Ranked: The Top Cyberattacks Against Businesses
The following content is sponsored by Global X ETFs.
Ranked: The Top Cyberattacks Against Businesses
Cyberattacks hit a record high in 2021, continuing the momentum that had developed during the COVID-19 pandemic. One reason for this increase is the shift to remote work, which has opened up new vulnerabilities. Home networks are typically less secure, and the rapid rise in the use of online services means security is falling behind.
In this graphic sponsored by Global X ETFs, we’ve visualized survey results showing the 10 most successful types of cyberattacks in 2021.
These results are from a 2021 whitepaper by Osterman Research, a market research firm focused on cybersecurity. They surveyed 130 cybersecurity professionals from mid and large-sized organizations to see which types of attacks were the most prominent.
|Type of Attack||Percentage of respondents (%)|
|Business email attack was successful in tricking a lower-level employee||53%|
|Phishing message resulted in a malware infection||49%|
|Phishing message resulted in an account being compromised||47%|
|Domain name was spoofed to perpetrate phishing campaigns||38%|
|Ransomware was detected before it could be activated||34%|
|Business email attack was successful in tricking a senior executive||28%|
|Domain name impersonation resulted in a third-party being compromised||16%|
|Phishing message resulted in a ransomware infection||14%|
|A ransomware attack was successfully launched||10%|
|A ransomware attack rendered internal IT systems non-operational||10%|
Source: Osterman Research (2021)
The report notes that these figures may be understated because organizations are likely to downplay their security incidents. Organizations may also lack the capability to detect all types of cyberattacks.
The Impact of Phishing Attacks
Phishing refers to an attack where the perpetrator pretends to be a trusted entity. These attacks can be carried out over email, text message (SMS), and even social media apps. The goal is often to trick the victim into opening a malicious link.
According to the whitepaper, opening malicious links can result in credential theft or ransomware infections. Credential theft is when attackers gain access to internal systems. This is incredibly dangerous, as it allows attackers to commit fraud, impersonate company officials, and steal data.
A powerful tool for preventing credential theft is multi-factor authentication (MFA). This method requires users to provide multiple verification factors to access a resource (instead of a single password).
The Threat of Ransomware
Ransomware is a type of cyberattack that involves blackmail, often for financial gain. For ransomware to be successfully planted, attackers must first gain access to a company’s networks.
Access can be gained through phishing, as discussed above, or alternate means such as compromised software updates. One such attack impacted over 57,000 Asus laptop owners in Russia after hackers created a malicious update tool on an official Asus server.
Cybercriminals have become increasingly ruthless in how ransomware attacks are executed.
– Osterman Research
Researchers have warned that ransomware attacks are becoming more dangerous and sophisticated. In addition to locking organizations out from core systems, hackers are also stealing data to increase their leverage. If a ransom is not paid, the stolen data may be published or even sold to the highest bidder.
The rising frequency and sophistication of cybercriminal activity is a major threat to the world.
According to the World Economic Forum’s 2022 Global Risks Report, ransomware attacks have increased by 435% since 2020. Furthermore, there is an estimated shortage of 3 million cybersecurity professionals worldwide.
To catch up, businesses and governments are expected to increase their spending on cybersecurity over the next several years.
The Global X Cybersecurity ETF is a passively managed solution that can be used to gain exposure to the rising adoption of cybersecurity technologies. Click the link to learn more.
Network Overload? Adding Up the Data Produced By Connected Cars
By 2025, connected cars could produce 10 exabytes (exabyte = 1B gigabytes) of data per month, a thousand-fold increase over current volumes.
- Connected cars could be producing up to 10 exabytes of data per month, a thousand-fold increase over current data volumes.
- This has serious implications for policymakers, manufacturers, and local network infrastructure.
Modern connected cars are almost like computers on wheels.
Today’s connected cars come stocked with as many as 200 onboard sensors, tracking everything from engine temperature to seatbelt status. And all those sensors create reams of data, which will increase exponentially as the autonomous driving revolution gathers pace.
With carmakers planning on uploading 50-70% of that data, this has serious implications for policymakers, manufacturers, and local network infrastructure.
In this visualization from our sponsor Global X ETFs, we add up the data produced by connected cars.
Data is a Plural Noun
Just how much data could it possibly be?
There are lots of estimates out there, from as much as 450 TB per day for robotaxis, to as little as 0.383 TB per hour for a minimally connected car. This visualization adds up the outputs from sensors found in a typical connected car of the future, with at least some self-driving capabilities.
The focus is on the kinds of sensors that an automated vehicle might use, because these are the data hogs. Sensors like the one that turns on your check-oil-light probably doesn’t produce that much data. But a 4K camera at 30 frames a second, on the other hand, produces 5.4 TB per hour.
|Sensor||Sensors per Vehicle||Data Produced|
|Vehicle Motion, GNSS/GPS, IMU||n/a||<0.1 Mbit/s|
|Total Data||3-40 Gbit/s/vehicle|
All together, you could have somewhere between 1.4 TB and 19 TB per hour. Given that U.S. drivers spend 17,600 minutes driving per year, a vehicle could produce between 380 and 5,100 TB every year.
To put that upper range into perspective, the largest commercially available computer storage—the 100 TB SSD Exadrive from Nimbus—would be full in 5 hours. A standard Blu-ray disc (50 GB) would be full in under 2 seconds.
Lag is a Drag
The problem is twofold. In the first place, the internet is better at downloading than uploading. And this makes sense when you think about it. How often are you uploading a video, versus downloading or streaming one?
Average global mobile download speeds were 30.78 MB/s in July 2022, against 8.55 MB/s for uploads. Fixed broadband is much higher of course, but no one is suggesting that you connect really, really long network cables to moving vehicles.
Ultimately, there isn’t enough bandwidth to go around. Consider the types of data traffic that a connected car could produce:
- Vehicle-to-vehicle (V2V)
- Vehicle-to-grid (V2G)
- Vehicles-to-people (V2P)
- Vehicles-to-infrastructure (V2I)
- Vehicles-to-everything (V2E)
The network just won’t be able to handle it.
Moreover, lag needs to be relatively non-existent for roads to be safe. If a traffic camera detects that another car has run a red light and is about to t-bone you, that message needs to get to you right now, not in a few seconds.
Full to the Gunwales
The second problem is storage. Just where is all this data supposed to go? In 2021, total global data storage capacity was 8 zettabytes (ZB) and is set to double to 16 ZB by 2025.
One study predicted that connected cars could be producing up to 10 exabytes per month, a thousand-fold increase over current data volumes.
At that rate, 8 ZB will be full in 2.2 years, which seems like a long time until you consider that we still need a place to put the rest of our data too.
At the Bleeding Edge
Fortunately, not all of that data needs to be uploaded. As already noted, automakers are only interested in uploading some of that. Also, privacy legislation in some jurisdictions may not allow highly personal data, like a car’s exact location, to be shared with manufacturers.
Uploading could also move to off-peak hours to even out demand on network infrastructure. Plug in your EV at the end of the day to charge, and upload data in the evening, when network traffic is down. This would be good for maintenance logs, but less useful for the kind of real-time data discussed above.
For that, Edge Computing could hold the answer. The Automotive Edge Computing Consortium has a plan for a next generation network based on distributed computing on localized networks. Storage and computing resources stay closer to the data source—the connected car—to improve response times and reduce bandwidth loads.
Invest in the Future of Road Transport
By 2030, 95% of new vehicles sold will be connected vehicles, up from 50% today, and companies are racing to meet the challenge, creating investing opportunities.
Learn more about the Global X Autonomous & Electric Vehicles ETF (DRIV). It provides exposure to companies involved in the development of autonomous vehicles, EVs, and EV components and materials.
And be sure to read about how experiential technologies like Edge Computing are driving change in road transport in Charting Disruption. This joint report by Global X ETFs and the Wall Street Journal is also available as a downloadable PDF.
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