Cybersecurity in 2019

Cyber Security in 2019

What threats or new trends can you expect to see in 2019. We had a chat with the team here at CyberCrowd and come up with the following buzzwords. As a result, we thought it might be useful to share our view and explain what they mean.

  1. Blockchain Technology

There are three main features of blockchain that help prevent major cybersecurity attacks. They include;

  1. being a trustless system
  2. Being immutable
  • Having network consensus

A blockchain system runs without the theory of human trust. All this means is that any code or functions are guaranteed to execute and written as long as the network is online. Blockchain networks are built in such a way that any individual node could attack it whenever it wishes. Consensus protocols like proof-of-work ensure that even if it happens, the network will still finish its functions as it was supposed to be, despite human dishonesty.

The blockchain sustains storage and safety of data by using various cryptographic properties such as digital signatures and hashing. When data enters a block, in a blockchain, hackers cannot tamper with it. This process is known as immutability and just like before, if anyone tried to mess around with a blockchain database, network consensus would find out and shut down the attempted attack.

What is consensus? Blockchains are made up of nodes that can be within one organisation, or all over the world on the computer of any person that wants to take part in. For any decision to be made, the majority of nodes need to come into agreement instead of a central authoritative figure. If any node is compromised by a hacker, the other nodes will automatically recognise the issue and not execute the request.

This is a great way to counter threats but there are problems of scalability and ensuring that this technology is tested and fit for purpose in large scale deployments.

  1. IOT (Internet of Things)

Combining big data and cloud, the IOT will enable an exponential increase in autonomy. There will be more than 26 billion devices by 2020. The applications for IOT include environmental monitoring, infrastructure management, industrial applications, energy management, medical and healthcare and transport systems.

With the growth in end point devices, security becomes very important. Techniques available to us are:

  1. End-point security – this demands that each IOT device complies with certain standards before network access is granted.
  2. VLAN – devices that don’t comply with end-point security should be quarantined to a VLAN (Virtual Local Area Network). Here there are strict measures such as only communicating via VPN, using hard passwords, double authentication.
  • Resilient Networking Principles – Coming up with a resilient network will depend on the type of resources one has at their disposal.
  1. Two principles – always take simplicity and modularity into consideration. For simplicity, one should not use recurring components as leads to more outages. As for modularity, you can put the network in different segments, having manageable, smaller components and isolate problems within a module.
  2. Data-driven Protocols – operating the economies of scale, having an efficient breadth of scope, and applying real-time interaction.
  1. AI (Artificial Intelligence) cyber security

AI has now taken centre stage in the cyber security industry. It consists of adaptive/machine learning algorithms with the ability to identify and respond to threats as they occur, which in a large organisation can be far too many for humans to respond to at the same speed and accuracy (notwithstanding the fact that humans want to have lunch, go home, have holidays etc)

AI helps in classification where any data received will be predicted whether or not the data is potentially malicious or safe for an environment. Other techniques involve detecting anomalies by processing data quickly in real time. It also uses algorithms that can track what standards of behaviour seem to qualify as normal and look for intrusions/hacking.

AI also uses probabilistic programming which is a set of computational language that doesn’t write computer programs deterministically using if-then rules, but can instigate a distribution of probabilities.

In the security space, there has been a shift from prevention-oriented tools where we are blocking out networks so as to keep malicious actors out, to a different type of mentality where we assume some malicious actors are going to get in and shift from prevention to probabilistic risk management. This requires a set of processes and skills that the existing security community is not equipped with.