How to Analyze Your Cybersecurity Threat Level

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It's impossible to be 100% secure. However, by analyzing the potential threats to your organization, you can understand where your organization stands in terms of cybersecurity. It's about figuring out how vulnerable you are to attack.

This article discusses three broad steps that every organization must take to assess their threat level adequately and improve their cybersecurity readiness.

No matter how careful you are, no matter how good the security measures built into your programs and devices are, there are still vulnerabilities out there in the world waiting to be exploited. The best way to protect your organization is to be always on guard, anticipating unique threats and proactively mitigating them.

Analyzing Cyber Threat Metrics

According to PwC’s 2021 Global Digital Trust Insights survey, 53% of tech and security executives admitted their uncertainty that their cybersecurity budgets were adequate to deal with the most significant risks.

Yet, the solution to this is not simply to spend more. The reality is that organizations are beefing up their spending on cybersecurity even while their systems get less secure.

To make wiser choices in cybersecurity, start by quantifying the risks your organization faces. According to the same survey, about 60% of cyber managers already implement strategies to optimize cybersecurity spending.

There are various models for cyber risk quantification but what matters most is that you apply the proper standards and use the right metrics. Some valuable metrics are given below:

• Intrusion attempts: your overall goal should be to minimize both the frequency and the volume of attacks you experience.

• System vulnerabilities: use this information to determine which vulnerabilities pose the most significant risk to your company and what needs to be done to fix them.

• Data transfer volume: this will let you identify unauthorized and potentially dangerous uses of your network.

• Mean Time-to-Detect: set up a list of specific indicators of compromise and be sure each is checked daily.

• Mean Time-to-Contain: this helps organizations understand how many resources they should dedicate to patching vulnerabilities in their IT systems.

There are several other metrics that you can apply depending on your organization’s security objectives.

However, your measurements must be tangible and granular. Tangible cybersecurity metrics are useful in measuring the success of security initiatives since they often involve numerical data that can be compared over time to determine trends.

Defining Security Priorities

Many businesses invest in technologies before having an accurate picture of their unique cybersecurity situation. But what is a VPN, firewall, or a fancy innovative technology useful for unless you have already established the right objectives?

Some of the cybersecurity considerations for 2022 include cloud adoption, zero-trust authentication, automation, and resilience, according to KPMG. If any leader must have learned anything over the past few years, cybersecurity is not an ‘IT thing’; it is a valid and severe business concern.

And then the COVID-19 pandemic came on board, injecting a whole new level of confusion into an already chaotic cybersecurity landscape.

According to Gartner, “By 2025, 70% of CEOs will mandate a culture of organizational resilience to survive coincident threats from cybercrime, severe weather events, civil unrest, and political instabilities.”

Analyzing your cybersecurity threat level must be an ongoing exercise in noting the change in priorities and defining the core cybersecurity objectives for your organization. And they must align with your business operations.

Find below some helpful tips to achieve this:

• When we talk about cybersecurity objectives, we should start by considering what's at stake. What are the critical business processes your organization relies on? These are your cybersecurity objectives.

• Examine...

9 Legal, Financial and Marketing Mistakes That Can Kill Your Small Business

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The failure rate of small businesses is staggering. 20%, 30%, 50%, and 70% of small businesses would have failed by their 1st, 2nd, 5th, and 10th year respectively.

If you own a small business, there's no doubt that you have a lot on your plate. There are government regulations to contend with, accounting work to be done and marketing campaigns that need to be planned and executed.

You also need to keep an eye on employee morale and handle the day-to-day operations of the business. It's a lot to juggle.

Yet, you can’t afford to make mistakes. Some mistakes can be costly and have a lasting impact on the survival of your business. Knowing the most common mistakes to avoid will help you get off on the right foot and set you up for future success.

Legal Mistakes

Using a Wrong Business Structure

One of the most critical decisions a founder(s) must take when starting their business, however small, is how to register the company. Most small businesses would do well as sole proprietorships or general partnership entities.

However, if the founder(s) are unwilling to bear personal responsibility for business liability, an LLC or a corporation (s-corp or c-corp) is the way to go. This is only one of the many considerations to make when registering your business with the government.

The type of entity you establish determines how you will file taxes, account profits, assume liabilities, access credits, and so on.

This information should be detailed in your business plan to give you a clear idea of where the business is heading and what to expect as the owner.

Not Using a Registered Agent

Business formation is a somewhat straightforward process, but going through the steps can be cumbersome.

You need an agent to guide you through entering into agreements, drafting legal documents, and ensuring compliance with business regulations.

Having a registered agent like Rocket Lawyer for your business is not even optional when you want to form your company in certain states.

Your agent helps you go through the actual business registration process, submit and retrieve forms, correspondence, and other such important documents and generally serve as a liaison between the government and your business.

Although you can be your own registered agent, for a small fee, you can pay a registered agent and have them worry about compliance issues on your behalf. That frees you up to focus on actual business operations.

Lack of Proper Written Agreements

We live in the age of technology when agreements can be easily reached via a couple of video calls and emails. But a smart business person knows not to enter into commitments without formal written agreements.

Informal agreements are unreliable, and even though the law sometimes enforces such ‘handshake deals’, you can never be too sure that the judgement would be in your favour.

Therefore, it is in your best interest to play it safe by forming formal written agreements to protect your business from risky exposure.

This is the point where you need a lawyer; they draft and review agreements to ensure that your business is not unreasonably exposed to harm.

Financial Mistakes

Conflating Personal and Business Accounts

This is a common small business owner mistake, especially for sole proprietorships and general partnerships, since there is no legal separation between the owner and their business.

Yet, even without this legal obligation, it is always advisable to keep personal accounts separate from business accounts to avoid business cash flow issues or compromising your personal finances and assets.

From the get-go, open a separate account for your business and keep financial transactions separate from your personal spending/income. And whenever you make a personal investment into the business, record it.

Choosing the Wrong Investor

One of the significant challenges small business owners have to deal with is the lack of capital to fund their business vision. At that...

New Applications of Machine Learning in Zero Trust Authentication

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Cyber attackers have begun implementing AI and using machine learning techniques to launch more severe attacks than ever experienced.

The weakness of traditional solutions is that they rely on signature-based detection, which, obviously, cannot stand the test of time against modern attack models.

For instance, since signature-based detection only works for known threats, such legacy technologies are powerless in the face of rising zero-day attacks.

On the other hand, behavioral analysis via machine learning is training the cybersecurity system to recognize attack patterns. Once a series of actions exceeds the set baseline, the system triggers an alert.

According to a cybersecurity executive, “An average phishing attacker will bypass an AI-based detection system 0.3 percent of the time, but by using AI this 'attacker' was able to bypass the system more than 15 percent of the time.”

Therefore, it is very necessary for organizations to implement more sophisticated, machine learning-enabled cybersecurity tools and technologies to protect their network from incursion.

Machine Learning, Zero-Trust, and Software-Defined Perimeters

It is important to note that machine learning is a complementary technology to other cybersecurity technologies. In a similar vein, zero-trust security must be approached not as a product, but as a platform, more precisely, a strategy.

That’s why there are new technologies challenging legacy solutions and our traditional outlook of network security. A software-defined perimeter, for instance, exists as an alternative solution to VPN and to some extent, firewalls.

SDPs work by creating a virtual perimeter around network assets. However, what’s unique is that SDPs authenticate users themselves, rather than devices. 

By design, SDPs are zero-trust and operate on a need-to-know model, but combining them with machine learning for authentication provides an even greater level of network security. After all, access control is one of the main features of an SDP.

Machine Learning in Adaptive Authentication

One of the emerging applications of AI in cybersecurity is behavioral biometrics. This has proven useful in security authentication. 

With machine learning, authentication systems can be trained to detect suspicious activity based on the real-time intelligence of the authentication context. Such is what Risk-Based Authentication (RBA) aims to achieve. RBA works based on principles of zero trust and least privilege. 

The system assesses every login attempt for the likelihood of hacking based on the login behavior. RBA’s adaptive intelligence uses information about the device, device IP address, user location, etc. to calculate a risk score.

Depending on this risk score, access may be granted or restricted, or the system may request additional user credentials. RBA eliminates the trouble with passwords since a hacker knowing the right password is not a guarantee that access will be granted.

Machine Learning in Continuous Authentication

Based on the same behavioral biometrics adaptive intelligence, there’s continuous authentication, by which a user session is assessed in real-time for signs of a breach.

This solves a real challenge in cybersecurity authentication, where a hacker hijacks a legitimate user session. Like RBA, the continuous authentication mechanism bases its decision upon a risk engine.

Continuous authentication provides a means to determine when a login session, for instance, an online banking session has been attacked midway. To do this, it runs in the background, analyzing user behavior for suspicious quirks. 

The user is not interrupted in their operation or transaction until a suspicious activity is detected and the system has to implement a protection protocol, such as requesting them to re-enter their password mid-session. An example is Gartner’s Continuous Adaptive Risk and Trust Assessment (CARTA).

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