Insights into Organizational Security Readiness: Lessons Learned from Cyber-Attack Case Studies
Abstract
:1. Introduction
- the evaluation of multiple real-world cyber-attacks to understand the types of attack;
- the categorization of the human factors leading up to the cyber threats;
- The characterization of cyber-attacks;
- the mitigation strategies; and
- the lessons learned for providing actionable knowledge to create more awareness for all stakeholders.
2. Motivation
3. Case Study Methodology
3.1. Understanding the Types of Attacks
3.2. Cyber-Attack Case Studies by the Industry
3.3. Categorization of the Human Aspects
3.4. Financial Impacts
3.5. Non-Financial Impacts
3.6. Number of Customers (Victims) Impacted
3.7. Cultural Factors
3.8. End-User Trust and Loyalty
3.9. Policy Issues
3.10. Training and Awareness
3.11. Technology Adoption (for Cyber-Threat Prevention)
3.12. Investment
3.13. Factors Leading to Cyber-Attacks
4. Results and Findings
- Denial of Service (DOS) attacks [50] usually occur when an environment has a weak configuration and cybersecurity policy despite training and the related cyber awareness, as shown in Figure 4 below. Strong cybersecurity policies and strong configuration in the IT infrastructure [51] are a necessity for a secure environment because training and cyber awareness are not good enough without implementing them properly. The credibility and the reputation of the organization are impacted heavily by this kind of incident. The DOS attack [52] is related to the circular impactful attributes that imply the loss of credibility.
- APT: In Figure 5, we notice that APT attacks are linked to the lack of technology adoption, with not much training, as well as minimal security policy. They may cause medium to high financial loss. Cyber awareness is not enough if we do not have the proper training and technology adoption for cybersecurity.
- Social Engineering: We see a lack of awareness and training with a lack of technology adoption. As a result, there is no corporate culture for security and no corporate investment for cybersecurity. The outcome from this may lead to significant financial loss. Ignorance is the main human factor for this kind of attack, as shown in Figure 6.
- Malware: If there is no strong cybersecurity policy, not much investment in security, and limited training and awareness on Cybersecurity, organizations may become victims of a Malware attack. The financial consequence from this attack could be very high, as depicted in Figure 7.
5. Overall Observation
- Out of the four main human factors, ignorance and negligence are the two human behaviors that appear to be linked to most of the cyber threats.
- Financial Institutes, Retail and Entertainment industries are the main targets for hackers, in addition to Technology, Health and Energy. This is especially true when financial gains are the key factor behind an attack.
- Biometric threats have serious consequences. When our biometrics are compromised, unfortunately, the mediation from these threats becomes very minimal, because we cannot change the configuration of our fingerprint.
- Cyber threats usually have high customer impacts. The financial loss can be immense, and organizational credibility is at stake.
- Insider threats are perhaps the most difficult to predict or detect. If the internal resources include an individual with bad intentions who may have significant access to the system, it becomes very difficult to protect the organizational assets.
- Having a strong cybersecurity policy is crucial to safeguard from cyber threats. We may have the most sophisticated technology, but with a weakly articulated cyber policy and less governance, an IT environment can be vulnerable to different types of cyber threats.
- We observed strong linkages between weak/no cyber policy and less investment on technology, no technology adoption, minimal training and education, and cyber awareness. Among these factors, technology adoption and human factors are the two dominant contributors. In other words, to make the digital assets safe, we need to invest adequately in security, train our employees, build and govern strong cybersecurity policy, and above all adopt and keep up with technology to overcome new and existing security threats. Developing and adopting a strong security policy will help increase awareness and provide opportunities for learning and establishing protocols to prevent cyber threats.
6. Mitigation Strategy
7. Conclusions and Open Challenges
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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Physical Intrusion (Security Violation) | Cyber Intrusion (Security Violation) |
---|---|
Reason—Greed, Activism, Political, Hurt | Reason—Greed, Activism, Political, Hurt |
Outcome to victims—Destruction, Financial Loss | Outcome to victims—Destruction, Financial Loss |
Outcome to attacker—Gain, fulfilling a political or personal agenda | Outcome to attacker—Gain, fulfilling a political or personal agenda |
Physical | Virtual |
Attacker—sense of power | Attacker—sense of power, accomplishing a political agenda |
Likelihood of getting caught is higher | Likelihood of getting caught is lower |
Mostly Visible | Not always visible—APT (takes long time) |
Visible breakage | Likely Invisible breakage |
Protection is by physical security (guard, lock) | Protection is by cyber security (Firewall, password protection) |
Case Studies | Types of Cyber Attacks | Human Factors | Industry | Financial Intensity (1–5) | Non-Financial Intensity | # of Customers Impacted (1–5) | Cultural Factors | End User Trust & Loyalty | Policy Issues | Training & Awareness | Technology Adoption | Investment |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Stuxnet Cyber Warfare | Malware (Worm) | Ignorance | Nuclear | 5 | Reputation | 4 | Y | N | Y | N | N | Y |
RSA APT Attack | APT | Ignorance | Technology | 3 | Credibility | 5 | Y | Y | Y | N | N | Y |
eBay Account Hack | Password Attacks | Ignorance | Technology | 3 | Reputation | 4 | N | N | Y | N | N | N |
German Steel Plant Attack | Social Engineering | Ignorance | Manufacturing | 3 | Maturity | 3 | N | N | Y | N | N | N |
Social Engineering Malware Attack (ISIS) | Social Engineering/Malware | Ignorance | Advertisement | 2 | Maturity | 3 | N | N | Y | N | N | N |
Heartland Payment System Data Breach 2008 | SQL Injection Attack | Ignorance | Financial | 5 | Credibility | 5 | Y | Y | N | N | Y | Y |
Home Depot Data Access Attack | malware (Worm) | Ignorance | Retail | 5 | Reputation | 5 | N | N | Y | N | N | N |
UAV (Unmanned Aerial/Air Vehicles) Feed Interception. | Cyber-Physical Attack | Ignorance | Communication | 5 | Maturity | 5 | N | N | Y | N | N | N |
Trojan Attack | Malware (Worm) | Ignorance | Financial | 4 | Maturity | 4 | N | N | Y | N | N | N |
South Korea Financial & TV Station cyber-attack—Summer of 2013 | Social Engineering/Malware | Ignorance | Entertainment/Financial | 3 | Reputation | 4 | N | N | Y | N | N | N |
Botnet Attack | DOS | Ignorance | Technology | 2 | Maturity | 3 | N | N | Y | N | N | N |
Francophoned | Social Engineering | Ignorance | Financial | 3 | Maturity | 3 | N | N | Y | N | N | N |
Interactive voice response (IVR) or Phone Phishing | Social Engineering | Ignorance | Financial | 3 | Maturity | 4 | N | N | Y | N | N | N |
Cross-Site Request Forgery (CSRF) | Browser Based Attack | Ignorance | Advertisement | 2 | Reputation | 3 | N | N | Y | N | N | N |
Sony—the wiper malware attack in 2014 | Malware (Worm) | Negligence | Entertainment | 5 | Reputation | 5 | N | N | N | Y | N | Y |
P.F. Chang’s Sales Machine Hacked | Malware | Negligence | Food | 4 | Maturity | 4 | N | N | Y | N | N | N |
Epsilon data breach attack | Malware | Negligence | Financial | 5 | Reputation | 5 | N | N | Y | N | N | N |
Omega Engineering Logic Bomb | Software Based Attack | Negligence | Technology | 5 | Credibility | 4 | N | N | Y | N | N | N |
Living social hack and password hack 2013 | Password Attacks/SQL Injection | Negligence | Communication | 4 | PII | 5 | N | N | Y | N | N | N |
Stuxnet attack through USB | APT | Negligence | Communication | 3 | Maturity | 3 | N | N | Y | N | N | N |
Hacktivism–Estonia | DOS | Negligence | Financial/Education | 4 | Reputation | 4 | Y | N | Y | N | Y | N |
Capture password by brute force | Password Attacks | Negligence | Retail | 3 | Maturity | 3 | N | N | Y | N | N | N |
TJX Cyber attack: WEP (Wired Equivalent Privacy) attack. | Malware | Negligence | Retail | 5 | PII | 5 | N | N | Y | N | N | N |
SQL Injection Attack at the Federal Reserve Bank. | Database Attack | Negligence | Financial | 5 | PII | 4 | N | N | Y | Y | N | Y |
Man in the middle attack | Software/Browser Based Attack | Negligence | Retail | 4 | Maturity | 4 | N | N | Y | N | N | N |
Tailgating | Social Engineering | Negligence | Retail | 3 | Maturity | 3 | N | N | Y | N | N | N |
Evernote DDOS Attack | DOS | Configuration | Retail | 4 | Credibility | 3 | N | N | Y | Y | N | N |
Adobe password breach 2013 | Password Attacks | Configuration | Technology | 4 | Reputation | 4 | Y | N | Y | Y | Y | N |
Dairy Queen International Data Breach | Malware | Configuration | Food & Agriculture | 4 | PII | 4 | N | N | Y | N | N | N |
Microsoft DOS Attack | DOS | Configuration | Technology | 3 | Reputation | 5 | Y | Y | N | Y | Y | Y |
Cyber espionage - Titan Rain Attack | APT | Configuration | Entertainment | 4 | Reputation | 4 | Y | N | Y | Y | N | N |
Flame Malware Attack | Malware | Configuration | Energy | 4 | Privacy | 3 | N | Y | Y | N | N | N |
Smurf Attack | DOS | Configuration | Education | 3 | Credibility | 3 | Y | Y | Y | Y | Y | N |
Logic Bomb Attack in South Korea Banks and broadcasting organizations | Database Attack | Configuration | Financial / Entertainment | 3 | Reputation | 3 | N | N | Y | N | N | N |
Kerberos Replay Attack | Password Attacks | Configuration | Communication | - | Maturity | - | N | N | Y | - | N | N |
Cross Site Scripting (XSS) | Browser Based Attack | Configuration | Entertainment | - | Reputation | - | N | N | Y | N | N | N |
iCloud Account Hack –Password Attack | Social Engineering / Password Attack | Deceit | Technology | - | Reputation | 5 | Y | Y | N | Y | Y | Y |
DOS Attack and DDOS Attack | DOS | Deceit | Entertainment | - | Reputation | 4 | N | N | Y | N | N | N |
DDOS–NTP | DOS | Deceit | Retail | - | Credibility | - | N | N | Y | N | N | - |
Bating | Social Engineering | Deceit | Transportation | 3 | Privacy | 2 | N | N | Y | - | N | N |
Pretexting | Social Engineering | Deceit | Financial | - | PII | - | N | N | Y | N | Y | Y |
Quid Pro Quo | Social Engineering | Deceit | Communication | - | Privacy | - | - | - | Y | - | N | N |
Sybil Attack | Mobile Ad hoc Network Based | Deceit | Retail | - | PII | 4 | N | N | Y | N | N | N |
Index | Association Rule | Confidence | Lift |
---|---|---|---|
1 | Investment=N ==> Policy Issues=Y | 1.00 | 1.10 |
2 | End User Trust & Loyalty=N Investment=N ==> Policy Issues=Y | 1.00 | 1.10 |
3 | Technology Adoption=N Investment=N ==> Policy Issues=Y | 1.00 | 1.10 |
4 | End User Trust & Loyalty=N ==> Policy Issues=Y | 0.97 | 1.07 |
5 | Technology Adoption=N ==> Policy Issues=Y | 0.97 | 1.07 |
6 | Cultural Factors=N ==> End User Trust & Loyalty=N | 0.97 | 1.16 |
7 | Cultural Factors=N ==> Policy Issues=Y | 0.97 | 1.07 |
8 | Cultural Factors=N ==> Technology Adoption=N | 0.97 | 1.16 |
9 | End User Trust & Loyalty=N Technology Adoption=N ==> Policy Issues=Y | 0.97 | 1.07 |
10 | Training & Awareness=N ==> Policy Issues=Y | 0.97 | 1.07 |
11 | Cultural Factors=N Policy Issues=Y ==> End User Trust & Loyalty=N | 0.97 | 1.16 |
12 | Cultural Factors=N End User Trust & Loyalty=N ==> Policy Issues=Y | 0.97 | 1.07 |
13 | Cultural Factors=N Technology Adoption=N ==> End User Trust & Loyalty=N | 0.97 | 1.16 |
14 | Cultural Factors=N End User Trust & Loyalty=N ==> Technology Adoption=N | 0.97 | 1.16 |
15 | Cultural Factors=N Technology Adoption=N ==> Policy Issues=Y | 0.97 | 1.07 |
16 | Cultural Factors=N Policy Issues=Y ==> Technology Adoption=N | 0.97 | 1.16 |
17 | Cultural Factors=N Policy Issues=Y Technology Adoption=N ==> End User Trust & Loyalty=N | 0.97 | 1.16 |
18 | Cultural Factors=N End User Trust & Loyalty=N Technology Adoption=N ==> Policy Issues=Y | 0.97 | 1.07 |
19 | Cultural Factors=N End User Trust & Loyalty=N Policy Issues=Y ==> Technology Adoption=N | 0.97 | 1.16 |
20 | Cultural Factors=N ==> End User Trust & Loyalty=N Policy Issues=Y | 0.94 | 1.15 |
21 | End User Trust & Loyalty=N Technology Adoption=N ==> Cultural Factors=N | 0.94 | 1.22 |
22 | Cultural Factors=N ==> End User Trust & Loyalty=N Technology Adoption=N | 0.94 | 1.22 |
23 | Cultural Factors=N ==> Policy Issues=Y Technology Adoption=N | 0.94 | 1.15 |
24 | End User Trust & Loyalty=N Policy Issues=Y Technology Adoption=N ==> Cultural Factors=N | 0.94 | 1.22 |
25 | Cultural Factors=N Technology Adoption=N ==> End User Trust & Loyalty=N Policy Issues=Y | 0.94 | 1.15 |
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Quader, F.; Janeja, V.P. Insights into Organizational Security Readiness: Lessons Learned from Cyber-Attack Case Studies. J. Cybersecur. Priv. 2021, 1, 638-659. https://doi.org/10.3390/jcp1040032
Quader F, Janeja VP. Insights into Organizational Security Readiness: Lessons Learned from Cyber-Attack Case Studies. Journal of Cybersecurity and Privacy. 2021; 1(4):638-659. https://doi.org/10.3390/jcp1040032
Chicago/Turabian StyleQuader, Faisal, and Vandana P. Janeja. 2021. "Insights into Organizational Security Readiness: Lessons Learned from Cyber-Attack Case Studies" Journal of Cybersecurity and Privacy 1, no. 4: 638-659. https://doi.org/10.3390/jcp1040032
APA StyleQuader, F., & Janeja, V. P. (2021). Insights into Organizational Security Readiness: Lessons Learned from Cyber-Attack Case Studies. Journal of Cybersecurity and Privacy, 1(4), 638-659. https://doi.org/10.3390/jcp1040032