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Cyber Threat Landscape Change Over Past Years


Every day, information technology (IT) and cyber security experts work hard to find new ways to defend against potential cyber-attacks. When a company aspires to have advanced cyber security capabilities, it must have a thorough understanding of how cyber security threats evolve. To fully benefit from newer technology, a company must review the threat environment for the relevant year. This analysis uncovered vulnerabilities in Internet of Things (IoT) applications, brute force attacks, data hacks, social engineering occurrences, and Distributed Denial of Service (DDoS) attacks. Cyber criminals are likely to use new technologies and developments in the future to gain unauthorized access to data.

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The evolution of IoT devices is an interconnected network computing that exchanges data without requiring human interaction. As the number of people using IoT environments has grown, so has the amount of effort put into exploiting them. About 500,000 IoT computers were hacked in 2018 by the VPN Filter malware (Sapalo Sicato et al., 2019). The VPNFilter malware is capable of stealing website credentials, potentially preventing hundreds of thousands of people from accessing the internet. Because of how difficult it is to shift the public’s view of data breaches, many businesses have closed their doors. Fraud, data hacks, and all other data that can be contained inside a company’s network can be prevented by a company that practices proper information protection. Data breaches have been reported on several social media platforms. Facebook has seen several major data breaches involving its users’ details. A data leak exposed the passwords of 50 million people in 2018 (Taylor & Garry, 2018). This was the most serious data leak in Facebook’s history. Hackers exploited the flaw to gain access to the accounts and take complete control of them.

One of the most popular methods used by hackers to obtain unauthorized access to information is social engineering. The user is normally the most vulnerable part of a network or computer. If a user’s cyber awareness is poor, they can be easily duped into divulging sensitive information. The W2 phishing scam was a social engineering assault that occurred in 2018. The W2 phishing scam aimed to gain access to company records to gain access to confidential company and employee data (Shi et al., 2020). Identity hackers would impersonate a top executive to obtain personal feedback from employees.

A denial of service (DoS) attack is used by a hacker to prevent users from accessing a computer or network. A denial-of-service (DoS) attack floods the target system with traffic, crashing it. From a single location, a DoS attack is launched against a target computer. DDoS attacks use several devices to target a single computer. In 2018 Akamai registered a series of DDoS attacks against DNS servers (Trejo et al., 2019). When the attacks were no longer successful, the attackers began flooding the entire subnet. Flooding is a form of denial-of-service attack. DoS is achieved by overwhelming a network system with a huge volume of traffic.

The Change Experienced over Past Years in Cyber Threat Landscape

The change experienced over past years in the cyber threat landscape is where vast segments of society were restricted access to technology. This is a constant source of concern in a changing threat environment. People lacked the skills to defend themselves against the most basic attacks. Multiple family members used the same mobile computer, significantly raising the risk of malware infection. Later, educators who traditionally used technology were now exchanging files as part of their normal online classroom experiences, potentially exposing their computers to malware. Many districts and educational institutions were required to make a swift transition to online learning, which meant skipping some of the training and cyber security procedures that came standard with conventional online learning models (Pavan Kumar, 2021).

Common Tactics, Techniques, and Procedures to Include Threat Actor Type

The action of a threat actor or group is defined by Tactics, Techniques, and Procedures (TTP), a crucial concept in cyber security. In the world of cyber security, tactics are high-level examples of the actions that threat actors are attempting to achieve (Zrahia, 2018). Initial access is a strategy used by threat actors to gain access to your network. Techniques are comprehensive explanations of the acts or behaviors that precede the strategy. Phishing is one tactic that could be used to obtain initial entry. Procedures are technical information or instructions that describe how a threat actor can use a strategy to achieve their goal. Procedures for a phishing assault, for example, would involve the order of operations or campaign phases. This may include information about the infrastructure used to send malicious emails, which they are targeting, and whether they are sending malware spam with a connection or attachment.

Vulnerabilities and Exploit Vectors Expected to be Exploited by Threat Actors

An advanced persistent threat is expected to exploit vectors and vulnerabilities by threat actors in the APT. This is a long-term, targeted cyber-attack in which an attacker gains network access and remains undetected for a long time. Rather than causing harm to the target organization’s network, APT attacks are used to steal data (Duong, 2020). Reasonably than trying to get in and out as quickly as possible, most APT attacks aim to gain and retain ongoing access to the targeted network.

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To summarize, many of the problems that many companies are experiencing stem from their dependence on a single system to detect or avoid a particular form of danger. A password will stop DoS attacks, an antivirus will stop malware, and NIPS (Network Intrusion Prevention System) will stop several other cyber-attacks. All layers of defense rely on data, which becomes the key to effectively securing a network and detecting anomalies that would otherwise be lost in a sea of logs.


Duong, L. (2020). Detecting APT attacks based on network flow. International Journal of Emerging Trends in Engineering Research, 8(7), 3134-3139. Web.

Pavan Kumar, S. (2021). Impact of online learning readiness on students satisfaction in higher educational institutions. Journal of Engineering Education Transformations, 34(0), 64. Web.

Sapalo Sicato, J., Sharma, P., Loia, V., & Park, J. (2019). VPN filter malware analysis on cyber threat in smart home network. Applied Sciences, 9(13), 2763. Web.

Shi, J., Li, J., Chen, Y., & Lu, Z. (2020). PRAN: Progressive Residual Attention Network for Super Resolution. IEEE Access, 8, 188611-188619. Web.

Taylor, R., & Garry, M. (2018). People infuse their passwords with autobiographical information. Memory, 27(5), 581-591. Web.

Trejo, L., Ferman, V., Medina-Perez, M., Arredondo Giacinti, F., Monroy, R., & Ramirez-Marquez, J. (2019). DNS-ADVP: A machine learning anomaly detection and visual platform to protect top-level domain name servers against DDoS attacks. IEEE Access, 7, 116358-116369. Web.

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Zrahia, A. (2018). Threat intelligence sharing between cyber security vendors: Network, dyadic, and agent views. Journal of Cyber security, 4(1). Web.

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