Dark Reading is part of the Informa Tech Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them.Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.

IoT
3/1/2018
04:45 PM
Connect Directly
Twitter
LinkedIn
Google+
RSS
E-Mail
50%
50%

Securing the Web of Wearables, Smartphones & Cloud

Why security for the Internet of Things demands that businesses revamp their software development lifecycle.

Wearables are only a small part of the Internet of Things (IoT), a complicated mesh of smart devices, mobile phones, and several applications working together in a digital ecosystem.

The IoT "user experience" is a product of interactions between wearables, smartphones, and applications and analytics software hosted in the cloud. Securing this web of hardware and software is a tricky challenge for companies accelerating into the IoT, an environment that didn't exist until a few years ago, says Deep Armor founder and CEO Sumanth Naropanth.

"What we're seeing industry-wide is that this class of products is somewhat initiating a paradigm shift in the entire security development lifecycle," he explains. "[Businesses] are now responsible for changing the old security development lifecycle (SDL) frameworks and best practices into something more agile."

At this year's Black Hat Asia, taking place March 23–26 in Singapore, Naropanth will discuss security and privacy research related to the development of IoT devices, including a custom SDL designed to incorporate wearables, phones, and the cloud. The session will elaborate on flaws and privacy issues related to IoT, and best practices for building new connected products.

[Learn more about the IoT security shift in Black Hat Asia session "Securing Your In-Ear Fitness Coach: Challenges in Hardening Next Generation Wearables," in which Naropanth will discuss gaps in IoT security and necessary changes to the software development lifecycle.]

Sumanth says it's time for businesses to think about the bigger picture and secure the broader IoT ecosystem rather than getting bogged down with ingredient-level IoT security. This means not only securing individual devices but the software and services connecting them.

"Looking at a fitness tracker or IoT device, what you see is really not everything that exists," he explains. "It's like the tip of the iceberg." Behind the small activity monitor on your wrist is an array of APIs, Web portals, cloud services, and more often than not, a mobile application.

Speed vs. Security
Businesses in the IoT market are learning how to be more agile, Naropanth explains. This is especially relevant to startups, which often view security as an "expense without returns."

This isn't true when in wearables and IoT. Now companies are worried about things like securing the hardware, doing secure boot, updating mobile phones securely, and doing crypto on a very limited IoT software stack — all before launching their products before anyone else. Most enterprises working on IoT and wearables are actually taking it seriously, he adds.

"The challenge for them is more about how to balance their time to market with adequate enough security so the product is at least reasonably secure when it goes out the door," Naropanth says.

A key component of this updated SDL is evaluating the ecosystem. Your company may be building a fitness tracker that has to work with Wi-Fi, Bluetooth, or a cloud-based component someone else has developed. It's your job to navigate the interoperability challenges related to the hardware and software connecting to the wearable.

Developing for the IoT: What to Keep in Mind
Sumanth explains two best practices for IoT businesses to prioritize as they create and connect new products. The first: getting the security and product teams on the same page.

"Catching security weaknesses earlier and earlier in the product lifecycle — it helps everyone," he says. "For the company and for the enterprise, it saves a lot of money." It's better to catch security weaknesses early than when code is about to ship. If errors are found later on, a larger team is needed to address the problem," he adds.

"We strongly encourage product teams to engage with the security team early in the process. It helps us find the weaknesses early on and reduce the number of bugs that get caught later."

Naropanth also recommends IoT developers to look at existing vulnerabilities from an IoT point of view. Often, old flaws can have a "butterfly effect" in the IoT and lead to wearable devices getting bricked. Furthermore, vulnerabilities in some parts of the IoT — for example, a smartphone — can affect other connected devices.

Related Content:

 

 

 

Black Hat Asia returns to Singapore with hands-on technical Trainings, cutting-edge Briefings, Arsenal open-source tool demonstrations, top-tier solutions and service providers in the Business Hall. Click for information on the conference and to register.

Kelly Sheridan is the Staff Editor at Dark Reading, where she focuses on cybersecurity news and analysis. She is a business technology journalist who previously reported for InformationWeek, where she covered Microsoft, and Insurance & Technology, where she covered financial ... View Full Bio
 

Recommended Reading:

Comment  | 
Print  | 
More Insights
Comments
Newest First  |  Oldest First  |  Threaded View
COVID-19: Latest Security News & Commentary
Dark Reading Staff 9/25/2020
Hacking Yourself: Marie Moe and Pacemaker Security
Gary McGraw Ph.D., Co-founder Berryville Institute of Machine Learning,  9/21/2020
Startup Aims to Map and Track All the IT and Security Things
Kelly Jackson Higgins, Executive Editor at Dark Reading,  9/22/2020
Register for Dark Reading Newsletters
White Papers
Video
Cartoon
Current Issue
Special Report: Computing's New Normal
This special report examines how IT security organizations have adapted to the "new normal" of computing and what the long-term effects will be. Read it and get a unique set of perspectives on issues ranging from new threats & vulnerabilities as a result of remote working to how enterprise security strategy will be affected long term.
Flash Poll
How IT Security Organizations are Attacking the Cybersecurity Problem
How IT Security Organizations are Attacking the Cybersecurity Problem
The COVID-19 pandemic turned the world -- and enterprise computing -- on end. Here's a look at how cybersecurity teams are retrenching their defense strategies, rebuilding their teams, and selecting new technologies to stop the oncoming rise of online attacks.
Twitter Feed
Dark Reading - Bug Report
Bug Report
Enterprise Vulnerabilities
From DHS/US-CERT's National Vulnerability Database
CVE-2020-15208
PUBLISHED: 2020-09-25
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can ...
CVE-2020-15209
PUBLISHED: 2020-09-25
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, a crafted TFLite model can force a node to have as input a tensor backed by a `nullptr` buffer. This can be achieved by changing a buffer index in the flatbuffer serialization to convert a read-only tensor to a read-write one....
CVE-2020-15210
PUBLISHED: 2020-09-25
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and ...
CVE-2020-15211
PUBLISHED: 2020-09-25
In TensorFlow Lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, saved models in the flatbuffer format use a double indexing scheme: a model has a set of subgraphs, each subgraph has a set of operators and each operator has a set of input/output tensors. The flatbuffer format uses indices f...
CVE-2020-15212
PUBLISHED: 2020-09-25
In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger writes outside of bounds of heap allocated buffers by inserting negative elements in the segment ids tensor. Users having access to `segment_ids_data` can alter `output_index` and then write to outside of `outpu...