Cybersecurity has become increasingly important as people and businesses are more and more likely to use the internet to conduct their work, creating opportunities for hackers while at the same time increasing the demand for protective tools.
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Behavioral Analytics for Insider Threat Detection
Behavioural analytics (BA), for instance, is particularly effective at identifying hostile insider activity and highly sophisticated attacks that easily bypass many traditional preventive security guardrails. This can be achieved using advanced analytics and unsupervised machine learning to analyse network baseline metrics to detect anomalies that exhibit access from geographies or at times of day that lie outside acceptable behaviours, correlating dynamically to authentication databases or to threat intelligence lists, such as the MITRE ATT&CK framework.
This information provided will allow behavioural analytics to determine what normal behaviour should look like, and then alert teams when a deviation from normal behaviour is detected, enabling rapid response if a breach is imminent or something is already occurring so that teams can take investigative action fast enough to potentially negate a cyberattack. Behavioural analytics is also commonly used by SIEM solutions to perform security monitoring and alerting in the moment, or can be used independently as an additional BA solution – with UBA (User Behavioural Analytics) and UEBA (User and Entity Behavioural Analytics) being some of the more recognisable examples.
Decentralized Security Operations
Even before March 2020, many organisations were continuing to move to remote or hybrid work arrangements. But, with the Covid-19 pandemic, many businesses found these moves were accelerated – IT workers took on new responsibilities in supporting remote work; centralised cybersecurity efforts became increasingly strained.
A decentralised cybersecurity method allows teams to set their own data policy settings while at the same time taking advantage of centrally provided security functions such as standardised protocols, efficient threat detection and prioritised data. These are attributes that almost no organisation in the world today can procure directly.
One worst-case scenario would be to implement centralised security solutions, like buying something in a shop: it’s never a perfect fit, but almost OK is still better than having nothing. The advantages of decentralised cybersecurity are that everyone gets exactly what they need to be as protected as possible, letting them act faster, and maximising their coverage – slowing down miscreants and reducing the risk of damaging data breaches that can ruin brands.
Traditional Signature-Based Antivirus Solutions Are Dying
As more malware samples are detected every day, the antivirus signature files just can’t keep up with the threat data – and yet these signature-driven security products are still a key component in enterprise endpoint protection strategies.
When new viruses or malware are detected, vendors will generate a ‘signature’ to counteract these menaces, and then upload it to a database. This database then generates an update – the updates often distributed throughout the day to keep users safe as new threats emerge – which is disseminated through antivirus programmes.
Sophisticated cybercriminals have also evaded signature-based antivirus detection efforts. This is because signatures can only detect very specific characteristics – somewhere between file hashes and internal strings – of files, and the malware creators typically update their malware without changing the external appearance, so as not to get flagged by signatures.
The Internet of Things (IoT) Creates More Opportunities for Cybercrime
IoT offers a stealthy and extensive attack surface that enables cybercriminals to run myriad criminal activities: intrusions into networks, data leaks, proliferation of botnets or distributed denial-of-service (DDoS) attacks. It gives unauthorised access to sensitive systems to store stolen data, servers or launch a DDoS attack against them.
It is further compounded by the fact that IoT devices are typically designed to maximise functionality rather than robust security, and could have dozens of underlying vulnerabilities used by cybercriminals to gain access to the organisation’s network. Common IoT device vulnerabilities such as weak passwords, insecure communication protocols, software vulnerabilities that haven’t been patched by the manufacturer and others could be exploited by cybercriminals.
To mitigate these risks, digital trust is needed to make a seamless IoT experience possible. The best way to achieve this is through functional convergence between IoT and cybersecurity solutions that are also built into the design from the beginning. Additional forms of more complex technology may be needed to close the significant threat surface that IoT devices bring.