusions are now more common in communication and counting than fixed or local devices. We are subject to these laws and threats because most of the data is outside the business firewall exposed to these threats. Some of the most common threats to our system are vishing, cybercrime, crime, etc.
Listed below is more information on security threats and solutions provided by Artificial Intelligence (AI) and Machine Learning (ML).
1. Social Engineering
In these types of security breaches, people are arrested by criminals as they impersonate another person in order to extract certain sensitive information, confidential data or both. To combat any form of unauthorized access to sensitive information, a cloud-based stack should be installed to protect against script-intensive targeted attacks including malware. Today many AI application development tools are aimed at preventing such violations.
2. Theft of sensitive information
Theft of sensitive information is now one of the most common forms of attack aimed at stealing victim's personal information such as their banking details. Attackers often use fraudulent emails containing links to users on a malicious and malicious site. These sites are often synonymous with real sites and trick users into entering personal information, such as passwords. AI and ML work very well together to resolve any differences in emails. Since AI and ML can successfully navigate large amounts of data, it is best to analyze the metadata, content and context of these emails and take appropriate action against these malicious emails. Keywords like urgency and promotion are considered by the AI system as suspicious emails, however, the decision is made only after analyzing the entire email and the following parameters. That there should be a previous conversation between the subject and the content of the email, and if any of the domain names are misspelled when available. ML-enabled protection learns continuously from such situations and the feedback provided by the user. This makes security stronger every day.
3. Theft of sensitive information in a Planned way.
Spear Phishing is a very systematic attack. The attacker in this case has already done a background check on the user, knowing the user's most common interests, frequently visited sites and analyzing social media feeds. Users are then sent anonymous emails that lead the victim to open slowly. Eventually the user ends up downloading the malicious file. AI and ML help in dealing with these types of attacks. AI is used to understand the patterns of communication between the victim and the attacker, and if the system suspects an ML AI system it blocks it before creating any damage.
4. Irrigation hole
An irrigation ditch is a type of attack based on a system used by a hunter when its victim falls into a trap. Here the attacker often exploits the vulnerabilities and vulnerabilities of the actual website visited repeatedly by the user. ML and AI use horizontal algorithms to detect any type of malicious data. Horizontal algorithms analyze whether a user has been targeted to any type of malicious website. In order to plan such an attack on large amounts of data from a representative, email and packet traffic is required which can be prevented when scanning internally outside the ML system.
5. Network Smell
Network Sniffing is the process of analyzing data packets that travel to a specific network. Network sniffers constantly monitor all data through a legible and clear message transmitted by the network. The best way to deal with this problem is to use encrypted links between hosts. VPNs (Virtual Private Network) are used for encryption. With powerful ML VPN and AI protection protection has risen to a whole new level. These VPNs are equipped with an intelligent algorithm that creates a secure environment in an open network such as WiFi that integrates and encrypts all data sent to the network. This is done to stop the attacker from interpreting the information even when the data packets are captured.
6. DDOS Attack (Distributed Service Denial)
DDOS Attack to this day remains straightforward but still valid. Its purpose is to cause disruption or suspension of a particular host or server by loading it with large amounts of useless traffic (data) that renders servers unresponsive. Such floods occur simultaneously using multiple botnet (infected systems) DDOS is effective as it reduces bandwidth and tends to exceed easy detection and is often combined with other attacks that also prevent detection. ML-powered AI systems can easily distinguish between good or bad traffic. This discovery works in a matter of seconds and that is why such systems are selected as accurate, fast and can easily analyze large amounts of data in a short period of time.