IA 2 - UNIT 2 Flashcards

1
Q

It involves using the internet, intranet, extranet, or other networks to support business processes.

A

E-Business

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2
Q
  • Primarily refers to online buying, selling, marketing, and servicing products and services.
  • Includes payment and delivery of products/services online.
A

E-Commerce

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3
Q

phishing attack primary targets

A
  1. retail services
  2. financial institutions
  3. ISP
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4
Q

Identified privacy and security as significant
concerns.

A

2001 Study
(Udo)

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5
Q

Buyer concerns about website security remain
critical.

A

2014 Findings
(Hartono et al.)

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6
Q

Importance of information security in e-commerce financial transactions.

A

2016 Emphasis
(Jotwani &
Dutta)

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7
Q

Types of Security
Threats

A
  1. Denial of Service (DoS)
  2. Spying Attacks
  3. Unauthorized Access
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8
Q

Overloading servers to make services unavailable.

A

Denial of Service
(DoS)

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9
Q

Interception of sensitive information during transactions (e.g., man-in-the-middle attacks).

A

Spying Attacks

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10
Q

You are gaining access to user accounts or sensitive data without permission.

A

Unauthorized Access

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11
Q

Types of DoS Attacks

A
  1. DDoS
  2. Virus Infection
  3. Computer Worms
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12
Q
  • Involves multiple compromised systems (botnets).
  • Often undetected by the owners of infected systems.
A

DDoS

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13
Q
  • Deliberately corrupts or deletes data.
  • Spread via email attachments or downloads.
A

Virus Infection

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14
Q

Self-replicating does not necessarily damage
but consumes bandwidth.

A

Computer
Worms

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15
Q

Types of Spying Attacks

A
  1. Sniffing
  2. Man in the Middle Attack
  3. Key Logging
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16
Q

Applications or devices that read, monitor, and
capture network data exchanges.

A

Sniffing

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17
Q

An attack where the attacker intercepts and
relays messages between two parties.

A

Man in the Middle Attack

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18
Q

a spying attack that records
each user’s keystroke on a computer.

A

Keylogging

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18
Q

Consequences of Spying Attacks

Gaining access to sensitive information can lead to:

A
  1. Identity theft
  2. Financial fraud
  3. Corporate espionage
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19
Q

is an organized framework of concepts, beliefs, principles, policies, procedures, techniques, and measures that protect system assets against threats.

A

security

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20
Q

Methods Supporting the AIC Objectives

A
  1. Authentication
  2. Encryption
  3. Access Control
  4. Firewalls
  5. Intrusion Detection and Prevention
  6. Systems (IDPS)
  7. Message Digest/Checksum
  8. Honeypot
  9. Digital Signature & Certificate
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21
Q
  • Technologies that measure and analyze unique physiological or behavioral characteristics are used to verify or identify individuals.
  • These technologies are convenient, as they eliminate the need for cards or passwords, and they are unique to each person, making them a reliable form of authentication.
A

Biometrics for
Authentication

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22
Q

Fingerprints were collected for bank verification
and mobile SIM registration.

A

Nigeria

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23
Q

Bradesco Bank’s palm vein biometric ATM
system

A

Brazil

24
Q

Biometric identification database to reduce
benefit fraud.

A

India

25
Q
  • The user provides biometric data via a sensor.
  • A template is created and stored.
A

Registration

26
Q

Modes of Biometrics

A
  1. Physical Biometrics
  2. Behavioral Biometrics
27
Q
  • User provides biometric data again.
  • New template is generated and compared to the stored one.
  • Access granted or denied based on matching.
A

Authentication

28
Q

Physical
Biometrics

A
  1. Fingerprints
  2. Face Recognition
  3. Hand Geometry
  4. Iris Recognition
  5. Palm Vein
  6. Identification
29
Q

Behavioral
Biometrics

A

Keystroke dynamics

30
Q
  • Generates profiles for network nodes based on sampled data.
  • Identifies nodes with out-of-line profiles as potential attackers.
A

Bayes Probability Algorithm

31
Q

Sampling and anomaly detection to monitor network nodes.

A

Kalutarage’s
Approach

32
Q
  • Combines boosting techniques with neural networks to improve the accuracy and generality of intrusion detection.
  • Tran et al. [68]
A

Adaptive Boosting &
Semiparametric Neural Networks

33
Q
  • Feng et al. [69]
  • A hybrid method that mines network data to detect anomalies and potential attacks.
A

State Vector Machine &
Ant Colony Networks

34
Q

Benefits of Machine Learning in Intrusion
Detection

A
  • Adaptive algorithms that learn and evolve with new attacks.
  • Real-time detection and response to anomalies.
  • Reduces manual analysis, increasing detection accuracy.
35
Q

is a decentralized, transparent, and secure method for managing transactions and data without intermediaries.

A

Blockchain

35
Q

Peer-to-Peer Security Using
Blockchains

A
  1. Immutability
  2. Protection from Fraud
  3. Cryptographic Hashing
36
Q

Once a block is
accepted and added
to the chain, it cannot
be altered.

A

Immutability

37
Q

The blockchain structure and validation process prevent tampering and fraudulent transactions.

A

Protection from
Fraud

38
Q

SHA-256 provides a
secure hash function,
ensuring data integrity.

A

Cryptographic
Hashing

39
Q

Challenges
in
Blockchain
Security

A
  1. Anonymity Concerns
  2. Scalability Issues
40
Q
  • Bitcoin transactions are anonymous, which may not be acceptable for traditional sectors like banking.
  • Solution: Modified blockchain models with knowable user identities.
A

Anonymity
Concerns

41
Q

Current implementations
may face challenges
scaling to accommodate
larger numbers of
transactions.

A

Scalability
Issues

42
Q

Peers in the network who validate new transactions by solving cryptographic puzzles.

A

Data Miners

43
Q

Maps business processes, application systems, and network topologies against possible attacks and defenses.

A

Enterprise
Security
Model

44
Q

As enterprises move to the cloud, network complexity increases,
making security more challenging.

A

Cloud
Complexity

45
Q

service oriented security framework

A
  1. authentication certificates
  2. code filters
  3. https
  4. ids/ips
  5. encryption
  6. access control
  7. seperate server for business data
45
Q

JP Morgan Chase employs a multi-layered security model to protect its banking and financial data. This model includes comprehensive business process mapping to identify potential vulnerabilities in financial transactions, customer data, and infrastructure.

A

Enterprise Security
Architecture

46
Q

Three
Phases of user education and engagement in information security

A
  1. awareness
  2. training
  3. education
47
Q

Basic understanding of security concepts.

A

Awareness

47
Q

incorporating awareness, training, and education at different user levels. This includes regular employee security briefings, specialized IT training, and advanced education for
cybersecurity staff.

A

Security Awareness
Programs at NASA

47
Q

In-depth knowledge for professionals working in
security fields.

A

Education

47
Q

Developing specific skills to handle security
challenges.

A

Training

48
Q

offers training materials and simulation tools to help organizations educate employees and end-users about phishing attacks. Their e-learning modules simulate real phishing scenarios to raise awareness and improve responses.

A

APWG’s Anti-Phishing
Training

49
Q

Methods of Delivering Security Awareness Training

A
  1. E-learning
  2. Content Coverage
  3. Compliance
50
Q

Mandatory online courses.

A

E-learning

50
Q

Phishing awareness, password security,
handling sensitive data

A

Content
Coverage

50
Q

Specific organizational requirements for data security

A

Compliance

51
Q

Example of
E-learning
Training

A
  1. Password Management Best Practices
  2. Sensitive Data Handling Procedures
  3. Phishing and Social Engineering
  4. Compliance and Regulatory Awareness (e.g., GDPR, HIPAA).