AI in CyberSecurity – Artificial Intelligence’s subsets i.e Machine Learning and Deep Learning are helping to fight with cyber attacks but the same time is used to work as a tool of attacks. We will be discussing these interesting phenomena in this post though this is the first post in “AI role in CyberSecurity” series by #AILabPage, the second post is available here
AI in CyberSecurity
In a cybersecurity context, AI is software that perceives its environment well enough to identify events and take action against predefined purpose. It can also learn and build the rules on the go as well; actually, that’s the real AI. The biggest fear of today’s time is the concern that hackers are getting much smarter. These hackers will use artificial intelligence in cyber attacks that are more sophisticated and harder to detect.
How AI is the Future of Cybersecurity ? What AI and Machine Learning will bring for CyberSecurity like wise we have many questions yet to be answered
We do have Artificial Intelligence in our systems and business strategies. Still, there is a frightening truth about increasingly common cyber-attacks. Which is most businesses and the cybersecurity players itself are not prepared for better use of AI.
AI has already proven to be both a benefit and a threat on the cybersecurity front. Barclays Africa is beginning to use AI and machine learning to both detect cybersecurity threats and respond to them.
Artificial Intelligence Dependency on Natural Intelligence Gaps
While the technology can help to fill cybersecurity skill gaps but at the same time its a powerful tool for hackers as well. In short, AI can act as a guard and threat at the same time. What matter is who use it for what purpose. In end, it all depends upon Natural Intelligence to make good or bad use of Artificial Intelligence.
There are paid and free tools available which can attempt to modify malware to bypass machine learning antivirus software. Question is how to detect and stop?
Cyber attacks like phishing and ransomware are said to be much more effective when they are powered by AI.
87% of US cybersecurity professionals report that either they are currently using or will use AI as part of their cybersecurity strategy.
On the other hand to power up the behavioural patterns AI, in particular, is extremely good at recognizing patterns and anomalies. This makes it an excellent tool for threat hunting.
Will AI be the bright future of security as the sheer volume of threats is becoming very difficult to track by humans alone. Maybe AI might come out as the darkest era, all depends upon Natural Intelligence.
Natural Intelligence is needed to develop AI/machine learning tools. Despite popular belief, these technologies cannot replace humans (in my personal opinion). Using them requires human training and oversight. AI is here to stay and it will have a large impact on security strategies moving forward. As results reveal Natural intelligence needs improvement as well.
AI Capability for CyberSecurity – As a Guard and a Terminator
Cybersecurity state as on date is too much vulnerable but the implementation of AI systems into the mix can serve as a real turning point. These systems come with a number of substantial benefits. These benefits will help prepare cybersecurity professionals for taking on cyber-attacks and safeguarding the enterprise.
Deploy AI and machine learning-based tech to help. With these helps tasks like policy enforcement, blocking malicious files and IPs, and protecting against phishing attacks. Machine learning won’t replace human intelligence rather should not be aimed for as well. These technologies can be used to automate and speed up security operations and repetitive tasks, according to the release.
Data Mining for Intrusion prevention and action in real time can be done to avoid misuse detection. Predictive models should be built from labelled data sets i.e for instance labelling data as “normal” or “intrusive”. Action required on top of these rules.
91% of cybersecurity professionals are concerned about hackers using AI in cyberattacks.
These models can deliver more sophisticated and precise solutions than manually created signatures based rules. Then challenge our self where we are unable to detect attacks whose instances have not yet been observed should become part of machine learning and on the fly building the same.
Anomaly Detection & Correction – AI Beyond If -Else Statements
Anomaly detection to build models of “normal” behaviour and detect anomalies as deviations from it. Possible high false alarm rate – previously unseen but may be legitimate can support system behaviours to be recognized as anomalies.
Integrating Artificial Intelligence into Cybersecurity can boost transparency levels in this playing field.
Security should be treated as a fabric for your network and business, which takes a platform approach. It can take threat intelligence gathered through Big Data analytics. After which it can automatically alert all inter-connected devices and with updated prevention.
AI-based signatures can work a lot better. All this is at a speed, low cost and should be within the reach of any organisation entrusted with. How it will be achieved depends upon the next step; which is the discussion point at length in a workshop.
In general, it is said firewalls no longer stop hackers but AI based cybersecurity can stop hackers though. The cybersecurity industry has always had a fortress mentality: Firewall the perimeter! Harden the system! This mindset has failed, miserably. Each new headline-generating hack has reminds us. Even if you do patching on all software’s you could still be at risk. It’s been proven already with attacks on cybersecurity.
Future of AI in CyberSecurity
Past & Future of Threats & Protection – the Year 2017 was dominated by news of major hacks, cybersecurity threats and data breaches. What will 2018 have in store? Cybersecurity threats and data breaches are on rising. What will 2019 will bring? We will see it in many ways why AI is crucial to cybersecurity.
Threat detection is certainly the main focus of today’s AI together with machine learning technology push. Not only it can monitor human behaviour, but also it can detect things that aren’t quite right and sound an alert.
As Enterprises are increasingly being entrusted with private data, the implications of leaks are potentially huge and wide-ranging. It is not just the individuals but big corporates in large numbers worldwide that are at risk. With correct guidance, direction and strategy business can lead to overcoming. AI machine learning has established what familiar patterns look like and can recognize normal traffic.
Machine Learning – A Cool Tool
Machine learning is both cool and valuable, but to apply it effectively requires that we disregard the former in order to be rigorous about the latter. In this session, we take a hard look at the qualities that make machine learning fit for purpose for problems in cybersecurity in order to lay out a global roadmap of how machine learning can help.
Some Questions to be answered –
- How artificial intelligence as a bundle of emerging technologies is shaping, securing and defining the future of cybersecurity?
- What is required for artificial intelligence to make this work as a jumpstart technique in order to lower cybersecurity cost?
Perhaps the most relevant answer is employing Artificial Intelligence. I have not used to deploy AI as employ is more relevant here for this work in a reward model.
If we don’t harness the power of artificial intelligence into cybersecurity then, hackers will eventually do this. It’s been known and said by many scientists who have got success in harnessing the power of artificial intelligence to create a program that, combined with existing tools, figured more than a quarter of the passwords from a set of more than 43 million profiles (One of the biggest social media platform).
In the info-security industry that comes first with leadership roles with best-developed products and excellent professional services, this will be known as the winner. Yet the researchers say the technology may also be used to beat baddies at their own game.
Points to Note:
All credits if any remains on the original contributor only. AI – a bundle of emerging technology is here which is powering every single business. AI is going to stay disrupt every business life. When AI will meet quantum computing for a friendly handshake that explosion would be a blessing to see. Number stats took from Webroot 2017.
Books & Other Material Referred
- Open Internet & Live conferences feedback and interactions.
- AILabPage (group of self-taught engineers) members hands-on lab work.
Feedback & Further Question
Do you have any questions about AI, Data Science, Quantum Computing, Deep Learning or Machine Learning? for FinTech or information security. Leave a comment or ask your question via email. Will try my best to answer it.
Conclusion – Artificial intelligence Just made guessing your Password a whole lot easier. In future with development and advancement of behaviour analytics, importance/requirement of passwords might vanish. Revenue leakage due to cybersecurity is the biggest issue for the legitmate industry but at the same time its a revenue source for the underground economy. The future of IoT spells blockchain and AI – the reality of blockchain today mainly spells cryptocurrency and hype. As on date we have 3 major challenges to our privacy and those are technology evolution, burgeoning security establishments (Face recognition) and no stop higher revenue motivations. The importance of a contextual view of threats that also incorporates visibility and data points from networks, endpoints, and human threat researchers to derive the most accurate cyber risk assessment.
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