Intigrating AI with Cyber Security

Intigrating AI with Cyber Security


What is Integrating AI with cyber security?

Artificial Intelligence is a branch of science that stimulates the human intelligence processes with the help of machines. It is a kind of natural behaviour that is worked on by the machines. AI techniques are being used in several different fields like:

  • Gaming sector
  • Agriculture sector
  • In Robots
  • In cyber security
  • In Police stations for investigation
  • For face and speech recognition
  • In Medicals and at hospitals

AI plays an important role in these areas, especially in the digital era. AI has the capability of learning new things with the help of structured and unstructured sources and algorithms, and has the reasoning power to identify the relationships between threats, malicious documents, suspicious IP addresses and several others. AI is augmented towards real-time sources as it eliminates time-consuming research tasks and provides optimal and best solutions for risk analysis.

Thus, combining the AI concepts with cyber security is sometimes referred to as Integrating AI with cyber security, thereby producing advanced and secured results on people’s devices.

Role of AI in Cyber Security

Artificial Intelligence is important because it enables human capabilities, helps in understanding, reasoning, planning, communication and perception that are to be undertaken by software thereby increasing effectivity and efficiency at low cost. AI is significant because it helps in successfully tackling a profound set of technical challenges. It automates repetitive learning and discovery through data. AI is different from hardware-driven, robotic automation. AI performs frequent, high-volume, computerized tasks reliably and without fatigue, and efficiently.

AI has been continuously evolving and it is getting easier day by day to detect and solve attacks. AI systems are trained to detect and analyse malware and ransomware attacks at an early stage, before entering into the system. They help in monitoring and analysing the multiple endpoints for the cyber threats that are emerging, it helps in detecting the malicious activity before a full successful attack could be made, and it helps in eliminating the zero-day vulnerabilities.

Artificial Intelligence and Cybersecurity Opportunities and Challenges

With the advancements made in making the digital life easier to access, there are several challenges faced in the field to provide such advancements.

Such challenges are:

  1. Business Threats:
    The company, while advancing its tools for more security, sometimes receives threats for not doing so, or face the consequences doled out by the criminals.
  2. Supervised Learning:
    As we know that learning is a process that never stops, so regular updates and supervision has to be done on the learning process, which is a big challenge as every time requires something to be added into the process, to make it more flexible and attractive.
  3. Security Risks:
    The biggest challenge is the security risks that are faced, because while advancing the tools or the software, it requires AI, and sometimes requires data to be unlocked by the company for applying it. So, keeping the data open for a few minutes or seconds could get it exposed and leaked, posing a huge security threat to the company. So, security risks are most experienced in cyber security and artificial intelligence.
  4. Insider Threats & Device Management:
    Sometimes , this can also be a challenge, as while making the AI advancements, it has to be kept in mind that the logic applied to it, should be applicable on all devices, else, would be insecure for some and secure for some. Thus, device management and insider threat challenges are also present in cyber security and artificial intelligence.

Examples of AI in Cyber Security

There are various AI applications in Cyber Security with real time examples:

  1. Used in Security Screening that is done by immigration officers and customs authorities to do human based screening that can lead to errors
  2. It is also used in security and crime prevention by the police departments as there are several software tools that help in detecting terrorists’ threats, and other such threats and malware attacks on the systems.
  3. It is helpful in detecting and analysing the mobile endpoints. Google uses AI to analyse mobile endpoints threats. It is also used to provide mobile security solutions to users to protect their devices.
  4. It enables AI powered threat detection and response platforms, which collects and stores the network meta data and provides unique security insights in real time.
  5. It helps in detecting sophisticated cyber-attacks, by modelling and analysing the behaviour of every device, user, and network to learn specific patterns and perform certain actions.
  6. It helps in reducing the threat response time as the software is updated on a timely basis, so that they have the capability for better detection and response time for advanced and new generation threats. This includes ransomware, malware, social engineering, encrypted attacks, etc.

Top AI in Cyber Security Projects

There are several AI projects with Cyber security that are brought out by the government as well as the private companies.

  1. ADFA Intrusion Detection Datasets:
    These are designed for the evaluation of traditional Host Based Intrusion Detection System (HIDS) and it works on both Linux and windows.
  2. ISOT Botnet and Ransomware Detection Datasets:
    This is a combination of several malicious and non-malicious datasets that are available, along with the ransomwares.
  3. Spam filter applications:
    AI is used in Gmail to detect and block unwanted spam mails and fraudulent messages.
  4. Fraud detection:
    AI based projects are used for detecting frauds with the help of algorithms that are based on predictable customer behaviour, and access the purchase items to check whether it is a regular purchase or not.

AI Threat to Cyber Security

As with the emerging digital world, where cyber security has become a big concern, AI is being developed with advanced techniques on a daily basis for making it easier for people to access AI based applications. But with the update made in AI, there are threats to AI as well, which the people while accessing and providing digital identity should keep in mind so as to protect themselves digitally.

There are several threats posed by Artificial Intelligence to cyber security.

  1. While monitoring and responding to the threats, the individuals’ data might get leaked.
  2. Encourage the criminals to create more sophisticated attacks
  3. Requires more resources and costs

Artificial Intelligence in Security Systems

Artificial Intelligence plays a very important role in security systems as well. These days, security systems have to be maintained with full privacy and confidentiality so that the customer’s details are not leaked from the database.

A recent case study, where the Air India passenger’s data got leaked on public servers, put the passengers who travelled with it in peril, because, their personal details including the card payment details and their location was leaked, from where the criminals could easily track the person and get to know his current location.

Cyber crimes such as these are commonplace these days, posing a great threat to the confidentiality and privacy of one’s data.

Thus, as AI is important in the cyber security field, it is important in the security systems as well; as it helps in maintaining the security of the company, keeping the database information secure using several algorithms.

Conclusion

Artificial Intelligence’s role is more flexible and robust than the traditional cyber security solutions. AI is adding value to the security sectors of corporations and individuals as well. In order to give AI more authority in the near future for security purposes, we need to make sure that it stays with the white hat people only. AI’s role in cyber-security is preventing cyber-attacks to a larger extent, and has an increased scope in providing a greater percentage of positive results in the future, due to higher usage.



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