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What is the Impact of Artificial Intelligence on Cyber Security?

Last updated on March 3, 2021, 12:12 p.m. 6567 Views

Kirandeep Kaur

Kirandeep Kaur |

3+ Technical Content Writer. and who is passionate about his career

What is the Impact of Artificial Intelligence on Cyber Security?

Last updated on March 3, 2021, 12:12 p.m. 6567 Views

Kirandeep Kaur


What is the Impact of Artificial Intelligence on Cyber Security

The increase in the growth of technologies is also leading cybersecurity at risk. With the new advancements, security professionals have been going through challenges and are failing at some point. Humans cannot keep up with the volume of potential attacks and intrusions the way artificial intelligence can. While AI is demonstrating profoundly valuable for battling digital wrongdoing or cybercrime, in the possession of malicious actors, AI additionally can be utilized for odious purposes. This blog backs the window ornament on the job of AI and AI in cybercrime and digital security. Let us harness the power of artificial intelligence in cybersecurity.

“51% Share of organizations that have high utilization of AI for detection of cybersecurity threats”

Biggest failures of Artificial Intelligence in cybersecurity

  • IBM’s Watson for Oncology canceled for $62 million and unsafe treatment recommendations
  • Microsoft’s AI chatbot corrupted by Twitter trolls
  • Apple’s Face ID defeated by a 3D mask
  • Amazon’s axes their AI for recruitment because their engineers trained it to be misogynistic
  • Amazon’s facial recognition software matches 28 U.S Congresspeople with criminal mugshots
  • Facebook’s chatbots developed their own language
  • Mitra the robot failed to greet the prime minister
  • Autonomous and driverless vehicles turned disastrous
  • iPhone X’s face recognition could not differentiate identical twins
  • Alexa orders all the dolls houses
  • Alexa causes the police to be called
  • Uber’s self-driving car kills a pedestrian
  • Yahoo’s massive empire crumbled under the weight of heavy-weight data breach of its three billion accounts.
  • Marriott's ill-suited security lost details of its 500 million guests.
  • LinkedIn was touted as LinkedIn for losing accounts of 117 million members.
  • The adult network site FriendFinder Barenaked details (names, passwords, and email addresses) of its 412 million private members out in broad daylight.
  • Court Ventures lost exclusive data of its 200 million users to just one hacker.
  • 113 million health-conscious FitMetrix users inadvertently shared their fitness details with hackers.
  • Myspace lost its 360 million accounts before sinking into obscurity. and many more…..

Why did Artificial Intelligence fail?

  • When you don’t have a good R&D team or you cut money for them
  • When you prioritize technology over business strategy
  • Working without a clear vision
  • Developing without addressing business requirements
  • When you stuck in a never-ending development loop
  • Assuming your customers are like developers
  • Assuming the AI hype is enough to succeed
  • Most AI models decay overtime
  • AI systems are more complex than traditional software
  • Optimizing for the wrong thing

“12% of the overall time taken to detect threats and breaches is reduced, with AI”

Artificial Intelligence services for cybersecurity

  • Digital Risk Management
  • Identity and Access Management
  • Endpoint Detection and Response
  • Cloud Access Security Brokers
  • Spam Prevention and Phishing Blocking
  • Statistical Methodology
  • Malware Detection
  • Behavioral Analysis

Kinda AI solutions companies are looking to build

  • The Rule-based detection systems for the handling of false positives results while handling attacks
  • Hunting of threats efficiently
  • Complete analysis of threat incidents and investigation
  • Threat forecasting
  • Retrieve the affected systems, examine the root causes of the attack, and improving the security system
  • Monitoring of security

AI is just another tool in a cybersecurity professional’s belt that can help them focus on the more critical and strategic work to be done in cybersecurity by relieving them of the more repetitive tasks.”

Neal Fisch Director of Enterprise Services and Security at California State University Channel Islands

Core capabilities of using artificial intelligence in a cybersecurity system

System Security

 

Network Security

Cloud Security

IoT Security

Malware

Autonomous Security

Data Security

 

Security Analytics

Threat Prediction

ML for Cyber

Social Network Security

Insider Attack Detection

Application Security

 

FinTech and Blockchain

Risk and Decision making

Trustworthiness

Data Privacy

Spam Detection

Bringing issues to light of cybersecurity benefits

Fixing IT security in the manners we've referenced requires some serious time and money. Subsequently, a few heads may shy away and hope present security methods and procedures are sufficient. That is the reason it's significant to make pioneers mindful of the dangers of a security break or infection flare-up. Another test is staying aware of the pace of developing threats. That is the reason technology organizations are making colossal interests in AI-based security arrangements. Changing over manual work into mechanized work is making organizations progressively serious. In any case, the machines that are accomplishing the work that individuals once did are liable to cyber-attacks as well. Shielding them from the new rush of human and robotic programmers has gotten vital.

More benefits of artificial intelligence in cybersecurity are:

  • Performance: It includes the expulsion of unnecessary data. Feature Extraction and Selection, Data Cutoff, Parallel Processing, Machine Learning, and Deep Learning Algorithms, Result Polling, and Optimized Notification are included.
  • Accuracy: It includes Alert Correlation, Signature-Based Anomaly Detection, Attack Detection Algorithm, and a mix of Multiple Detection Methods, Algorithm Selection.
  • Scalability: It includes Dropped Netflow Detection, Dynamic Load Balancing, and MapReduce. Netflow Detection including Netflow Sequence Monitoring, Netflow Collection, Netflow Storage, and Data Analysis, creating cautioning messages.
  • Security: It includes Source Data Transformation containing User Activity, Application Activity, DataBase Activity, Network Activity, Distributed Data Storage, Public Key Infrastructure, and Encryption.
  • Alert ranking: The pre-handled security occasion information sent to the Data Analysis module, which examinations the information for recognizing Cyber assaults. The aftereffects of the examination (i.e., alarms) sent to the alarm positioning segment, which positions the cautions dependent on a predefined measure.
  • Reliability and usability: It includes Data Ingestion Monitoring, Maintenance of Multiple Copies, Dropped Netflow Detection, and Alert Ranking.

How to get rid of Artificial Intelligence failures?

To get rid of AI failures, the focus should be on solving the real business problem that a business is facing rather than solving imaginary problems. The AI systems need to be up to date. The monitoring of all AI systems for anomalous behavior is required. Whilst creating AI models, thorough documentation of AI and ML systems is required. On the other hand, AI interpretability is also essential to debug AI systems and then, finally, run multiple security checks on your AI models. For some legislatures, the next phase of considering AI security will require making sense of how to execute thoughts of transparency, auditing, and accountability to adequately address the risks of AI decision processes and model data leakage. In a few points, cognitive AI-driven solutions for cybersecurity are:

  • Pattern Recognition
  • Anomaly, Intrusion, Incident Detection
  • Intrusion Response
  • Statistical Methodology
  • Malware and Spam Detection
  • Data Privacy, Risk and Decision Making
  • Threat Monitoring

“69% Share of executives who say AI in cybersecurity provides higher accuracy of detecting breaches”

New threats of artificial intelligence

While AI has enormously improved security groups' abilities to recognize, oversee, and ensure against threats, the technology may create new challenges. At DARPA's Cyber Grand Challenge in 2016, the world's first all-machine digital hacking competition, it was indicated that it is conceivable to completely mechanize misuse age and assault dispatch. Past mechanization, AI can help adjust an endeavor for a specific situation quicker and assist assailants with looking and group information worth exfiltrating too. Besides, AI can help mask assaults – as indicated by Max Heinemeyer, Director of Threat Hunting at Darktrace, "we expect AI-driven malware to begin imitating conduct that is generally ascribed to human administrators by utilizing contextualization". As we've seen, AI is as of now changing how different cybersecurity organizations are reacting to dangers and managing staffing deficiencies. Toward the day's end, AI is much the same as some other innovation – it very well may be utilized to expand how ventures secure themselves, or abused by aggressors to break considerably more endeavors and take valuable information.

AI in cybercurity market

The present difficulties – Technological limitations and location holes 

To start with, it is fundamental that we see the present difficulties. At this point, when you investigate the security design of numerous organizations, you see that a large portion of them have contributed a great deal to show signs of improvement esteem out of their security architecture and Security Operations Centre’s (SOCs). In the meantime, organizations are as yet attempting to ensure their organizations and their information. These issues emerge in light of the fact that interior procedures and security groups are constrained through mechanical limitations, which are intensified by the advancement of the attacks – and the attackers – that they face. Subsequently, we have to conquer mechanical limitations and computerize procedures to empower SOC groups to remain in front of even the most complex programmers. Dissimilar devices should be coordinated into a typical security design, and the advantages of AI with improved execution, better precision, and the treatment of huge datasets will empower mechanized and canny examination and reaction forms.

Winning the battle of Artificial Intelligence

Industries such as finance, retail, healthcare, and information security are the early adopters of AI. The spirited ecosystem of AI can also be seen active throughout the world to support large and small organizations deploying AI for cybersecurity. The future of artificial intelligence suggests a time of human intelligence is significantly enhanced by creativity, speed, and accuracy. AI enables us to respond in an intelligent way, understanding the relevance and consequences of a breach or a change of behavior, and in real-time develop a proportionate response. When we’re applying the human brain to what we are more confident about among human problems. The combination of machine learning and artificial intelligence technologies can provide entry-level professionals. According to a study by U.S. cybersecurity software titan Symantec - 978 million individuals around 20 nations were influenced by cybercrime in 2017. Researchers said victims of cyber-attacks lost an aggregate of $172 billion, i.e., an average of $142 per individual as a result. Though, currently, we are still in the beginning stage to analyze and contemplate better.

An AI is a computer system capable of carrying out activities that usually involve human intelligence. From SIRI to self-driving cars, artificial intelligence (AI) is progressing rapidly. Many companies trying to automate many job positions through the use of smart machines, there is a concern that people may be squeezed out of the workforce.

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