Author: Riyas Vettukattil
Machine learning is the science of getting computers to act without being explicitly programmed. This is achieved by several set of algorithms that can learn from and make predictions on data.
In the recent years, we have witnessed self-driving cars, speech recognition systems, better and effective search engines, and a better understanding of the human genome with the aid of developments in machine learning.
Machine learning is getting extensive so that you may be using it several times in a day without even knowing it. Common applications of machine learning in today’s technology include voice recognition, fraud detection, email spam filtering, text processing, search recommendations, video analysis, etc.
A recent survey showed that 81% of respondents believe that machine learning will have some impact or significant impact on their organization in the next five years.
One of the major contributors for the rapid growth and improvement in machine learning in recent years is “Big data”, which deals with generating, storing and analyzing huge sets of data.The availability of cheap and plentiful computation has further helped to the rapid growth in this area of technology.
When we look at the recent landscape in the cyber security industry, the collection and storage of large amounts of useful data points is already in place. It is not surprising that most of the security analysts are challenged by the vast amount of raw data from dialing monitoring systems even though there are several tools to help them analyze and interpret this large data.
The cyber security game is complex and the challenges are never ending. There is always a growing demand for qualified and experienced individuals to successfully defend and manage vital infrastructure and systems against intruders and malicious actors. Even a minor flaw by a security team may be enough to create a major security incident.
You may be interested in reading: Securing Internet of Things(IoT) – How a Connected Device may Risk your Life?
Machine learning provides the possibilities for round the clock monitoring and can easily handle larger data loads than a human can deal with. This can help to priorities and utilize human efforts in a more productive manner by reducing the time spend on unimportant signals.
If we take the other way around, it is possible that in future we will see a variety of cyber-attacks and malicious actors who can use AI and machine learning for creating more sophisticated cyber-attacks towards organizations. Such scenario can be tackled only by adopting machine learning and AI to strengthen the personals and tools used in cyber security.
Business actors and c-level executives are advised to familiarize themselves with the cutting edge of safety with Artificial Intelligence and Security Research
Challenges and Threats with AI
- AI can be used to protect, defend and to attack cyber infrastructure.
- AI can be used to automatically identify the attack surface that hackers can target.
- AI can be misused to perform more automated and increasingly sophisticated social engineering attacks.
- AI-enabled cyber attacks can cause an epidemic-level spread of intelligent computer viruses which can mutate and evade Antivirus products.
- The only solution to defend against AI-enabled hacking is by using AI
- The worst outcome will be beyond simple imagination, there is potential to damage human well-being on a global scale.
- Talent shortage in information security: A report from (ISC)2 shows that there will be more than 1.5 million unfilled positions by 2020 in the field of global cyber security. AI can help in this situation to equip the professionals with powerful tools
- AI enables analysts to focus on more advanced investigations rather than spending valuable time on data crunching.
- AI, when applied in an interactive manner, together with humans, can promise several opportunities for identifying, combating, and managing cyber risks.
To summarize, machine learning has an immense potential in the future for mitigating cyber-attacks. This will not be a fully automated solution but will need proper tuning by human experts. This will help to filter real attacks from other activities which may appear suspicious but are actually benign activity.
Key idea behind machine learning in cyber security is not to replace firewalls, antivirus, or human security experts, but to complement these more traditional defenses to create a more multi-layered defense.