Information Technology & Data Analytics

profilejenny2000000
08-Lesson_08.pdf

Lesson 8: Protecting People and Information

Information Technology & Data Analytics

November 29, 2021

Information Technology & Data Analytics

Protecting People and Information: Threats and Safeguard

Chapter 8

8

Information Technology & Data Analytics

Introduction

13

Information Technology & Data Analytics

➢ Handling information responsibly means understanding the following issues

• Ethics

• Personal privacy

• Threats to information

• Protection of information

INTRODUCTION

14

Information Technology & Data Analytics

1. Ethics

• Learning Outcomes #1 & #2

2. Privacy

• Learning Outcome #3

3. Security

• Learning Outcome #4

CHAPTER ORGANIZATION

15

Information Technology & Data Analytics

Ethics

16

Information Technology & Data Analytics

➢ Ethics

• the principles and standards that guide our behavior toward other people

➢ Ethics are rooted in history, culture, religion, and philosophy

➢ The question is:

• what is right or wrong?

ETHICS

17

Information Technology & Data Analytics

➢ Actions in ethical dilemmas determined by

• Your basic ethical structure

• The circumstances of the situation

➢ Your basic ethical structure determines what you consider to be

• Minor ethical violations

• Serious ethical violations

• Very serious ethical violations

Factors that Determine How You Decide Ethical Issues

18

Information Technology & Data Analytics

Basic Ethical Structure

19

Information Technology & Data Analytics

1. Consequences of the action or inaction

2. Society’s opinion of the action or inaction

3. Likelihood of effect of action or inaction

4. Time to consequences of action or inaction

5. Relatedness of people who will be affected by action or inaction

6. Reach of result of action or inaction

Circumstances of the Situation

20

Information Technology & Data Analytics

➢ Intellectual property – intangible creative work that is embodied in physical form

• Is digital creative work considered intellectual property as well?

oYes!

➢ Copyright – legal protection afforded an expression of an idea

• Can you used copyrighted material without permission?

oMaybe, but usually no

➢ Fair Use Doctrine – may use copyrighted material in certain situations:

• For teaching purposes

• Certain transformative uses are considered fair in the U.S.

Intellectual Property

21

Information Technology & Data Analytics

➢ Using copyrighted software without permission violates copyright law

➢ Pirated software

• the unauthorized use, duplication, distribution, or sale of copyrighted software

➢ Remember technology can leave a trace!

• Websites you have visited

• Pictures you have taken (digital pictures have metadata)

• Emails you have sent

• Devices you have used

• Ink jet printers may leave tracking information as well

Intellectual Property

22

Information Technology & Data Analytics

➢ The European Union adopted the proposal on digital copyright rules in September, 2018

➢ Makes sharing platforms such as YouTube, Facebook, or Google News liable for copyright infringements.

➢ These parties also need to pay right holders for copyrighted material that they make available • It exempts small and micro platforms from the directive • Open source platforms will not be affected

➢ Enables authors and performers to “claim” additional remuneration from the party exploiting their rights when the remuneration originally agreed is “disproportionately” low compared to the benefits derived.

➢ This is the original proposal on copyright in the Digital Single Market

Intellectual Property

23

Information Technology & Data Analytics

➢ Always use citations and add references to the material you use

➢ Use free images protected under CC-0 (Creative Commons 0) or Public Domain Licenses

➢ Sites include, but are not limited to:

• Pexels

• Unsplash

• Public Domain Pictures

What can you do?

24

Information Technology & Data Analytics

Privacy

25

Information Technology & Data Analytics

➢ Privacy – the right to left alone when you want to be, to have control over your own personal possessions, and not to be observed without your consent

➢ Dimensions of privacy

• Psychological: to have a sense of control

• Legal: to be able to protect yourself

➢ Personal information privacy

• Do we have the right to information privacy?

• What can be done with our private data?

PRIVACY

26

Information Technology & Data Analytics

➢ Key logger (key trapper) software

• a program that, when installed on a computer, records every keystroke and mouse click

➢ Hardware key logger

• hardware device that captures keystrokes moving between keyboard and motherboard

➢ Screen capture programs

• capture screen from video card

Privacy and Other Individuals

27

Information Technology & Data Analytics

➢ E-mail is stored on many computers as it travels from sender to recipient

Is E-mail Safe?

28

Information Technology & Data Analytics

➢ E-mail service with built end-to-end encryption

Welcome, ProtonMail!

29

Information Technology & Data Analytics

Privacy Concerns

30

➢ Facebook tracks your browsing

➢ Google remembers all your searches

• You can delete your search history and other data

• https://safety.google/

• https://myactivity.google.com

➢ Your Internet Service Provider (ISP) has your browsing history

➢ Each website you visit may have many trackers that follow your browsing habits

• Add-ons such as Ghostery help blocking tracking technologies

Information Technology & Data Analytics

➢ Cookie ▪ a small file that contains information about you and your Web

activities, which a Web site places on your computer • Usually improve your browsing experience • Could store unwanted private information. The European Union

passed legislations about cookies.

➢ Web log – ▪ one line of information for every visitor to a Web site

➢ Clickstream ▪ records information about you such as what Web sites you

visited, how long you were there, what ads you looked at, and what you bought.

Privacy While Browsing

31

Information Technology & Data Analytics

➢ Anonymous Web browsing (AWB) – hides your identity from the Web sites you visit

➢ Use a proxy

➢ Use your browser’s privacy mode

➢ Use a search engine which does not track you, such as Duck Duck Go

Privacy While Browsing

32

Information Technology & Data Analytics

Anonymity while browsing

33

➢ Tor project – Promotes anonymity online

• Can be used as a browser in your device

• Orbot is a free proxy for Android to use other apps securely

➢ A proxy is another system which redirects your communications

• A proxy is someone who represents someone else

Information Technology & Data Analytics

Anonymity while browsing

34

➢ VPN • Virtual Private Network • It is an extension of a private network that links it through a

public network

➢ Current top vendors: • NordVPN • TunnelBear VPN • Private Internet

Access VPN • Proton VPN

Information Technology & Data Analytics

New Privacy Concerns

35

➢ Geolocation information

➢ Event Data Recorders (EDR) – located in the airbag control module and collects data from your car as you are driving. • What other information might your car be tracking?

➢ Tracker apps for smartphones • Some are available after jailbreaking or rooting your device, and

might be “invisible” to the user

➢ Beware of DNS Hijacking

• What can you do? ▪ Always set up the screen lock ▪ Use encrypted communications, such as Signal

Information Technology & Data Analytics

➢ Businesses want:

• To gather prospective customers’ information

• To advertise their products

➢ Businesses should:

• Let customers know about their products, but not pester them with unwanted advertising

➢ Consumers want businesses to:

• Know who they are, but not to know too much

• Provide them with what they want, but not gather information on them

Privacy and Consumers

36

Information Technology & Data Analytics

➢ Companies need information about their employees to run their business effectively

➢ As of March 2005, 60% of employers monitored employee e-mails

➢ 70% of Web traffic occurs during work hours

➢ 78% of employers reported abuse

➢ 60% employees admitted abuse

➢ Visiting inappropriate sites

➢ Gaming, chatting, stock trading, social networking, etc.

Privacy and Employees

37

Information Technology & Data Analytics

➢ Success – Hire the best people possible

➢ Efficiency – Make sure employees make the best use of their time

➢ Compliance – Ensure appropriate behavior on the job

➢ HR and Legal – Avoid litigation for employee misconduct

➢ Intellectual Property – Data Loss Prevention(DLP)

➢ Security – Avoid intrusions

Reasons for Monitoring

38

Information Technology & Data Analytics

➢ About 2,000 government agencies have databases with information on people

➢ Government agencies need information to operate effectively

➢ Whenever you are in contact with government agency, you leave behind information about yourself

Privacy and Government Agencies

39

Information Technology & Data Analytics

➢ Law enforcement

• NCIC (National Crime Information Center)

• FBI

➢ Electronic Surveillance

• Carnivore or DCS-1000

• Magic Lantern (software key logger)

• NSA (National Security Agency)

• Echelon collect electronic information by satellite

Government Agencies Storing Personal Information

40

Information Technology & Data Analytics

➢ IRS

➢ Census Bureau

➢ Student loan services

➢ FICA

➢ Social Security Administration

➢ Social service agencies

➢ Department of Motor Vehicles

Government Agencies Storing Personal Information

41

Information Technology & Data Analytics

➢ Health Insurance Portability and Accountability Act (HIPAA) protects personal health information

➢ Financial Services Modernization Act requires that financial institutions protect personal customer information

Laws on Privacy

42

Information Technology & Data Analytics

➢ General Data Protection Regulation (GDPR) • Cookies • Data breach reporting

➢ ePrivacy Directive (ePR) • Confidentiality • Metadata • Spam • Cookies (again)

➢ China’s PIPL • Similar to GDRP • Compensation and HR • Into effect November 1st,

2021

Laws on Privacy

43

Information Technology & Data Analytics

• Incident in which otherwise protected data has been viewed, stolen or used by an unauthorized entity

Data Breach

44 Breach Level Index, 2016

Information Technology & Data Analytics

• Incident in which otherwise protected data has been viewed, stolen or used by an unauthorized entity

Data Breach

45 Breach Level Index, 2017

Information Technology & Data Analytics

• Incident in which otherwise protected data has been viewed, stolen or used by an unauthorized entity

Data Breach

46 Breach Level Index, 2018 First Half Infographic

Information Technology & Data Analytics

Data Breach

47 Breach Level Index, 2018 First Half Infographic

Information Technology & Data Analytics

Data Breach

48 Breach Level Index, 2018 First Half Infographic

Information Technology & Data Analytics

Data Breach

49 Breach Level Index, 2018 First Half Infographic

Information Technology & Data Analytics

World’s Biggest Data Breaches

50 World’s Biggest Data Breaches and Hacks

Information Technology & Data Analytics

➢ The forging of someone’s identity for the purpose of fraud

Identity Theft

51 Breach Level Index, 2018 First Half Report

Information Technology & Data Analytics

Organization Records breached

Date of Breach

Type of Breach

Source of Breach

Location Industry

Thailand Tourism

106,000,000 08/21 Identity Theft Malicious Outsider

Thailand Government

Experian 220,000,000 01/21 Identity Theft Malicious Outsider

Brazil Financial

Facebook 2,100,000,000 04/04/18 Identity Theft Malicious Outsider

U.S. Social Media

Equifax 147,900,000 07/15/17 Identity Theft Malicious Outsider

U.S. Financial

Home Depot 109,000,000 09/02/14 Financial Access

Malicious Outsider

U.S. Retail

JP Morgan 83,000,000 08/27/14 Identity Theft Malicious Outsider

U.S. Financial

Notable Breaches

52 Breach Level Index

Information Technology & Data Analytics

53

➢ Vulnerability in a web applications tool, Apache Struts • The patch was released on March 7th, 2017 • Equifax knew about the flaw, but did not take action fast enough

➢ The company claims it identified the breach on July 29th, 2017 • Equifax waited for a full day to take the application offline • They discovered the breach started by Mid-May, 2017

➢ Hackers got access to Personal Identifiable Information (PII) such as: • Name, social security number, birth date, address, license

number, credit card information

➢ The breach was publicly announced on September 7th, 2017

Information Technology & Data Analytics

54

➢ Equifax created a website (equifaxsecurity2017.com)…

but instead sent its users to a fake site (securityequifax2017.com)

➢ Some of its executives sold $1.8 million USD in shares after the breached was identified

• It was later confirmed they did not know about the breach at the time

➢ The following issues also collaborated to the debacle:

• PII as not properly encrypted

• Did not have effective breach detection mechanisms

• Network was not segmented enough

Information Technology & Data Analytics

55

➢ Breach happened in 2016

➢ Hacker gained access to information of 57 million riders and drivers

➢ Names and license number of 600,000 drivers were exposed

➢ Uber paid the hacker $100,000 through its bug bounty program

➢ Company asked the hacker to:

• delete the data

• stay quiet

• Signed a nondisclosure agreement.

New York Times: Uber Settles Data Breach Investigation for $148 Million

Information Technology & Data Analytics

56

➢ Uber covered up the incident

➢ November 2017: The Breach was released to the media

➢ September, 2018: A settlement of $148 million USD was reached and divided among all US states and D.C.

New York Times: Uber Settles Data Breach Investigation for $148 Million

Information Technology & Data Analytics

57

➢ Attacks started March, 2018

➢ They tried containing it for three months

➢ Admitted to the attack six months later

➢ 9.4 million records were stolen, all from passengers

➢ They had just spent over 1 billion USD on network improvements

➢ Opened a website for users to confirm if they were affected: https://infosecurity.cathaypacific.com/

Information Technology & Data Analytics

58

➢ On July 17th, 2019, the bank received a tip that customer’s personal information was posted on Github.

➢ Two days later, they confirmed information from credit card users was taken

➢ The incident took place on March 22, nearly four months before the tip

➢ Single hacker? Paige Thompson

➢ Stolen data includes • 140,000 Social Security Numbers • 80,000 linked bank account numbers • One million Canadian Social Insurance Numbers • Customer status, credit scores, credit limits, balances, transactions,

contact information, among other data

Information Technology & Data Analytics

59

➢ How was the hack performed? • Hacker found a misconfigured firewall on a AWS cloud server • Then used a “special command” to extract files from a directory

➢ Capital One claims they fixed the breach shortly after they were notified

➢ People Affected • 100 million individuals in the USA • Six million individuals in Canada

➢ What now?

➢ Capital One official information on the issue

Information Technology & Data Analytics

➢ Phishing (carding, brand spoofing)

• a technique to gain personal information for the purpose of identity theft

➢ Spear phishing

• targeted to specific individuals

➢ Whaling

• targeted to senior business

executives and government leaders

Identity Theft

60

Phishing

Spear Phishing

Whaling

Information Technology & Data Analytics

Identity Theft

61

Information Technology & Data Analytics

Phishing and Whaling

62LinkedIn

Information Technology & Data Analytics

➢ Pharming • rerouting your request for a legitimate Web site by

osending it to a slightly different Web address oor by redirecting you after you are already on the legitimate

site

➢ Pharming gains access to the giant databases that Internet providers use to route Web traffic.

➢ Hard to spot

➢ Line of defense: • Secure websites! SSL, https

Pharming

63

Information Technology & Data Analytics

➢ Spoofing • To disguise itself to trick someone • E-mail, website and even phone spoofing are very common

➢ Spam • unsolicited e-mail from businesses advertising goods and services

➢ These e-mails get past spam filters by • Inserting extra characters • Inserting HTML tags that do nothing • Replying usually increases, rather than decreases, amount of spam

➢ Lately, e-mail servers and clients have become very efficient at filtering spam

Spoofing and Spam

64

Information Technology & Data Analytics

Spoofing

65

Information Technology & Data Analytics

➢ Adware

• software to generate ads that installs itself when you download another program

➢ Spyware (sneakware, stealthware)

• software that comes hidden in downloaded software and helps itself to your computer resources

➢ Trojan horse software

• software you don’t want disguised as something else

➢ Scareware

• It does not cause harm, but causes the user to get anxious and take action

Cyber Threats

66

Information Technology & Data Analytics

Scareware

67The Windows Club

Information Technology & Data Analytics

➢ Ransomware • Takes your device “hostage” until a ransom is paid • Cryptoviral

oIt does encrypt files, making it almost impossible to recover information

➢ Virus • It is software attached to other software which has the ability to self-

replicate • The user need to perform an action in order to activate it

➢ Worms • It is software which replicates itself without attaching to any other

software • Usually attack operating systems’ vulnerabilities through the

network or portable media

Cyber Threats

68

Information Technology & Data Analytics

Ransomware

69Wordfence

Information Technology & Data Analytics

Security

70

Information Technology & Data Analytics

➢ Attacks on information and computer resources come from inside and outside the company

➢ Computer sabotage costs about $10 billion per year

➢ In general, employee misconduct is more costly than assaults from outside

SECURITY AND EMPLOYEES

71

Information Technology & Data Analytics

Security and Employees

72

Information Technology & Data Analytics

➢ Hackers – • knowledgeable computer users who invade other people's

computers

➢ Denial-of-service (DoS) attack • floods a Web site with so many requests for service that it slows

down or crashes • Distributed DoS Attack DDoS – Many systems attack a single target.

It is very hard to stop

➢ Brute force attack • attacks based on trial an error, as opposed to expert attacks • Dictionary attack

oTries to gain access to a password by using the most common ones, based on a dictionary

Security and Outside Threats

73

Information Technology & Data Analytics

Worst Passwords 2020

74NordPass: Worst Passwords 2020

Information Technology & Data Analytics

Social Engineering

75Social Engineering Scams: MediaPro Security Awareness Animation

➢ Manipulating people to do something or to share confidential information

Information Technology & Data Analytics

How Safe Are You?

76Source: My Credit Karma Report

Information Technology & Data Analytics

➢ Anti-virus software – detects and removes or quarantines computer viruses • McAfee, Norton, Avast, AVG

➢ Anti-spyware and anti-adware software – detects and remove spyware, software and malware • AdAware Ad-block, CCleaner

➢ Spam protection software – identifies and marks and/or deletes Spam • Most corporations and web based e-mail servers have improved

their spam filters • E-mail filters can assist with this task • SPAMfighter, Mailwasher

➢ Anti-phishing software – lets you know when phishing attempts are being made • Email clients and many web browsers have this software integrated

Security Measures

77

Information Technology & Data Analytics

➢ Firewall

• Protects a computer or network from intruders.

• Software based: Windows, McAfee, Norton

• Hardware based: Usually installed in network equipment, standalone or as part of a router

• DMZ

Security Measures

78Hardware Expert

Information Technology & Data Analytics

➢ DMZ - Demilitarized zone

Firewall with DMZ

79Stack Exchange

Information Technology & Data Analytics

➢ Vulnerability Patching • Installing software packages known as patches to proactively

prevent or reactively remediate an issue

➢ Ethical Hacking • Testing system vulnerabilities to prevent attacks • Penetration testing

➢ Awareness and Training • Key to prevent attacks, as many have their inception at users’ hands

➢ Security Policies • Specify how to protect the organization from threats

Security Measures

80

Information Technology & Data Analytics

➢ Security Policies – including, but not limited to:

• Information Technology Security Policy

• General Security Policy

• Acceptable Use Policy

• Access Control Policy

• Management Security Policy

• Password Security Policy

• Encryption Security Policy

• Data Retention Policy

• Email Security Policy

• Media Disposal Policy

Security Measures

81

Information Technology & Data Analytics

➢ Two-factor authentication (2FA) – Uses a second method of identification in addition to the username and password. It can be:

• A hardware or virtual token which generates random codes

• A code sent via e-mail

• SMS, or app authentication through a mobile device

Security Measures

82Banamex

Information Technology & Data Analytics

➢ Anti-rootkit software • stops outsiders taking control of your machine

oGMER, RootRepeal, Malwarebytes, Rootkit Hunter

➢ Encryption • scrambles the contents of a file so that you can’t read it without

the decryption key

➢ Public Key Encryption (PKE) • an encryption system with two keys: a public for everyone and a

private one for the recipient

➢ Biometrics • the use of physiological characteristics for identification

purposes

Security Measures

83

Information Technology & Data Analytics

➢ AI Surveillance

• Both in technology and the workplace

➢ Next Generation Firewalls

• These Cisco videos provide good insight on these new trend

➢ Cloud Security

• Palo Alto networks is one of the most important vendors

➢ Security as a Service

• FWaaS – Firewall as a Service

• CSaaS – Cyber Security as a Service

New Security Measures?

84

Questions?

Thank you!