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IoT (D)DoS prevention and corporate responsibility A model to prevent internet pollution and liability claims alike S. Scholtes June 7, 2019 Research Project 2 Master of System and Network Engineering Institute of Informatics University of

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IoT (D)DoS prevention and corporate responsibility

A model to prevent internet pollution and liability claims alike

  • S. Scholtes

June 7, 2019

Research Project 2 Master of System and Network Engineering Institute of Informatics University of Amsterdam

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Outline

  • Motivation
  • Growth aspects
  • Legislative developments
  • Related work
  • Research question
  • Model
  • Conclusion
  • Discussion
  • Future work

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Introduction

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Motivation (D)DoS & IoT growth

(D)DoS attacks: [5] [4]

  • 1. 620Gbps attack - 20 September 2016 on KrebsOnSecurity.com.
  • 2. 990Gbps attack - 22 September 2016 on hosting provider OVH.
  • 3. 1.2Tbps attack - October 2016 on DNS provider Dyn.
  • 4. 1.3Tbps attack - February 2018 on on Github.
  • 5. 1.7Tbps (alleged) - February 2018, victim undisclosed.

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Motivation (D)DoS & IoT growth

(D)DoS attacks: [5] [4]

  • 1. 620Gbps attack - 20 September 2016 on KrebsOnSecurity.com.
  • 2. 990Gbps attack - 22 September 2016 on hosting provider OVH.
  • 3. 1.2Tbps attack - October 2016 on DNS provider Dyn.
  • 4. 1.3Tbps attack - February 2018 on on Github.
  • 5. 1.7Tbps (alleged) - February 2018, victim undisclosed.

IoT growth: [8]

  • 1. 2019 - 14.2 billion ”things” in use.
  • 2. 2021 - 25 billion ”things” in use.
  • 3. 76.05% growth in 2 years.

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Legislative (international)

Viktor Vitowsky: [14]

  • 1. Make IoT manufacturers liable based on section 5 from the Federal

Trade Commission (FTC).

  • 2. Businesses damaged by IoT launched DDoS attacks could bring civil

claims. Senator Mark R. Warner asked the Federal Communications Commission (FCC): [15]

  • 1. Internet Service Provider (ISP) policing.
  • 2. Minimum technical security standards defined by the FCC.

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Legislative (national)

House of representatives asked the Ministry of Justice and Security: [9]

  • 1. Develop a quality mark or control stamp
  • 2. internet service providers (ISP) and telecommunication companies

have enough capabilities to detect insecure IoT devices.

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Research question

How can organisations prevent contributing to Internet of Things denial of service attacks?

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Research question

How can organisations prevent contributing to Internet of Things denial of service attacks?

  • 1. Detection methods

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Research question

How can organisations prevent contributing to Internet of Things denial of service attacks?

  • 1. Detection methods
  • 2. Prevention methods

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Research question

How can organisations prevent contributing to Internet of Things denial of service attacks?

  • 1. Detection methods
  • 2. Prevention methods
  • 3. Minimise contribution

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Related Work

  • Muhammad UmarFarooq et al. and Antoine Gallais et al. list

different IoT security attacks [6] [7].

  • Mukrimah Nawir et al. shows the taxonomy of attacks in IoT

environments [12].

  • Elike Hodo et al. uses an artificial neural network to detect threats

in an IoT environment [10].

  • Andria Procopiou et al. developed ”ForChaos” which detects denial
  • f service attacks using forecasting and chaos theory [13].
  • Daniel Jeswin Nallathambi et al. use honeypots to mitigate denial of

service attacks in IoT environments [2]

  • A blockchain mitigation solution is presented by Minhaj Ahmad

Khan et al. [11].

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Model

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IoT architecture

Figure 1: IoT architecture (Adapted from: [3][6][1])

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IoT defensive layers

Figure 2: IoT defensive layers

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Module overview

Figure 3: Module overview

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(D)DoS Detection Module (DDM)

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(D)DoS Detection Module (DDM) logic

Figure 4: Detection methods

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(D)DoS Detection Module (DDM) logic

Figure 5: Anomaly logic

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(D)DoS Detection Module (DDM) logic

Figure 6: Threshold detection

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(D)DoS Detection Module (DDM) logic

Figure 7: Signature detection

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(D)DoS Detection Module (DDM) logic

Figure 8: Statistic collector

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Control Module (CM)

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Control Module (CM) logic

Figure 9: Statistic extractor

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Control Module (CM) logic

Figure 10: Threat analyser

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Control Module (CM) logic

Figure 11: Lower modules information pass-through

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Mitigation Decision Module (MDM)

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Mitigation Decision Module (MDM) logic

Figure 12: Emergency ACL

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Mitigation Decision Module (MDM) logic

Figure 13: IoT controller update push check

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Mitigation Decision Module (MDM) logic

Figure 14: IoT controller update push check

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Mitigation Decision Module (MDM) logic

Figure 15: Reporting implemented mitigation solutions

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Mitigation Decision Module (MDM) logic

Figure 16: Reporting lower module information

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Update Module (UM)

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UM logic

Figure 17: IoT controller firmware check

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Update Module (UM) logic

Figure 18: IoT controller software check

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Update Module (UM) logic

Figure 19: IoT controller configuration check

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Update Module (UM) logic

Figure 20: IoT controller access control list check

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Report Module (RM)

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Report Module (RM) logic

Figure 21: Statistic extractor

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Report Module (RM) logic

Figure 22: Maintenance ID reporting and extracting

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Asset Management Module (AMM)

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Asset Management Module (AMM) logic

Figure 23: Manufacturers and deployment

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Asset Management Module (AMM) logic

Figure 24: Previously in maintenance check

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Asset Management Module (AMM) logic

Figure 25: Same error check

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Asset Management Module (AMM) logic

Figure 26: Error threshold check

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Asset Management Module (AMM) logic

Figure 27: Error threshold check

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IoT architecture with added modules

Figure 28: Modules within the IoT architecture

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Conclusion, Discussion & Future Work

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Conclusion

How can organisations prevent contributing to Internet of Things denial of service attacks?

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Discussion

  • Model applicability dependent on used IoT architecture.
  • Module to device translation.
  • High likely hood of availability (detection and mitigation).
  • Access control list side effects.
  • Layer 3 attributes.
  • External influences effecting the design.

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Future Work

  • Proof of concept (measure performance)
  • 1. DDM detection methods
  • 2. DDM traffic sampling rate
  • 3. RM databases
  • 4. CM threat logic
  • Applicable hardware setups
  • Include object defensive layer
  • Threat level matrix guidelines.

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References i

Vipindev Adat and BB Gupta. “Security in Internet of Things: issues, challenges, taxonomy, and architecture”. In: Telecommunication Systems 67.3 (2018), pp. 423–441. M Anirudh, S Arul Thileeban, and Daniel Jeswin Nallathambi. “Use

  • f honeypots for mitigating DoS attacks targeted on IoT networks”.

In: 2017 International Conference on Computer, Communication and Signal Processing (ICCCSP). IEEE. 2017, pp. 1–4. Armir Bujari et al. “Standards, security and business models: key challenges for the IoT scenario”. In: Mobile Networks and Applications 23.1 (2018), pp. 147–154.

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References ii

  • Cloudflare. Famous DDoS Attacks — The Largest DDoS Attacks

Of All Time. 2018 (accessed May 12, 2019). url: https://www.cloudflare.com/learning/ddos/famous-ddos- attacks/.

  • enisa. Major DDoS Attacks Involving IoT Devices. 2016 (accessed

May 11, 2019). url: https://www.enisa.europa.eu/publications/info- notes/major-ddos-attacks-involving-iot-devices. Mario Frustaci et al. “Evaluating critical security issues of the IoT world: Present and Future challenges”. In: IEEE Internet of Things Journal 5.4 (2018), pp. 2483–2495. Antoine Gallais et al. “Denial-of-Sleep Attacks against IoT Networks”. In: International Conference on Control, Decision and Information Technologies (CoDIT). 2019.

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References iii

  • Gartner. Gartner Identifies Top 10 Strategic IoT Technologies and
  • Trends. 2018 (accessed May 13, 2019). url:

hhttps://www.gartner.com/en/newsroom/press- releases/2018-11-07-gartner-identifies-top-10- strategic-iot-technologies-and-trends. Het bericht ’Agentschap Telecom slaat alarm over hackbare apparaten’. url: https://www.tweedekamer.nl/kamerstukken/kamervragen/ detail?id=2018Z10731&did=2018D32722. Elike Hodo et al. “Threat analysis of IoT networks using artificial neural network intrusion detection system”. In: 2016 International Symposium on Networks, Computers and Communications (ISNCC). IEEE. 2016, pp. 1–6.

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References iv

Minhaj Ahmad Khan and Khaled Salah. “IoT security: Review, blockchain solutions, and open challenges”. In: Future Generation Computer Systems 82 (2018), pp. 395–411. Mukrimah Nawir et al. “Internet of Things (IoT): Taxonomy of security attacks”. In: 2016 3rd International Conference on Electronic Design (ICED). IEEE. 2016, pp. 321–326. Andria Procopiou, Nikos Komninos, and Christos Douligeris. “ForChaos: Real Time Application DDoS Detection Using Forecasting and Chaos Theory in Smart Home IoT Network”. In: Wireless Communications and Mobile Computing 2019 (2019). Vincent J. Vitkowsky. “The internet of things: A new era of cyber liability and insurance”. In: (2015).

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References v

Mark R. Warner. Sen. Mark Warner Probes Friday;s Crippling Cyber Attack. 2016 (accessed May 14, 2019). url: https://www.warner.senate.gov/public/index.cfm/ pressreleases?ContentRecord_id=CD1BBB25-83E0-494D- B7E1-1C350A7CFCCA.

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Questions?

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Additional slides: DDM

Figure 29: DDM overview

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Additional slides: CM

Figure 30: CM overview

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Additional slides: MDM

Figure 31: MDM overview

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Additional slides: UM

Figure 32: UM overview

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Additional slides: RM

Figure 33: RM overview

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Additional slides: AMM

Figure 34: AMM overview

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