Machine learning is not a new-fangled security technology, but it is poised to be a crucial element in battling known and unknown ransomware threats and exploit kit attacks, among others. Machine learning is deployed through a layered system with human- and computer-provided inputs running through mathematical algorithms.
This model is then pitted against network traffic, allowing a machine to make quick and accurate decisions about whether the network content—files and behaviours—are malicious or not.
Enterprises must also ready themselves with proven protection against the anti-evasion techniques that threat actors will introduce in 2017. This challenge calls for a combination (versus a silver-bullet type approach) of different security technologies that should be available across the network to form a connected threat defence.
• Advanced anti-malware (beyond blacklisting)
• Antispam and antiphishing at the Web and messaging gateways
• Web reputation
• Breach detection systems
• Application control (whitelisting)
• Content filtering
• Vulnerability shielding
• Mobile app reputation
• Host- and network-based intrusion prevention
• Host-based firewall protection
A majority of today’s threats can be detected by the aforementioned techniques working together, but in order to catch zero-day and “unknown” threats, enterprises must use behaviour and integrity monitoring as well as sandboxing.
IoT affords both risks and conveniences. Smart device users should learn to secure their routers before allowing any smart device to access the Internet through them. They should then include security as a consideration when buying a new smart device.
Does it provide for authentication or allow password changes? Can it be updated? Can it encrypt network communications? Does it have open ports? Does its vendor provide firmware updates?
Enterprises that collect data from EU citizens should expect a bump in administrative expenses as they grapple with major process changes and hire DPOs to comply with the GDPR. A thorough review of a company’s data protection strategy will also help in passing audits.
These new challenges require a new take on endpoint security, a cross-generational security approach combining proven threat-detection techniques for known and unknown threats with advanced protection techniques such as application control, exploit prevention and behavioural analysis, sandbox detection, and high-fidelity machine learning.
Training employees against social engineering attacks and about the latest threats like BEC will complete the security culture needed to fortify an enterprise’s defences for 2017 and beyond.
If you interested in knowing more about making your network as secure as possible then please get in touch with us. We have a number of great products that can help to either protect your network or quickly recover your data in the event of an attackCase Study: Long Term IT Services Transform Technology School »