Securing the Cyber Security
I

n the Cyber Security Arena - AI's crucial need today is to enable the engineers to handle the depth and detail spontaneously and accurately. Advancements in machine learning enable AI applications to mechanically adapt to changes in threats and spot issues as they arise. On the one hand, AI is a way security experts analyze, study, and understand cybercrime, and on the other, it can also be a tool in the hands of cybercriminals who use technology to improve their traits in cyber-attacks!


Here are some most pressing cybersecurity needs that AI tools and platforms can help to meet .


Detect "Stealth Mode" Activities

Cybercriminals are already inside many systems, waiting for the right time to attack. When they do, they often operate in stealth mode, unable to detect. With the help of AI, we can rapidly analyze multiple situations for suspicious activity and flag any possible malicious activity right away!


Stay Ahead in AI Race

Cybercriminals might have probably got there before you. There are multiple ways AI can be used for both helpful and harmful activities wherever it is enabled. Hence, it will be an arms race of AI versus AI due - detecting and blocking cyber threats using AI, while the hackers themselves might be using the same AI to analyze the data traffic on the network and enter the systems.


Workload Sharing and Maintenance - Cyber Security Teams

In these troubled times, where we are under strict lockdowns and quarantines due to COVID-19, AI can play a crucial role right now in offloading work from cybersecurity engineers. Enabling us to face security threats better during these tough times. AI can help us speed up the security breach detection process through various red flags and alerts. Patterns of network traffic can be mapped with any unusual activity within the network to create these alerts. Thus, optimizing the workload of cybersecurity teams.


AI to Rescue From

  1. Malware - Malware includes computer viruses, worms, Trojans, and spyware. Malware is created to make money illegally by stealing sensitive and confidential information from victim's computers. Malware makes its way to your system, through questionable downloads, infected websites, or an email with an infected file. When malware is introduced to a network, AI can immediately detect them and block them from accessing systems resources and causing further problems to your computer.


  1. Hacking - Hacking is an endeavor to use a non-public network within the personal computer. It is the unauthorized access to possess control over digital devices like computers, smartphones, tablets, and the entire network. AI can make our digital future safer and robust; imagine blocking the hackers from the network through machine learning-enabled security solution, which acts as a shield of the cybersecurity teams and avoid manipulation by hackers.
  2. Phishing - A term used for describing a wide range of tactics used by cyber attackers to trick you into handing them over sensitive information such as personal information, banking, and credit card details and passwords. They can lure you into providing your valuable data by acting as someone you know or as a legitimate organization. We can prevent it through employee security awareness and training the AI is the key part of solid phishing defense. We can avoid phishing by enhancing the level of computing performance with the help of AI. This high level of processing will improve your computer predictive modeling and identify attacks before they can even occur.
  3. Ransomware - Typically, a kind of malware that holds your pc hostage and demands money. It locks up your computer and threatens to destroy data and demands ransom or payment from you to regain your ability to use it again. The security software uses AI to detect, isolate, and delete the infected or corrupted files that can spread ransomware. AI models created by using unsupervised machine learning by Security software can recognize the difference between clean and malicious files with speed and more efficiency.

Enhancing Digital Security Systems

Ideally, suppose you are like many modern businesses. In that case, you will have multiple layers of protection, for example, you might have hardware or software firewalls as your first defense if hackers get past these defenses, they will encounter your antivirus or anti-malware then they might face your detection and intrusion prevention solutions.

But what if they get past these protections, and if a person is monitoring your cybersecurity manually, you are in trouble. Hackers might hack any time; they don't follow a fixed timetable to attack, so we have to rely on AI to help us fight against these intruders.


Examples of this type of security system are:

  1. 'ForAllSecure,' a startup based in Pittsburgh who launched Mayhem a fully automatic exploit defect detection system. Available for off-the-shelf as well as enterprise software installations. They are mostly used in smart devices and appliances, to spot and ascertain whether a Bug is exploitable. In software terminology, Bugs are errors that can cause unexpected results or can potentially lead to security breaches. If found, the bot autonomously produces a working control-flow hijack exploit string i.e., secures vulnerabilities.
  2. Another machine-learning startup PatternEx recently developed an artificial intelligence platform called AI2 that is claimed to predict cyber-attacks significantly better than existing systems by continuously incorporating input from human experts. The technology is leveraged by a continuous loop of feedback between the human analyst and AI system, called Active Contextual Modeling, and is able to learn in real-time.


Recruit AI to Shield against Intruders.

We can add AI, but as you might have guessed, it cannot be done overnight, and it needs a lot of training and groundwork to use it for your advantage. Some of the applications of AI with Cybersecurity include -

  • Create a more secure Biometric-based Sign IN.
  • Using Predictive Analytics detects Threats and Malicious Activities.
  • Use Natural Language Processing to Enhance Learning and Analysis.
  • Securing Conditional Authentication and Access

Once we have integrated the AI successfully, we should also learn how to use it effectively.



Few more applications of AI in Cyber Security
  • Gmail uses machine learning to block 100s of millions of spam emails for us every day by filtering out unwanted emails efficiently, creating a spam-free inbox.
  • IBM's Watson, a cognitive training software, uses machine learning for detecting threats in the cyberworld.
  • Balbix leverages Advanced AI for gathering and analyzing comprehensive inventory and threat information at the enterprise level.


Using AI in Cybersecurity - Impacts

  1. Although there are many advantages of integrating AI in cybersecurity, there are also challenges that we should face, one such challenge is - It requires more Resources and Finances than traditional non-AI cybersecurity solutions.
  2. The adoption of AI in cyber security can also lead to a whole new world of threats to digital security based on its Vulnerabilities. Just how AI can be used to stop cyber-attacks, the same way AI can also be used to launch more sophisticated attacks. There is always a risk of a more complex, and adaptive malicious software getting created that can exploit these vulnerabilities.
  3. Hackers can turn AI into a double agent to their advantage - Another risk of AI in cybersecurity comes in the form of Adversarial Artificial Intelligence, which means that something that causes machine learning tools to misinterpret the inputs into your system and behave favorably to the attacker. This occurs when the AI system's networks are tricked into misidentifying or misclassifying objects due to intentionally modified inputs.
  4. Affordability - Artificial intelligence applications are growing as a result of information science and big data, and this makes experts virtually unavailable on the market or laborious to seek out. As there aren't many AI-enabled cybersecurity solutions out there in the market, several firms face the danger of overspending.
  5. Unemployment - Like each AI-driven application, machine-controlled cybersecurity indicates a threat of state i.e, several firms don't keep IT specialists who manually take a look at the network. Instead, AI will get the task done automatically resulting in employing lesser number of engineers.


Every blessing comes with a disadvantage; with the introduction of AI, it can be used for both helpful and harmful purposes. By overcoming the disadvantages mentioned above, we can make AI the perfect solution for cybersecurity.

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  8. How Artificial Intelligence(AI) and Machine Learning(ML) are helping in Cybersecurity. Url