3 Security Risks to Watch for in 2016

3 Security Risks to Watch for in 2016

Security in our insecure world is a growing issue. To help IT professionals plan, here are three predictions for new IT security risks in 2016.

1. The Internet of Things (IoT) will make enterprises more vulnerable by expanding the attack surface.

How vulnerable are IoT devices? Very, according to one report published earlier this year. When HP Enterprise reviewed 10 popular IoT devices, it found that all but one collects at least one piece of personal information; six provide user interfaces (UIs) vulnerable to weak credentials and other issues; seven use unencrypted network services; eight fail to require passwords of sufficient complexity; and seven let attackers identify user accounts through account enumeration.

And IoT devices are expected to proliferate quickly. Gartner released a report showing the growth of IoT devices to reach 25 billion in the next five years.  Market watcher IDC recently forecast worldwide IoT spending will grow by an average of 17 percent a year through 2019, reaching $1.3 trillion. By industry, manufacturing and transportation could be at the greatest risk. Both have been connecting supply chains, products, customers and even workers.

2. The nature of state cyber attacks will evolve from reconnaissance (cyber-spying) to network-infrastructure infiltration and physical attacks.

Governments are no longer satisfied merely with strong cyber defenses such as detection, protection and mitigation; now they also want the ability to conduct cyber attacks and effectively wage war. These attacks include freezing or stealing money, causing problems in infrastructure like power plants, and interfering with the daily operations of hospitals and other public institutions.

Cyber-attacks on industrial equipment was deemed difficult because of the safety monitoring systems used in proprietary ICS/SCADA networks. But it’s now been demonstrated that even these provide little-to-no protection if the a PLC device is hacked. Compromising this type of equipment can involve a combination of cyber and physical attacks that require skills that transcend traditional hacking and could lead to a an escalation of the damage caused.

The threat is real. Consider a few examples. In 2009 spies from Russia, China and other countries penetrated the U.S. electrical grid and left behind potentially damaging software. The United States and Israel are believed to have created Stuxnet, a malicious worm designed to sabotage Iran’s nuclear program. Operation Aurora, an advanced persistent threat, was reportedly launched by the Chinese government. And then there’s the current online war between Russia and Ukraine.

Stealth is a prime characteristic of these attacks. In other words, they’re highly sophisticated — and therefore extremely difficult to detect.

3. The growth of containerized services in the cloud will fuel more attacks on cloud infrastructures and providers.

A growing number of IT shops run applications in software “containers,” rather than on virtual machines (VM). Containers give applications an independent runtime environment, yet avoid the overhead of full-fledged VMs. The approach adds flexibility and efficiency. But it also creates new security risks.

For one, there’s the issue of sprawl. Here, containers let organizations run multiple instances of an application; the risk is that these instances are running with varying and perhaps unsafe security patches. For another, there’s the sheer newness of the approach, which means many security experts simply don’t know how to keep containers safe.

There you have three security predictions for 2016. It should be a good year for extra protection.

Read What CIOs Need to Know about the IoT and Security Risks to learn more about this issue.

About Mike Stute

Chief Scientist, Masergy
Mike Stute is Chief Scientist at Masergy Communications and is the chief architect of the Unified Enterprise Security network behavioral analysis system. As a data scientist, he is responsible for the research and development of deep analysis methods using machine learning, probability engines, and complex system analysis in big data environments. Mike has over 22 years experience in information systems security and has developed analysis systems in fields such as power generation, educational institutions, biotechnology, and electronic communication networks.