Akshi Csas
Akshi Csas
KOMMA AKSHITHA
21MID0155
2
o Trojan horses disguise malicious code as 3.3. Cybersecurity Threats: Current Landscape
legitimate software, and spyware gathers
sensitive information without consent. Cybersecurity threats can arise from various sources, both
external and internal. The following are key contemporary
b. Phishing and Social Engineering: Phishing attacks threats:
involve deceiving individuals into revealing personal or
confidential information, such as usernames, passwords, or a. Nation-State Attacks: With geopolitical tensions
financial information. Phishing can be conducted through increasing, nation-states are increasingly targeting foreign
email, fake websites, or social media platforms. governments, critical infrastructure, and corporations with
sophisticated cyber operations, often involving APTs. State-
• Social engineering is often combined with sponsored actors are responsible for several high-profile
phishing, where attackers exploit psychological cyberattacks, such as those attributed to Russian, Chinese,
manipulation to trick users into revealing their and North Korean state-backed groups.
information.
b. Cybercrime: Cybercriminals are motivated by financial
c. Denial of Service (DoS) and Distributed Denial of gain and engage in activities like identity theft, fraud,
Service (DDoS) Attacks: ransomware attacks, and the dark web market. The rise in
cryptocurrency has facilitated these activities by providing a
• A DoS attack aims to overwhelm a system's means of anonymous transactions.
resources, making it unavailable to its users.
c. IoT Vulnerabilities: The proliferation of Internet of
• A DDoS attack involves multiple compromised Things (IoT) devices has expanded the attack surface for
devices, often part of a botnet, used to flood a cyber threats. Many IoT devices have poor security
target with traffic and disrupt its operations. DDoS standards, and they are often used as entry points for
attacks have become increasingly common in attackers to infiltrate larger networks. Botnets like Mirai
recent years, especially in political and commercial have exploited these vulnerabilities to conduct large-scale
cyber conflicts. DDoS attacks.
d. Man-in-the-Middle (MitM) Attacks: MitM attacks d. Cloud Security Risks: Cloud computing has introduced
occur when an attacker intercepts communications between new risks associated with data storage, privacy, and
two parties to eavesdrop, alter, or inject malicious data. This compliance. The shared responsibility model in cloud
can lead to data breaches or unauthorized data manipulation. services means that while the cloud provider secures the
Examples include session hijacking and SSL stripping infrastructure, users are responsible for securing the data and
attacks. applications within the cloud environment.
Misconfigurations, poor access control, and inadequate
e. SQL Injection and Cross-Site Scripting (XSS):
security practices can lead to data breaches.
• SQL injection occurs when an attacker inserts
e. Supply Chain Attacks: Supply chain attacks involve
malicious SQL code into an input field to gain
targeting third-party vendors or partners with access to an
unauthorized access to a database.
organization's systems. The SolarWinds attack is one of the
• XSS attacks involve injecting malicious scripts into most notorious examples, where attackers inserted a
webpages viewed by other users, often to steal backdoor into software updates, compromising thousands of
session cookies or manipulate data. organizations globally.
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attackers. Social engineering relies heavily on exploiting c. Autonomous and Adaptive Security Systems: With the
human psychology. increasing complexity and speed of cyberattacks,
autonomous security systems that can adapt and respond in
c. Inadequate Security Measures: Weaknesses in the real-time are becoming essential. These systems would be
design and implementation of security controls—such as capable of analyzing vast amounts of data, learning from
insufficient encryption, improper access control, or lack of past attacks, and predicting future threats.
network segmentation—create openings for cyberattacks.
Additionally, a lack of security awareness in both d. Blockchain for Cybersecurity: Blockchain technology,
individuals and organizations exacerbates the problem. with its decentralized, immutable ledger, holds potential for
securing sensitive transactions, preventing data tampering,
d. Supply Chain and Third-Party Risks: As organizations and enhancing transparency. Research is focused on
rely on third-party vendors and external partners, integrating blockchain into cybersecurity solutions such as
vulnerabilities in these entities' systems can lead to breaches secure voting, identity management, and supply chain
in their clients' systems. Attackers often target these third security.
parties because they may have less stringent security
protocols in place. e. Zero Trust Architecture: The Zero Trust security model,
which assumes that no user or device is trusted by default,
even inside the corporate network, is gaining prominence.
3.5. Impact of Cybersecurity Attacks Research into how to implement Zero Trust effectively,
including identity management, continuous monitoring, and
Cybersecurity breaches can have far-reaching consequences, micro-segmentation, is critical for improving security.
including financial loss, reputational damage, legal and
regulatory repercussions, and national security threats. The f. Privacy-Enhancing Technologies: As data privacy
global cost of cybercrime is estimated to be trillions of concerns rise, research into privacy-enhancing technologies
dollars annually. Specific impacts include: (PETs) such as differential privacy, homomorphic
encryption, and secure multi-party computation can provide
• Financial Loss: Direct financial losses, including new ways of analyzing data while maintaining privacy.
ransom payments and theft of intellectual property,
can cripple businesses.
a. Artificial Intelligence and Machine Learning in • Network Entry Points: Attackers can exploit
Cybersecurity: AI and ML techniques can be employed to vulnerabilities in IoT devices to gain unauthorized
enhance threat detection and response capabilities. access to larger networks, steal sensitive data, or
Researchers are exploring ways to use machine learning disrupt services.
algorithms for anomaly detection, identifying new attack
• Botnet Creation: IoT devices are often targeted to
vectors, and automating incident response.
create botnets for launching distributed denial-of-
b. Quantum Computing and Cryptography: The advent service (DDoS) attacks, exemplified by the Mirai
of quantum computing presents both a challenge and an botnet incident.
opportunity in cybersecurity. While quantum computers
Cryptocurrency and Blockchain Attacks
could break existing cryptographic schemes, they also offer
the potential for more robust encryption protocols based on • Wallet Theft and Exchange Breaches: Attackers
quantum principles. Research into post-quantum target cryptocurrency wallets and exchanges
cryptography is vital. through phishing, malware, or exploiting weak
security practices.
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• Smart Contract Exploits: Vulnerabilities in smart • Complex Systems: Large, interconnected systems
contract code can result in financial losses, as seen often have dependencies that create unintended
in notable breaches like the DAO hack. security gaps.
• Mining Pool Compromises: Attackers can disrupt Human Factors and Security Awareness
or hijack mining pools, diverting rewards or
degrading network performance. • Social Engineering Attacks: Techniques like
phishing and baiting exploit human psychology,
• Blockchain Integrity Risks: While blockchain is bypassing technical defenses.
inherently secure, weaknesses in its implementation
or adjacent technologies can be exploited. • Weak Password Practices: Poor password
hygiene, including the use of default, weak, or
Artificial Intelligence (AI) and Machine Learning (ML) reused passwords, is a common vulnerability.
Threats
• Lack of Training: Employees often lack awareness
• Automated Phishing Campaigns: AI-driven of cyber threats, increasing their susceptibility to
phishing attacks leverage natural language attacks.
processing to create highly convincing and
personalized messages, increasing their success Regulatory and Compliance Complexities
rate. • Diverse Standards: Different regions and
• Deepfake Technologies: Attackers use AI- industries have unique regulations, creating
generated deepfake videos or audio to impersonate challenges for multinational organizations.
individuals, enabling fraudulent transactions or • GDPR and Beyond: Stringent regulations like the
spreading misinformation. General Data Protection Regulation (GDPR)
• Adversarial AI Attacks: Malicious actors can impose severe penalties for non-compliance,
manipulate AI models by feeding them crafted data requiring robust data protection measures.
to mislead or disrupt their functioning, affecting • Evolving Legal Landscape: Organizations must
applications like facial recognition or fraud constantly adapt to new laws and guidelines, which
detection. can be resource-intensive.
4.2 Cyber Security Vulnerabilities and Challenges • Real-time Monitoring: Developing tools to detect
and respond to threats as they occur, minimizing
Software Vulnerabilities potential damage.
• Outdated Software: Many organizations fail to • Automated Incident Response: AI-driven
update software regularly, leaving systems exposed automation can identify and neutralize threats faster
to known vulnerabilities. than manual processes.
• Zero-Day Exploits: Attackers increasingly target
• Early Warning Systems: Building systems
undiscovered software vulnerabilities, making
capable of predicting and alerting organizations
proactive security measures critical. about emerging threats based on data patterns.
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Blockchain-based Security Solutions cyberattacks, new threats, and major vulnerabilities.
The analysis analyzed prevalent cyber attacks, including
• Enhanced Data Integrity: Using blockchain to malware, phishing, DDoS, and advanced persistent threats,
ensure the immutability and authenticity of while also investigating the varied motivations behind these
sensitive information. criminal acts. After that, it examined current cybersecurity
threats, emphasizing how they are becoming more complex
• Secure Supply Chains: Implementing blockchain
and dynamic. These threats include supply chain assaults,
for tracking and verifying goods throughout supply
chains, reducing risks of tampering. nation-state attacks, cybercrime, IoT vulnerabilities, and
cloud security issues.
• Decentralized Identity Management: Employing
The review also examined the underlying causes of
blockchain for secure, user-controlled identity
cybersecurity vulnerabilities, including software bugs,
systems to mitigate fraud.
human error and carelessness, insufficient security
Artificial Intelligence and Machine Learning for Cyber measures, and the dangers associated with third-party
Defense dependencies. It was underlined that cybersecurity breaches
have serious consequences, including monetary losses, harm
• Anomaly Detection: Leveraging ML to identify to one's reputation, and repercussions for national security.
unusual patterns indicative of cyber threats. The paper listed a number of important topics for upcoming
cybersecurity research. Among these are the creation of
• Predictive Analytics: Using AI to forecast
proactive threat detection and response systems, the use of
potential vulnerabilities and attacks based on
blockchain technology for improved security, the
historical data.
development of encryption that is resistant to quantum
• Adaptive Security Systems: Building systems errors, and the use of AI and machine learning to strengthen
capable of evolving defenses in response to cyber defenses. It was also emphasized how important it is
emerging threats. to handle new threats like cryptocurrency attacks, IoT
vulnerabilities, and the security issues brought on by 5G and
Internet of Secure Things (IoST) edge computing.
• Secure-by-Design Principles: Ensuring IoT In order to help scholars, practitioners, and policymakers
devices are built with robust security features from navigate the constantly changing landscape of cybersecurity
inception. opportunities and challenges, this review will synthesize
insights from recent studies and trends. This will ultimately
• End-to-End Encryption: Implementing help to develop more secure and resilient digital systems.
comprehensive encryption for data in transit and at
rest across IoT ecosystems.
Sl. Paper Title Objective Applicati Challenges Security Dataset Evaluatio Key Limitations Results/Rem
No /Author on Identified Techniques Utilized n Metrics Contributi arks
/References utilized ons
1 To provide a
"A Survey of
comprehens
Cybersecurity Vulnerabili Serves as a
ive survey Difficulty in Comprehen
Vulnerabilitie ty valuable
of managing sive review Lack of
s, Attacks, assessment, overview for
vulnerabiliti General emerging of detailed
and intrusion Not Not cybersecurit
es, threats, cybersecu threats, lack cybersecuri implementa
Countermeas detection specified specified y
and rity of standard ty threats tion
ures" systems, professional
countermeas countermeas and strategies.
(Dhanraj, R., firewalls, s and
ures in ures defenses.
& Mishra, encryption researchers.
cybersecurit
M., 2017)
y.
2 Provides a
"Cyber To classify Rapidly classificati
Highlights
Security various evolving on
Intrusion Generalized the need for
Attacks: cyberattacks attack framework
Cyberatta detection, in scope adaptive
Classification and propose techniques, for
ck behavioral Not Not without defense
and Future future insufficient cyberattack
classificat analysis, specified specified detailed mechanisms
Directions" directions research s and
ion machine case as attack
(Bhardwaj, for into new outlines
learning studies. methods
A., & Pathak, cybersecurit attack future
evolve.
A., 2019) y research. vectors research
areas.
3 Lack of Explains
To explore large, the Demonstrate
"The Role of Dependence
the labeled Machine Accuracy, potential of s promising
Machine Publicly on high-
integration datasets, learning false ML for results for
Learning in Threat available quality data
of machine complexity algorithms, positive cybersecuri automating
Cybersecurity detection, datasets for effective
learning in anomaly rate, ty, focusing threat
: A Survey" anomaly for ML machine
techniques interpreting detection, recall, on attack detection
(Singh, A., & detection (e.g., learning
into results from neural precision, prediction using
Sharma, M., KDDCup) model
cybersecurit machine networks F1-score and machine
2020) training.
y. learning anomaly learning.
models detection.
4 "Cyber Highlights
Encryption,
Security IoT device the specific IoT Acknowledg
secure
Threats, To discuss vulnerabiliti vulnerabilit ecosystems es the urgent
communica IoT-
Challenges, the unique es, ies in IoT are highly need for IoT-
tion specific
and cybersecurit IoT scalability Not systems heterogeneo specific
protocols, datasets or
Vulnerabilitie y challenges security issues, weak specified and us, cybersecurit
IoT- simulated
s in IoT" in IoT device suggests complicatin y standards
specific data
(Zhang, Y., & systems. authenticati approaches g defense and
intrusion
Wang, Z., on to mitigate strategies. practices.
detection
2018) them.
7
5 Provides a
"A Survey on To survey Surveys good
Network common Increasing Firewalls, different foundation
Lack of
Security network complexity IDS/IPS, types of for network
Detection real-world
Attacks and security of network traffic Network network security
Network rate, false network
Defense attacks and traffic and analysis, traffic attacks and defense
security positive attack data
Mechanisms" their growing deep datasets proposes mechanisms,
rate for
(Liu, L., & defense sophisticatio packet defense though more
evaluation.
Zhang, W., mechanisms n of attacks inspection mechanism practical
2019) . s for each. testing is
needed.
6 Evolving Identifies
"Emerging nature of emerging Highlights
To discuss Threat
Cybersecurity threats, threats like Many the critical
emerging intelligence
Threats: An challenges AI and emerging need for
cybersecurit sharing,
Overview and General in keeping quantum threats are proactive
y threats advanced Not Not
Future cybersecu pace with computing speculative cybersecurit
and future malware specified specified
Directions" rity new attack and offers and require y research in
directions analysis,
(Gupta, M., & vectors, lack insights on extensive anticipating
for research AI-based
Sharma, R., of future validation. future
in the field. detection
2020) standardized defense threats.
defenses strategies.
7 Discusses
"Cyber
the role of
Threat Data Adoption Advocates
To survey Data sharing collaborati
Intelligence anonymizat hurdles, for improved
the role of trust issues, Threat Informatio ve defense
Sharing: A Cyber ion, including frameworks
cyber threat technical intelligenc n sharing and
Survey of threat encryption privacy to facilitate
intelligence barriers, and e datasets, accuracy, intelligence
Techniques, intelligen for secure concerns better
sharing in lack of public attack sharing in
Models, and ce sharing, and collaboratio
improving collaboratio repositorie detection cybersecuri
Applications" sharing machine organizatio n between
cybersecurit n between s rate ty, with
(Hossain, M., learning for nal security
y. entities various
& Khan, S., analysis resistance. entities.
models
2021)
explored.
8 "A
Comprehensi OWASP Reviews Focuses on
To survey
ve Survey on vulnerabiliti Secure top known
common
Web es, lack of coding vulnerabilit attack Strong focus
security OWASP Detection
Application Web secure practices, ies in web types, on practical
vulnerabiliti Top 10, accuracy,
Security applicatio coding penetration application lacking web security
es and CVE remediatio
Attacks and n security practices, testing, s and exploration defense
attacks in databases n time
Vulnerabilitie session vulnerabilit discusses of new web tools.
web
s" (Alharbi, managemen y scanners defensive security
applications.
H., & Patel, t issues techniques. risks.
R., 2018)
9 Discusses
Shared the security Overempha Calls for
"Cybersecurit To discuss Encryption,
resources, Cloud challenges sis on more
y Challenges cybersecurit access Data
multitenanc service specific to cloud- research into
and Research y issues and control breach
Cloud y, lack of provider cloud specific secure cloud
Opportunities research policies, rate,
computin visibility logs, computing challenges, architectures
in Cloud opportunitie multi- intrusion
g into third- simulated and less focus , with a
Computing" s in cloud factor detection
party environme provides a on hybrid focus on
(Li, X., & Yu, environment authenticati rate
infrastructur nts roadmap cloud trust and
S., 2019) s. on
e for future models. privacy.
research.
10 Rate
"A Survey on Distributed limiting,
Provides an Mitigation
DDoS Attacks To review attack traffic Emphasizes
Attack in-depth techniques
and DDoS complexity, analysis, Network the need for
mitigation review of often
Mitigation attack difficulty in anomaly traffic scalable,
DDoS efficiency, DDoS struggle
Techniques" techniques real-time detection datasets distributed
protection service attack types with scale
(Natarajan, and mitigation, systems, for DDoS DDoS
availabilit and and high
P., & mitigation large-scale cloud- simulation mitigation
y defensive traffic
Muthusamy, methods. botnet based solutions.
techniques. volumes.
R., 2021) threats DDoS
protection
11 Reviews AI
Shows
techniques
Lack of Machine significant
"Artificial for
labeled data, learning promise for
Intelligence in AI-based Publicly detecting AI models
To explore the black- algorithms, automating
Cybersecurity threat available Accuracy, and require a
the box nature deep threat
:A detection, malware detection mitigating large
applications of AI learning, detection but
Comprehensi anomaly datasets rate, false cyber volume of
of AI in models, decision requires
ve Review" detection, (e.g., positive threats, quality data
cybersecurit computation trees, AI- further
(Salama, S., malware CICIDS rate with to function
y. al resource based refinement
& Ganaie, M., analysis 2017) examples effectively.
requirement malware in model
2020) of
s analysis transparency
successful
.
application.
8
12 Highlights
the unique
Security
Lack of cybersecuri
"Cybersecurit Secure frameworks Urges the
To identify standardized ty needs of
y for Smart communica Risk are still development
cybersecurit security Smart city smart
Cities: tion reduction, underdevelo of secure,
y challenges Smart frameworks, datasets, cities,
Challenges, protocols, vulnerabili ped for scalable
in smart city IoT simulated particularly
Threats, and data ty smart cities, solutions for
cities and systems vulnerabiliti environme in the
Solutions" encryption, detection hindering future smart
propose es, data nts context of
(Verma, A., & smart grid rate full city
solutions. privacy IoT and
Rai, S., 2021) security implementa ecosystems.
concerns critical
tion.
infrastructu
re.
13 Proposes
"Next- Increasing
next-
Generation To discuss sophisticatio
generation Highlights
Cyber the future of n of Many next-
Next-gen defense the need for
Defense cybersecurit cyberattacks gen systems
firewalls, Detection systems future-proof
Systems: y defense General , difficulty are still in
AI-based Not accuracy, leveraging defense
Challenges mechanisms cybersecu in the
security, specified resilience AI, systems that
and Research , focusing rity integrating conceptual
blockchain to attack blockchain, can evolve
Directions" on next- next-gen or prototype
for security and other with new
(Ahmed, A., generation technologies phase.
modern threats.
& Khan, S., systems. into legacy
technologie
2020) systems
s.
14 Provides a
Scalability Demonstrat
To explore Blockchain compelling
"Blockchain issues, Blockchain es how
the potential integration case for
for Blockchai performance , Attack blockchain
of into integrating
Cybersecurity n for overhead, cryptograp Blockchai detection can
blockchain existing blockchain
: Threats and secure lack of hic n datasets, rate, enhance
technology systems is in
Opportunities transactio standard techniques, security scalability security,
in complex cybersecurit
" (Kumar, V., ns, data protocols decentraliz logs performan particularly
enhancing and y but
& Verma, N., protection for ed trust ce in
cybersecurit resource- requires
2022) blockchain systems decentraliz
y. intensive. standardizati
security ed systems.
on.
15 Emphasizes
Explores The the
To discuss the security transition to importance
"Cybersecurit Network 5G-specific
cybersecurit Network risks 5G of
y Risks and slicing encryption, 5G testbed
y challenges reliability, specific to networks developing
Emerging vulnerabiliti network environme
specific to 5G attack 5G may expose robust
Threats in 5G es, massive slicing nts,
5G network resilience, networks new attack security
Networks" IoT device security, network
networks security data and vectors, measures for
(Zhou, M., & integration, edge simulation
and explore confidenti suggests making 5G network
Zhang, T., supply chain computing datasets
research ality measures to security infrastructur
2020) risks security
directions. mitigate more e before
those risks. complex. widespread
deployment.