Improvements of cybersecurity by AI and its applications

Improvements of cybersecurity

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The cybersecurity companies have witnessed a significant growth amid the COVID-19 crisis. With the world going digital, several people are investing in cybersecurity.

Also, cybersecurity is an important issue because the government, corporate, financial, military, and medical organizations collect, process and use a huge amount of unparalleled data on computers and various other devices.  A significant percentage of data can be sensitive information, whether that can be intellectual property, personal information, financial data or other type of data that requires unauthorised exposure is categorised under malicious attack.  In order to avoid these attacks, cybersecurity is of utmost importance.

Is it absolutely necessary to use AI in cybersecurity?

Well! The honest answer to this question is YES. It is the need of the hour to use AI in cyber security because AI has its own advantages when collaborated with cybersecurity. Some of the main advantages of AI in cybersecurity are listed below:

  • Processing of massive volumes of data: The most significant advantage of AI in cybersecurity is its ability to process multiple and huge amount of data. It is done by automation of creating algorithms to protect the data from threats. This processed data covers a huge set of IT network elements. This data might include shared files, sites visited, emails, third-party software, and patterns of hacker activities. Since AI is more thorough and accurate than the human effort, it requires less time to process all the data. It therefore uses robust processors which come along the artificial intelligence security software. These processors zip through bulk amount of data immediately and within it comes up with a solution.
  • Picking out the tiniest threat:Generally, Cyber criminals keep a track and always work in the shadow, waiting to attack at the most vulnerable situations. . They also keep updates on new ways and tricks to infiltrate the network. As they are advanced in camouflaging themselves better, their threats go unnoticed by the human eye. However, the usage of artificial security in cybersecurity detects and provides solution to the weakest threat in the system.
  • Accelerating detection and response time:AI is greatly beneficial when it comes to speeding up the genuine issues. AI is useful in cross-referencing multiple alerts and source data rapidly. Despite cybersecurity experts dictating the order of solving the incidents, AI does most of the work.
  • Tackles advanced hacking techniques:Hackers use advanced and complicated techniques in order to breach networks and data. For instance, the techniques of obfuscation, polymorphism, etc. which are very malicious and difficult to identify. A countermeasure to avoid the breaching of personal data is utilising social honeypots. These honeypots are used as a decoy user in order to try and trap the attackers.

AI in cybersecurity has some amazing predictions for 2020!

  • Machine learning and AI will continue to facilitate asset management improvements which will also provide exponential gains. It is said that these exponential gains will be helpful in increasing IT security by providing greater endpoint resiliency.
  • The AI will be used to analyse defence mechanisms and simulate behavioural patterns in order to bypass the security controls, and machine learning to hack into organisations.
  • AI and machine learning will provide hinderance to the hardware finding its way into organization’s supply chain.
  • AI in cybersecurity can be used for fighting supply chain corruption. Since, there has been reports of corrupt supply chain which took place because there is no way to determine who has access to the data as people tend to work in remote coworking places. But as it is suggested that AI will be utilised in business which will help in knowing the corrupted supply chains.
  • It is also said that cybersecurity will chance the scenario of how we deal with cyber threats. The attackers or hackers influence ML and AI to take advantage of the vulnerabilities and to gain access to the most valuable business systems and network. This has made IT security organisations to keep up, but it is very impossible to stay ahead of the threats.
  • It has also been known that AI can be used for taking over accounts and along with the increasing number in the account takeovers, AI will become a vital source to overcome this issue. The average consumer will eventually realise that the password protections are no longer secured as they can be easily logged in. Also, the captcha that is used does not know who is logging into it becomes a lot less reliable. Because of this, AI will be the most essential for protecting the consumer’s online journey including the online payments transactions.

Taking a glimpse at the applications of AI…

  • Security screening: There are immigration officers and custom who can detect people lying about their intentions is done by security screening. Nevertheless, these screening processes make mistakes sometimes but are considered more efficient than humans as it is known that the human nature can be easily distracted and tired. The US Department of Homeland has developed a security system called as AVATAR. This AVATAR system screens the body gestures and facial expressions of the people. It has been designed to recognise the tiniest and the minute changes in the body gestures and the expressions which may give rise to suspicion. This system also has a feature which can distinguish the changes in the voice because it is intended to ask questions during the screening process. If at all a passenger is suspected he/she is flagged.
  • Crime prevention and security: The Computer Statistics (CompStat) AI system is an early AI system used the police department of New York City in 1995. It includes organizational management, and philosophy which depends on different software tools. This system was used for “predictive policing” and it has been used since then to investigate crime across the US. California based Armorway is using AI and game theory to predict terrorist threats. The Coast Guard also uses this system for port security in New York, Boston, and Los Angeles.
  • To analyse mobile endpoints: Google has initiated AI in order to analyse mobile threat endpoints and the organisations can use this in order to protect the growing number of mobile phone devices. To adopt mobile anti-malware solutions which incorporate AI, Zimperian and Mobilelron have collaborated. Mobilelron’s compliance and security engine can address challenges like device, network, and application threats along with AI integration of Zimperian. Skycure, Lookout, and Wandera are the other vendors that offer mobile security solutions and each of these use their own AL algorithms to detect the potential threats.
  • Reduces threat-time response: There was a global bank which was facing cyber threats and advanced attacks. The bank needed to improve its threat detection and response as their current solution was not effective in detecting threats and mitigating new generation of threats. They decided to deploy Paladon’s AI based Managed Detection and Response Service (MDR) service which is based on machine learning capabilities and data science. The bank’s threat detection and response capabilities were enhanced and improved which included ransomware, malware, zero-day attacks, social engineering, encrypted attacks, data exfiltration, advanced target attacks, etc.

Thus, it is known that the impact of AI in our lives is bound to grow in the increasing years are more technology will be integrated into our lives. For cybersecurity, the main subsidies concentrate on faster analysis and mitigation of threats.

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