Methods of Threat Detection can sometimes be difficult and overwhelming, depending on the organization and the number of assets being protected. In this guide, you’ll learn about four different methods of threat detection, including their pros and cons, as well as why certain organizations choose to employ these strategies over others. Additionally, you’ll receive tips on how to prioritize your threat detection efforts based on your organization’s assets, vulnerabilities, and the resources available to address these threats.
What are 4 methods of threat detection?
- 1) Know Your Enemy
- 2) Data Mining
- 3) Heuristic Software Testing
- 4) Dynamic Analysis
1) Know Your Enemy
There are a number of different ways to protect yourself from cyber threats. It’s essential to learn as much as you can about these threats before investing in any technology that promises protection. Luckily, there’s a lot we do know. Here are four major threat types: Malware: Malware is malicious software that infects computers and devices to collect data or cause damage to programs and files on your computer, steal your personal information or lock you out until you pay a ransom fee.
The most common form of malware is ransomware, which locks users out until they pay an exorbitant fee with bitcoin (or some other form of cryptocurrency). Phishing: A form of social engineering meant to get users to share sensitive information via email or another form. This information could be used for identity theft or financial fraud. Spear phishing is when hackers target specific individuals by using their names in emails to make them more believable.
Spoofing: This occurs when someone disguises themselves as someone else online, usually through email addresses and phone numbers that look legitimate but aren’t—like those associated with government agencies like IRS or FBI. Ransomware attacks often start off by spoofing law enforcement agencies so people think it’s real and pay up immediately rather than doing research into whether it’s actually legitimate. Viruses: Viruses are self-replicating pieces of code that spread from one device to another through removable media like USB drives, CDs/DVDs, memory sticks, and hard drives connected over a network like WiFi.
2) Data Mining
Data mining is a type of analysis that allows people to search through large databases and pull out what’s important. It’s often used by businesses in order to better target their customers, by law enforcement agencies who monitor online activity for criminals, and it’s even used by intelligence agencies to sift through large amounts of data looking for suspicious behavior. With all of our digital data becoming available on a global scale, we’re all leaving a lot more footprints behind than ever before. Data mining helps keep us safe from those who would do us harm! Here are four different ways you can use data mining to detect threats.
- Catching Criminals
- Finding Bad Behavior
- Predicting Future Behavior
- Identifying Influencers
1. Catching Criminals –
Law enforcement officials say they need more tools like these to combat terrorism and cybercrime, especially as information moves away from phones and computers into smart cars, homes, and other connected devices.
2. Finding Bad Behavior –
The U.S Department of Homeland Security says big data has allowed them to see patterns among suspicious individuals or groups that previously weren’t visible
3. Predicting Future Behavior –
Data mining isn’t just about catching bad guys after they’ve done something wrong; it also helps predict future criminal behavior, which can help prevent crimes before they happen.
4. Identifying Influencers –
One of the biggest challenges with social media is figuring out which users have influence over others and how much influence each person wields over specific topics.
3) Heuristic Software Testing
Heuristic Software Testing is a method in which testers follow their own intuition, experience, and knowledge to find software bugs. Although it lacks formal structure and defined processes, Heuristic Software Testing produces more bugs than scripted testing. It is more flexible, faster, and can easily be performed by untrained people; however, it has less precision.
When combined with other forms of software testing, Heuristic Software Testing leads to fewer undetected bugs at lower costs. The major benefits of using heuristic techniques include high-level quality checks that can catch logical errors or help determine if an application meets user expectations and pre-scripted tests that can be used again and again with different values instead of being written specifically for every test case, and quick identification of program logic errors.
4) Dynamic Analysis
Dynamic analysis is a software testing technique for evaluating computer software. Such tests execute software in an environment similar to how it will be used by its end users and look for discrepancies such as crashes, hangs, deadlocks, or security issues. Compared to more traditional testing techniques such as unit testing and integration testing that occur only during development, dynamic analysis is useful even after a system has been released. It can expose latent bugs and vulnerabilities that would otherwise be impossible to find without exposing actual users to harm. This makes dynamic analysis very attractive to organizations that seek secure systems.
In order to run a test with valid results, it is essential that all dependencies required by both parties are present on either physical machines or virtual machines (VMs). If there exists any possibility of malicious activity due to data exchange between two parties, it must be assumed that data manipulation will take place at some point before or during runtime. This may result in incomplete execution paths and unexpected behaviors which must be detected prior to execution. Dynamic testing also includes monitoring systems while they operate under normal use conditions.
