- Security TWENTY
- Women in Security
The covid-19 pandemic has forced companies and its employees to adapt to new social distancing and lockdown measures over the past year. As a result, many businesses have embraced remote working to ensure organisational continuity, writes Alan Hayward of SEH Technology.
This accelerated digital transformation means that companies have had to reconsider how to protect their data and develop new models to remain cyber secure. In fact, a recent report from Accenture stated that 68% of business leaders believed their cyber security risks are increasing. This suggests the importance of businesses making cyber security awareness, prevention and security best practices a part of their company culture.
Cyber criminals are on the hunt for network vulnerabilities and opportunities to capitalise on recent workplace disruptions. New coronavirus-themed phishing scams are on the rise, leveraging fear and increasing the risk of exploiting valuable data, which not only puts employees’ own privacy at risk, but could result in company security breaches too. We have also seen a huge growth in breached data from devices that employees are using from home, such as mobile and IoT devices. These will often lack the same level of security tools built into corporate devices, such as antivirus software, customised firewalls or automatic online backup tools.
As we settle into our new normal, it’s important for organisations to consider and embrace emerging technologies that will positively impact the future of their cyber security practices. These technologies include: Artificial Intelligence (AI), Big Data and Automated Networks.
It’s evident that the opportunities for cyber attacks are increasing at a rapid pace. Depending on the size of the business, there are a significant amount of signals that need to be identified and analysed to accurately calculate the security risk. But analysing and improving cyber security doesn’t have to be left up to employees anymore. AI tools for cyber security have recently emerged to help IT teams to reduce the risk of breaches and improve their procedures more effectively and efficiently.
These tools are able to quickly analyse millions of events and identify security threats at a much faster rate than a human. What’s more, these technologies evolve over time, learning from past experiences to identify new attacks, implementing a behaviour history. This builds a profile on individual users, assets and company networks, allowing AI to detect and respond to instances of abnormality. Recently we have seen a number of organisations deploy this technology across a wide range of categories including, IT asset inventory, threat identification, breach predictions and incident response.
In recent years, many security experts have claimed that Big Data is a threat to businesses, but in fact it is a useful tool to bolster best practices, with 84% of organisations using it to block attacks. Big Data stores large amounts of data and can help analysts to examine, observe and detect irregularities within a company’s network. The information available through Big Data can drastically change the amount of time required to detect and resolve a cyber security issue and allow IT teams to predict and avoid the risk of breaches from cyber criminals. These threats include malware or ransom attacks, compromised devices and malicious insider programs.
Businesses can also consider combining Big Data analytics with AI to perform an extensive analysis of previous and existing data, identifying what they deem as normal. Based on these results, they can use AI to strengthen their security measures and create alerts to notify the IT teams when threats have been detected. It’s important to remember that whilst cyber criminals can target Big Data when establishing their attacks, businesses can use the same data to build a counter defence.
Modern cyber attacks have become increasingly automated, and if businesses are to build a strong defense they need to enable automation to reduce the volume of threats and respond faster. Automation brings a number of benefits such as predicting behaviours and executing protections in a timely manner, but it can also help limit the number of attacks in the future. By correlating threat data across the network, IT teams can build their own security infrastructure that helps to predict the attacker’s next steps. AI can also be implemented to help analyse the data collected to create accurate results and allow automation to data sequence more efficiently.
Once a threat has been identified, companies can generate protections faster than attacks can progress through the network. This involves ensuring that security measures are enforced not only where the threat was first identified, but across all of the technologies within the business to provide consistent protection against cyber attacks. Utilising automation is the best way to move fast, coordinate protection and stop it quickly.
For most people, remote working is a new reality which exposes fresh cybersecurity risks that need to be managed. It’s vital for businesses to assess the threats and the resulting cyber security policy should determine the processes that need to be put in place to minimise the risk of attacks or data breaches. Ultimately, by combining Big Data analysis, AI sequencing and automated networks, organisations can be confident that they will be able to identify and better predict attacks, as well as move fast enough to limit the damage in the long term.