For obvious reasons, business leaders see Bring Your Own Device (BYOD) programs as an excellent way to make employees happy while helping them be more productive with their time. The concept of allowing workers to bring their personal wireless devices into work has certainly grown in popularity in recent years. Research shows that the number of employee-owned devices used in the workplace will grow to more than one billion by the year 2018. That’s a lot of devices to keep track of, which could cause a nightmare for IT departments. Perhaps the biggest concern with the rapid growth of BYOD deals with the security issues that accompany it. Meeting and overcoming those security challenges is a priority for businesses, but answers have been hard to come by. As companies look to make their employee-owned devices more secure, the advances from machine learning may prove to be a deciding factor.
Security remains a serious problem for all companies, particularly those with BYOD policies, in part because threats are being created and set loose almost on a daily basis. In the third quarter of 2013 alone, 259 new security threats were discovered targeting smartphones. Additional research shows up to 80% of personal and business smartphones are unprotected. With that lack of security, company data is in serious jeopardy of being lost or stolen, which could have disastrous consequences for the organization. There are, of course, many different antivirus programs and security features for computers and mobile devices out there, but their effectiveness leaves a lot to be desired. Attackers are always coming up with new ways to infiltrate computers and devices. Current antivirus measures look for certain file signatures with a history of spreading malicious code, but attackers have found ways around that by infecting unsecured WiFi networks, using fake emails, and taking advantage of seemingly harmless downloads.
That’s why machine learning can play such an important role in protecting BYOD devices. One startup company named Zimperium is using the technology as a way to provide early detection of potentially damaging viruses, malware, and worms. How Zimperium’s machine learning technology (called zIPS for Zimperium Intrusion Prevention System) works is by allowing the program to learn how your smartphone or tablet normally functions during your daily use. By learning this, the program can then detect when your device starts to behave in an irregular manner. The program then sends you an alert along with a description of what it has determined the problem is. By adopting this machine learning approach, Zimperium provides a method by which future attacks can be stopped without knowing exactly what form those attacks will come in. This in turn gives machine learning a definite advantage over other malware protection methods that require knowing more about attacks before stopping them.
The need for machine learning for security protection is especially great since BYOD policies usually require the use of cloud computing. Securing the cloud is a major concern for businesses, especially if vital or sensitive data is involved. Cloud computing provides for more flexible work patterns, but it also opens up more avenues for potential attacks. Machine learning works to prevent those attacks by creating its own algorithms for assessing the risks for how apps are utilized for BYOD and identifying when usage falls outside of the established parameters. Part of the success that comes from machine learning and security is related to its past success with regular computer security. Microsoft is using machine learning to make its computers more secure by detecting malware and eliminating it. As more companies take the concept and morph it into a workable form for wireless devices, mobile technology will become just as secure as the regular desktop computers.
There likely won’t be a way to completely eliminate all security threats for BYOD, but machine learning is a very promising technology that can minimize security concerns. Business leaders want to use BYOD, but the main thing stopping them is the security risk. Alleviate that worry, and you’ll likely find BYOD popping up much more often than before.
- .NET Development
- Banking & Finance
- Communities & Social networks
- Custom App Development
- Development process
- Digital Marketing
- Drupal Development
- E-commerce & Retail
Best Frontend Programming Languages to Create Beautiful and Fast InterfacesRead more
Capability Maturity Model Integration – QArea's big journeyRead more
QArea is a Unique Services Provider in 2019 CEE AwardsRead more
Ultimate Development Trends in 2018 to Reward Your Business in 2019Read more
Why You Should Write Your Next Microservice Using GolangRead more