Overview of IoT and Security issues

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• Introduction to IoT & Market • Smart Applications • Technology & Research Challenges • Security Threats • Wireless Sensor Network Security • Security Visualization • Conclusions

Outline of the Presentation

CTTC 2015 seminar by Prof. A.A. Economides 2

Introduction to Internet of Things (IoT)

3 CTTC 2015 seminar by Prof. A.A. Economides

2020 forecast :

• 25 - 50 billion devices (Cisco, Ericsson, IDC, ABI, Gartner)

• 26 objects/ person (Intel)

• Economic impact: $ 2 - 5 trillion (Cisco, McKinsey Global Institute,

IDC, GSMA & Machina Research, Gartner, Harbor)

“Worldwide ICT infrastructure that enables ubiquitous services among interacting humans, machines, data and applications”

75% of companies are already exploring the IoT. 15 % of companies already have an IoT solution in place (21 % of transportation & logistics companies) 53 % plan to implement one within the next 24 months,

and another 14 % in the next two to five years.

(source: Zebra Technologies / Forrester Consulting).

IoT deployment


Cisco predicts that IoT will cause IP traffic to reach 1.6 zettabytes by 2018 (300% increase compared to 2013). By 2018, 57% of IP traffic will come from devices other than PCs. Wi-Fi will generate 49% of IP traffic, other mobile-connected devices will generate 12% of it. Cisco will invest $1 billion to build the world's largest

Intercloud network to tackle the IoT.

Cisco plans an Intercloud network


http://www.techradar.com/us/news/internet/cloud-services/cisco-investing-1bn-in-cloud-network-for-internet-of-everything-1236428

Healthcare & Wellbeing, e.g. Angel Sensor, Fitbit, Hexoskin, Intraway, Jawbone, Nymi, InKol Health Hub, Pebble, Philips Lifeline, Withings, Zebra MotionWorks,

Home & Building, e.g. Belkin, Nest, Neurio, Quirky, Sensorflare, SMA, SmartThings, Vivint, WallyHome, Withings, ZEN Thermostat,

City & Community, e.g. Bigbelly, Bitlock¸ FUKUSHIMA Wheel, Kiunsys, Placemeter,

Silver Spring Networks, Waspmote, Utilities, e.g. Enevo, Mayflower CMS, MeterNet, Osprey Informatics, Paradox,

Trilliant, Environment, Agriculture & Livestock, e.g. FilesThruTheAir, Fruition Sciences,

OnFarm, Semios, Topcon Precision Agriculture, Car & Transportation, e.g. Audi, CarKnow, Connected Rail, Dash drive smart, Delphi

Connect, Ericsson, Libelium, Logitrac, PowerFleet, Industry & Services, e.g. Argon Underground Mining Safety, Condeco Sense,

DAQRI’s Smart Helmet, Numerex, Perch.

Smart Applications


83 projects across 12 areas: sensors monitor traffic, parking spaces, street lights, air pollution, meteorological conditions, humidity of green spaces in parks, trash bins ...

Street lights in Born are shut down automatically if they don’t detect

any activity nearby. They also monitor humidity, temperature, pollution, and noise. Expected to have 3,360 lights on 160 streets by 2015.

The trash cans alert sanitation workers on a tablet that they need to

be emptied.

The irrigation systems in Poblenou Central Park monitor the moisture in the soil and turning on pop-up sprinklers. Parks employees can also access meteorological data and rain gauges and adjust the quantity of water used.

Barcelona Smart City


Technology


Sensors & Actuators

Wireless Communications: RFID, WiFi, Bluetooth, Cellular, Satellite, etc.

Cloud Computing – Storage, Processing, Analytics, Security, etc.

Networks (HW & SW)

Addressing

Application/Data Layer

Transport Layer

NWK Layer

DataLink Layer

PHY Layer

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3G

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RFI

D/N

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IPv6

TCP

HTTP CoAP

RPL

6LoWPAN

TCP/UDP

Application 1 Application 2 Application N ° ° ° °

ONEM2M/ETSI M2M Service Layer

CTTC 2015 seminar by Prof. A.A. Economides

Source: IoT-Butler.eu

• AllSeen Alliance • Eclipse Foundation • Industrial Internet Consortium • Internet of Things Consortium • Internet Protocol for Smart Objects (IPSO) Alliance • IoT Alliance • Oasis • OneM2M • Open Interconnect Consortium (OIC) • Thread Group • ZigBee Alliance

IoT Alliances



Source: D.Culler (2011). The Internet of Every Thing - steps toward sustainability. CWSN.

http://www.cs.berkeley.edu/~culler/

Devices (Sensors, Actuators, etc.), Networking & Communications, Data Management, Decision Making, Security & Privacy, Social & Legal issues, Economics, Human Behavior & Usability, Marketing, etc.

Research Challenges


#1 New threats to data / physical security (42 % responders) #2 Inability of IT systems to keep pace with change

(38 % responders) #3 Regulatory or compliance challenges (32 % responders)

Biggest Drawbacks of IoT (Cisco survey)


The Center for Strategic and International Studies estimated that $100 billion is lost annually to the US economy, and 508,000 US jobs are lost, because of malicious online activity.

Ponemon Institute estimated that the average cost of an organizational data breach was $5.4 million in 2014 ($4.5 million in 2013).

Losses due to attacks


Nearly half (46%) of the IT leaders said that they will invest more next year in: access control,

intrusion prevention,

identity management, virus and malware protection.

ComputerWorld Survey


M2M Network Security market will grow at a CAGR

of 22.9 % over the period 2013-2018 (TechNavio)

IoT and Industrial Security Market to exceed $ 675 million by 2018 (Infonetics)

Network Security market


What do you think the greatest threat IoT will be over the next 5 years?


source: SANS survey

Where do you consider the greatest risk to be in “Things” connecting to your network and the Internet?


source: SANS survey

Given the current state of your security program, how would you rate your ability to provide security to IoT ?


source: SANS survey

• 25 % - 50 % of remote workers and IT personnel who work remotely in critical infrastructure industries report that they have at least one IoT device connected to corporate networks.

• 75 % admit to accessing corporate documents from their home networks.

• only 30 % of IT professionals believe their company has the

technology necessary to adequately evaluate the security of IoT devices,

• 59 % of IT personnel are concerned that IoT could become “the most significant security risk on their network.”

• 20 % of respondents state that they have “no visibility” into current protection levels.

Tripwire & AtomicResearch surveys


Chief Information Security Officers and Security Operations executives at 1700 companies in nine countries (2015):

• Only 10% of Internet Explorer users run the latest version.

• Less than 50% of respondents use standard tools

such as patching and configuration to help prevent security breaches and ensure that they are running the latest versions.

Cisco Security Capabilities Benchmark


• 6 out of the 10 popular IoT devices did not use encryption when downloading software updates.

• 90 % of the devices collected at least one piece of

personal information via the device, the cloud, or its mobile application.

• 70 % of the devices used unencrypted network

service and transmitted credentials in plain text.

Hewllet Packard tested 10 IoT devices


1. Insecure web interface 2. Insufficient authentication 3. Insecure network services 4. Lack of transport encryptions 5. Privacy concerns 6. Insecure cloud interface 7. Insecure mobile interface 8. Insufficient security configurability 9. Insecure software 10. Poor physical security OWASP

Top 10 security problems with IoT devices


Avast: Routers will be a prime target for hackers. Hackers may want to take over the local network. WatchGuard: - criminals stealing billions in digital assets, - nation states launching long-term attacks. NOT to worry about IoT security (for now): NOT much value attacking your watch or TV. Symantec: Attacks on IoT will focus on smart home. NOT expect any large-scale attacks, but instead one-off attacks against connected devices, e.g.

home routers, smart TVs & connected car apps.

Security predictions for 2015


A wireless network consisting of a large number of autonomous sensors that are spatially distributed in area of interest in order to cooperatively monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion, pollutants, etc.

Sensor:

Wireless Sensor Network (WSN)


Sensors

ADC

Processor

Memory Transceiver

Location finding system (optional)

Mobilizer (optional)

Sensing Unit Processing Unit

Power unit

Communication Unit

WSN Architecture


Internet, Satellite

Sink

Sink

Task Manager

User

Sensor Field

Sensor Node

Figure – The big picture

WSNs are vulnerable to various types of attacks

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CTTC 2015 seminar by Prof. A.A. Economides

Internet, Satellite

Sink

Sink

Task Manager

User

Sensor Field

Sensor Node

Spoofed Routing

information

Wormhole Attack

Eavesdropping: an attacker intercepts packets transmitted over the air for further cryptanalysis or traffic analysis.

Traffic analysis: allows an attacker to determine that there is activity in the network, the location of the BSs, and the type of protocols being used.

Message injection: an adversary injects bogus control information into the data stream.

Message modification: a previously captured message is modified before being retransmitted

Node capture: An embedded device is considered being compromised when an attacker, through various means, gains control to the node itself.

Denial-of-Service (DoS) attacks: can be grouped into two categories

Service degradation (e.g., collision attack), and

Service disablement through power exhaustion (e.g. jamming)

Attack Models


Pas

sive

att

acks

A

ctiv

e at

tack

s

Layer-based attack categorization


Application Layer

Transport Layer

Network Layer

Data Link Layer

Physical Layer

Flooding Attack | Desynchronization attacks

Replay Attack | Sybil Attack | Spoofed, altered, or replayed routing information | Sinkhole, Wormhole Attack | Hello Flood Attack

Collision Attack | Sybil Attack | Node Replication | Acknowledgement Spoofing Attack

Eavesdropping | Jamming | Battery Exhaustion

Po

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Data Aggregation Distortion | Message Injection or Modification

Figure – Sensor Network Protocol Stack

Attacks on specific protocols

Selective forwarding: A malicious node refuses to forward all or a subset of the packets it receives and simply drops them. If a malicious node drops all the packets, the attack is then called black hole.


Acknowledgement spoofing: Spoof link layer acknowledgements (ACKs) to trick other nodes to believe that a link or node is either dead or alive.

Attack against TinyOS beaconing: The base station periodically broadcasts beacons or “route updates”. An attacker can use this mechanism to create routing loops by announcing a different node as the BS.

Figure- Attack against TinyOS beaconing

Spoofed, altered, or replayed routing information


This type of attack may be used for:

loop construction

attracting or repelling traffic,

extending or shortening the source route

In this example, an adversary pollutes the entire network by sending bogus routing information stating for instance that “I am the base station”.

Figure - An adversary spoofing a routing update from a base station

Wormhole and Sinkhole Attacks

The attacker uses two transceivers and one high quality out-of-band channel in order to create a ‘wormhole’.

Then, the attacker tunnels the

packets received at one location of the network and replays them in another location.

The wormhole can drop packets

directly (sinkhole) or more subtly selectively forward packets to avoid detection.


Wormhole link

Figure - A laptop-class adversary using a wormhole to create a sinkhole in TinyOS beaconing.

HELLO Flood Attack


Every new node broadcasts “Hello messages” to find its neighbors. Also, it broadcasts its route to the BS.

Other nodes may choose to route data through this new node if the path is shorter.

A laptop-class adversary that can retransmit a routing update with enough power to be received by the entire network leaves many nodes stranded.

Target nodes attempt to reply, but the adversary node is out of radio range. However, they have chosen this node as their parent

This attack puts the network in a state of confusion.

Figure - HELLO flood attack.

Sybil Attack

“a malicious node

illegitimately claims

multiple identities”

The Sybil attack can

disrupt geographic and

multi-path routing

protocols.

36

Adversary A at actual location (3,2) forges location advertisements for non-existent nodes A1, A2, and A3 as well as advertising her own location. After hearing these advertisements, if B wants to send a message to C: (0,2), it will attempt to do so through A3. This transmission can be overheard and handled by the adversary A.

Confidentiality is provided through the use of encryption technologies.

Cryptographic algorithms such as the DES, RC5, RSA are used to protect the secrecy of a message.

MAC (Message Authentication Code) or Digital Signature Algorithms (DSA) can be used to assure the recipient’s integrity of the data and authenticity of the message

Digital Signatures can be used to ensure non-repudiation.

Availability can be achieved by adding redundant nodes. Multi path and probabilistic routing can also be used to minimize the impact of unavailability.

Data freshness is ensured by adding a counter value in each message.

Overview of Countermeasures


• SNEP (Secure Network Encryption Protocol)

• μTESLA

• TinySec 1. authenticated encryption (TinySec-AE)

Data payload is encrypted MAC is used to authenticate packet

2. authentication only (TinySec-Auth)

Standalone Security Protocols for WSNs


A summary of attacks against routing protocols


Protocol Relevant Attacks

Directed diffusion and its multipath variants

Bogus routing information, selective forwarding,

sinkholes, Sybil attack, wormholes, HELLO floods

Geographic routing (GPSR, GEAR) Bogus routing information, selective forwarding, Sybil attack

Minimum cost forwarding Bogus routing information, selective forwarding,

sinkholes, wormholes, HELLO floods

Clustering-based protocols (LEACH, TEEN, PEGASIS)

Selective forwarding, HELLO floods

Rumor routing Bogus routing information, selective forwarding, sinkholes, Sybil, wormholes

Energy conserving topology maintenance (SPAN, GAF, CEC, AFECA)

Bogus routing information, Sybil attack, HELLO floods

• Link layer security

– Simple link layer encryption and authentication using a globally shared key can prevent the majority of outsider attacks: bogus routing information, Sybil, Selective Forwarding, Sinkholes.

– Link layer security mechanisms provide little protection against insiders, HELLO floods, and Wormholes.

• Wormhole and sinkhole attacks

– Routing protocols that construct a topology initiated by a base station are the most vulnerable against these types of attacks.

Solution: Geographic protocols that construct topology on demand using localized node interactions instead of using the base station.

Secure Routing – Countermeasures


• Various security mechanisms have been proposed to address the security concerns of WSNs.

• Despite the fast development of computer security mechanisms, the scale and complexity of the generated wireless data put major challenges to the representation and understanding of security-relevant network information.

• To address this issue, efficient visualization techniques have been adopted by the researchers to bridge the gap.

A new security discipline emerges!

Network Security Visualization


• Network traffic visualization is one of the first directions to take when it comes to understanding, and analyzing information in vast amounts of network data.

• Many visualization tools graphically monitor real-world or simulated

WSNs (e.g. Surge, MoteView, Octopus, SNA, TOSSIM, OPNET, NS-3).

• While these tools offer some form of visualization, they are designed for

applications other than wireless security. Accordingly, these tools:

– lack the specialized techniques in visualizing security-related data.

– tend to miss abnormalities and security attacks that occur unpredictably.

Until now…Visualization only for network traffic monitoring


The power of visualization should go beyond the simple ”illustration” of network behavior in order to help the analysts discriminate between normal and abnormal network activities.

Network security visualization provides insight into areas that other system fail to enlighten by integrating visualization and machine learning techniques.

In the near future… Visualization for network security


Security Visualization Techniques


Node Links

Glyphs

Parallel Coordinates

Bundle Diagrams

Radial Panels

IoT enables dramatic society transformation!

IoT Security is at risk!

WSN Security challenge!

Conclusions


[email protected]

http://conta.uom.gr




http://conta.uom.gr/

Overview of IoT and Security issues

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