Artificial Intelligence Key To Do ‘more With Less’ In Securing Enterprise Cloud Services
Security professionals in the enterprise are facing an uphill battle to maintain control of corporate networks.
Data breaches and cyberattacks are rampant, sensitive information belonging to both companies and individuals is spilling unchecked into the underbelly of the Internet, and with the emergence of state-sponsored threat actors, it is becoming more and more difficult for organizations to keep up.
It is estimated the cyberattacks and online threats will cost businesses up to $6 trillion annually by 2021, up from $3 trillion in 2015.
Once cyberattackers compromise an enterprise network or cloud service, information can be stolen, surveillance may be conducted, or in some cases, ransomware attacks can lock down an entire operation and hold a business to ransom.
However, new technologies are entering the cybersecurity space which may help reduce the financial cost and burden on cybersecurity professionals pressed for time and often operating with limited staff and budgets.
Artificial intelligence (AI), machine learning (ML), and predictive analytics applications may one day prove to be the key to maintaining control and preventing successful hacks, data breaches, and network compromise.
These technologies encompass deep learning, algorithms, and Big Data analysis to perform a variety of tasks. The main goal of AI and ML is usually to find anomalies in systems and networks of note, whether it be suspicious traffic, unauthorized insider behavior and threats, or indicators of compromise.
Able to evolve over time, the purpose of AI technologies is to learn, detect, and prevent suspicious and dangerous activities with improvements and refinements the longer such applications and systems are in use. This provides companies with a custom cybersecurity system which tailors itself to their requirements, in comparison to an off-the-shelf, traditional antivirus security solution — which is no longer enough with so many threats lurking at the perimeter.
iboss CEO Paul Martini
In an interview with ZDNet, Paul Martini, CEO and co-founder of cloud gateway and security firm iboss said that enterprises are experimenting with these kinds of technology to “alleviate the staffing pressures caused by the well-known skills shortage in cybersecurity.”
Cybersecurity Ventures estimates that by 2021, there will be 3.5 million vacancies in the cybersecurity market left unfulfilled. To make matters worse, a report from Capgemini estimates that only 43 percent of individuals in IT roles have the cybersecurity skills required for their jobs.
While the market as a whole, training facilities, and IT organizations rush to bridge the gap, AI and machine learning technologies may be able to alleviate some of the pressure that enterprise players now face to keep data secure and networks safe.
“AI, predictive analytics, and automation allow security teams to leverage technology and do more with less,” the executive says. “AI and predictive analytics are critical aspects of improving efficiency and productivity because they reduce the number of false alarms and streamline time-intensive manual tasks.”
“For cloud services, in particular, AI and predictive analytics can leverage network anomaly detection to not only identify potential security concerns but performance issues like latency,” Martini added.
The range of these technologies is broad, but according to the executive, “any technology that takes the burden off your security and IT team is extremely useful.”
Behavioral analysis, malware prevention, and email-based security solutions are of particular use to enterprise players when the cloud is concerned.
AI, machine learning, and predictive analytics used to monitor cloud services and networks can detect suspicious traffic, anomalies, and fraudulent emails, in order to hopefully prevent an attack before it occurs.
As both personal and corporate networks have now evolved from simple PC to router systems to include mobile devices, different operating systems, and Internet of Things (IoT) products, more robust security systems are required to keep threats at bay.
“AI and predictive analytics certainly make it more difficult for threat actors to penetrate networks but as we’ve seen throughout the years, threat actors are innovative and resourceful, skilled and dedicated attackers will continue to find ways to penetrate network security,” Martini says. “While AI and predictive analytics will do well preventing the most frequent and basic attacks, highly targeted attacks that leverage unorthodox or custom attack methods will continue to cause problems for enterprise security teams.”
However, AI and machine learning technologies are not intended to replace cybersecurity teams or human input.
Instead, these technologies are best suited as a means to augment security teams — freeing them up from manual tasks to focus on more difficult challenges, patch processes, and critical security issues.
See also: AI is becoming ubiquitous across enterprise software
Data also comes into the mix. AI, ML, and predictive analytics are only as effective as the information the systems are working with, and unless enterprise firms are collecting high-quality information relating to services, users, network traffic, and more, they may find that avoidable false positives and incorrect conclusions will reduce performance levels.
“AI and predictive analytics are better suited for cloud-based cybersecurity functions because they have the benefit of larger datasets,” the executive added. “The more historical and real-time data AI programs have, the better they will be. While AI and predictive analytics will still be valuable for traditional security solutions, the highest level of performance will always be in the cloud.”
According to Gartner, 59 percent of organizations are still in the midst of developing AI strategies, while the remainder is in the process of piloting or adopting AI solutions across the board.
The research firm says that enterprises should focus on narrow AI, which are ML-based solutions which target specific tasks, including security and monitoring, rather than general AI applications, in order to maximize business value.
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Artificial Intelligence Is Rapidly Transforming The Art Of War
Several months ago, Vladimir Putin said, “Artificial intelligence is the future, not only for Russia, but for all humankind … whoever becomes the leader in this sphere will become the ruler of the world.” Artificial Intelligence (AI) and its sister technologies will be the engine behind the fourth industrial revolution, which the World Economic Forum described as “unlike anything humankind has experienced before.”
These technologies are capturing people’s imagination. However, one area remains in the shadow of public discourse: AI’s implications for national security and future warfare.
AI’s promise, in the context of national security and armed conflicts, is rooted in three main fields: improving efficiency through automation and optimization; automation of human activities; and the ability to influence human behavior by personalizing information and changing the way information is shared.
Efficiency — the optimal use of minimal resources — is key. In 2016, Google successfully reduced its data center cooling energy use by 40 percent with the “deep mind” neural network. If military planners could reduce spending by 40 percent while maintaining a high level of strategic supremacy and operational readiness, precious resources could be allocated to long-term capacity building, as well as curing the chronic disease of democracy — the constant, growing burden of defense and security spending.
The characteristics of the current and future battlefield pose a great challenge to advanced militaries. Modern battlefields have become a hide-and-seek playground, especially since armed conflicts now focus on heavily populated urban areas. Advanced militaries must choose one of two alternatives: exercise air power, thus causing civilian casualties, or deploy boots on the ground, thus risking heavy losses.
AI could change this costly equation. Combined with “big data” and predictive analytics, it could help militaries identify patterns, links, and anomalies in vast amounts of information. Image processing could find the enemy needle in the urban haystack, while fusion centers could automatically combine massive amounts of data from various sources into landscape analysis for forces in the field.
In cyberspace, AI is already used by both attackers and defenders. Given the state of cybersecurity today, however, greater implementation of AI systems could be a real turning point. New generations of malware and cyberattacks can be difficult to detect with conventional cybersecurity protocols, especially if they themselves use AI. Machine learning allows defending systems to adapt over time, giving defenders a dynamic edge over hackers. AI-based systems can also categorize and prioritize attacks based on threat level. With this kind of automation, there’s almost no doubt that we will soon witness cyber wars machine-to-machine.
And while robots might yield better results in military tasks than humans, full-scale implementation is still far from feasible, especially given the current limits of such basic physical abilities as walking and running. It is more likely that we will witness the emergence of “swarms” of micro-drones capable of performing a wide array of tasks, such as intelligence gathering, gaining aerial dominance, or firing highly-accurate micro-missiles.
Finally, AI will play a significant role in winning the hearts and minds of civilians. Advertisers already use AI to tailor messages to the consumer, based on observed-past and predicted-future behavior. Furthermore, AI can create an alternative truth, with no basis in real facts. Current software can create scenes that have never occurred by manipulating existing visuals and sounds. These capabilities are already used to influence political behavior, and there’s every reason to believe that the battle over narratives — or the truth — is only in its infancy.
These rapid technological developments pose a great challenge to national security, but they also hold incredible promise. We can only hope that our policy-makers will deploy AI to its greatest advantage.
Shay Hershkovitz, Ph.D., is a political science professor specializing in intelligence studies. He is also a former IDF intelligence officer whose book, “Aman Comes To Light,” deals with the history of the Israeli intelligence community.