IoT Medical Devices Security Vulnerabilities on Wi-Fi Networks
IoT medical devices security vulnerabilities affects many different types of in-hospital equipment including diagnostic equipment (e.g., MRI (Magnetic Resonance Imaging) machines and CT (Computerized axial Tomography) scanners), therapeutic equipment (e.g., infusion pumps and medical lasers) life support equipment (e.g., heart support machines), internet-connected devices for monitoring patients vital signs (e.g., thermometers, glucometers, blood pressure cuffs, wearables), as well as novel, intelligent and disruptive devices which can keep track of medication schedules (e.g., GlowCap outlets and AdhereTech wireless pills).
The Internet-of-Things (IoT) is gradually realizing a radical transformation of healthcare services based on the deployment of numerous medical devices, which already represent a considerable segment of the billions of internet-connected devices that are nowadays available.
These devices are used in conjunction with mobile terminals (e.g., tablet computers, smart phones) which enable health professionals both to configure them and to visualize their data. Moreover, several IoT applications integrate RFID tags, as a means of uniquely identifying and associating with each other devices, patients, doctors, drugs, prescriptions and other artifacts engaging in the care service provisioning process. While several of the above listed devices can be deployed in the patients’ homes, the majority of them are deployed in the hospital environment.
In principle, IoT technologies enable the processing of data and the orchestration of services from all these devices in order to facilitate health professionals to access accurate and timely information about the patients’ status, but also to configure disease management processes for prognosis, diagnosis and treatment. Beyond disease management, the deployment of IoT medical devices security in the hospital can be also used to boost the efficiency of hospital operations.
As a prominent example, the continuous monitoring of IoT medical devices security can serve as basis for reducing their downtime. Likewise, devices emit notifications that can trigger proactive maintenance and replenishment of supplies. Furthermore, information from medical devices can be exploited in order to optimize resources utilization and patient scheduling. Based on these processes, healthcare will become a setting that will annually contribute over $1 trillion to IoT’s business value by 2030, as projected by a recent report of McKinsey Global Institute.
IoT Medical Devices Security Risks
The expanded use of IoT medical devices in hospitals raises serious privacy and security challenges, given the proclaimed and widespread vulnerabilities of wireless devices. IoT medical devices security vulnerabilities has always been a concern for applications, but in the case of healthcare it is a matter of life and death. Indeed, beyond compromising patient’s data confidentiality, security vulnerabilities can have life-threatening implications, as IoT devices are used to control medication or even to drive surgical interventions and other therapeutic processes.
Since commands to several devices are transmitted wirelessly, hackers can invade the wireless network in order to gain control over devices and transmit unauthorized commands with fatal results. For instance, a malicious attack against an insulin pump can lead to a wrong dose to a diabetes patient. As another example, the hacking of an electrical cardioversion device could instigate an unnecessary shock to a patient.
There is a host of different IoT medical devices security vulnerabilities easily include a non exhaustive list of common attacks includes:
- Password hacking: It is quite common for medical devices to be protected by weak passwords that can be hacked. This is the case when the built-in passwords provided by the device vendors are maintained.
Hackers can easily discover such passwords in order to gain access to device configuration information. Moreover, in several cases, hackers are also able to control the device and use it to launch more advanced attacks.
Poor Security Patching: Some medical devices are poorly patched, either because some patch has not yet been deployed on the device or because the device runs an “old” operating system (e.g., an older version of Windows or Linux). Poorly patched devices are vulnerable to malware and other attacks, which makes them an easy target for hackers.
Wi-Fi: The weak link in IoT Medical Devices Security Vulnerabilities
Denial of service attacks: Medical devices are usually lightweight and resource constrained, which makes them susceptible to denial of service attacks. The transmission of simultaneous requests to the device can cause it to stop, disconnect from the network or even become out of order.
Unencrypted data transmission: It’s quite usual for attackers to monitor the network in order to eavesdrop and steal passwords. The transmission of unencrypted data can therefore ease their efforts to gain access to the device in order either to extract information or even exploit the device for transmitting malicious commands.
IoT medical devices security is serious business, as most of the medical devices are Wi-Fi enabled, which renders Wi-Fi the technology that carries the vast majority of the traffic that is exchanged between medical devices. However, Wi-Fi networks are conspicuously associated with IoT Medical Devices security vulnerabilities , which make them the weak link. For example, the WEP (Wireless Encryption Password) mechanisms that empower Wi-Fi security are weak, as WEP passwords can be easily stolen.
This can accordingly enable hackers to launch attacks based on the sniffing of unencrypted traffic. In order to alleviate WEP problems, IEEE and the Wi-Fi community have specified and implemented Wi-Fi standards and protocols (e.g., WPA2, WPA2-PSK (TKIP/AES)) with much stronger encryption capabilities. Nevertheless, not all IoT medical devices security vendors provide proper support for these standards, putting the operation of devices and their interoperability with others at risk.
In recent years, special emphasis has been given in producing standards and best practices for securing wireless medical devices, on the basis of the implementation of appropriate authentication and encryption mechanisms for IoT medical devices security.
This has led to the specification of IEEE 802.1X, which is a ratified IEEE standard for network access control. 802.1X is flexible and supports a variety of Extensible Authentication Protocol (EAP), including EAP with Transport Layer Security (EAP-TLS) and Advanced Encryption Standard (AES) encryption. The latter provides two-way authentication between devices based on the installation and use of X.509 certificates.
Alleviating IoT Medical Devices Security Vulnerabilities
The vision of IoT enabled hospital care cannot be realized without very strong security. CIOs and IT managers of healthcare services providers cannot therefore afford to treat security investments with caution, in an effort to reduce budgets which could ignoring low-probability risks.
Rather, they should adopt a holistic approach to IoT medical devices security and their operation, spanning technology, processes and security policy aspects.
At the technological forefront, latest Wi-Fi technologies offering strong security and encryption features should be deployed and tested.
This may involve purchasing technologically advanced equipment and testing it in terms of IoT medical devices security features, configuration problems, wireless stability and more. There is also a need for medical engineering processes in order to ensure that IoT-enabled process provide high security levels.
IoT medical devices security vulnerabilities is particularly important in the case of the trending BYOD (Bring Your Own Device) services, which involve the deployment and use of third-party devices as part of healthcare processes.
Moreover, as part of the holistic security approach, hospitals must tweak their security policies in order to keep up with IoT-related technological developments.
The right technology, the proper processes and an IoT-aligned security policy provide a sound basis for hospitals to adhere to security and privacy regulations, to avoid relevant liabilities and ultimate to maximize returns on their IoT investments.
Next Generation of IoT Medical Devices Cyber Security Recruitment
The NextGen Executive Search cyber security team is intimately familiar with the newest IoT medical devices security over WiFi networks. We identify and develop candidates so that in the shortlist we deliver to clients those who not only meet, but exceed your expectations. We target only “A players” who produce 8 to 10 times more than “B players, backed by an industry leading 12 to 36 month replacement guarantee. For more information on recruiting cyber security professionals for in-hospital medical devices using ioT device and data network connections, speak with the cyber security practice lead, click on the image below.
Industrial Robotics Cyber Security Challenges in IIoT
The line is blurring between information technology (IT) and operational technology (OT). As more industrial robotics equipment is connected to the industrial internet of things (IIoT), the vulnerabilities increase. Among the many devices being added to networks are robotic machines. That’s raising red flags for some experts. And it has many people worried. What are the risks associated with connecting an army of robots? It’s the stuff of science fiction.
Industrial Robotics Cyber Security Concerns on the Rise
The World Robotics Report 2016 gives us some insight into the scope of global automation growth: “The number of industrial robotics deployed worldwide will increase to around 2.6 million units by 2019.” It says that the strongest growth figures are for Central and Eastern Europe. The report cites China as the market for growth, and says that North America is on the path to success. “The USA is currently the fourth largest single market for industrial robots in the world,” according to the report.
TechCrunch contributor Matthew Rendall says “Industrial robotics will replace manufacturing jobs — and that’s a good thing”. He writes that the “productivity growth” behind 85% of job losses is all about machines replacing humans. Luddite and famous poet Lord Byron would not have been pleased. But Rendall is not bothered. He says that “more is getting done” by industrial robotics that are safer and more reliable than human beings. And he believes that this robotics revolution will be beneficial to workers and society in the long run.
All this rush to automation might be the best thing since jelly doughnuts. But one question could make all the difference between abysmal failure and glorious success: Can we keep them secure?
Challenge in Industrial Robotics Cyber Security
We probably don’t need to worry about robots taking over the world any time soon. (Let’s hope, anyway.) What concerns security experts is that our computer-based friends can be hacked. Wired Magazine reports how one group of researchers was able to sabotage an industrial robotics arm without even touching the code. That’s especially worrying when you think that most industrial robotics have a single arm and nothing else. These devices are made to make precise movements. Hackers can change all that.
German designer Clemens Weisshaar addressed the issue in a form at Vienna Design Week in 2014. “Taking robots online is as dangerous as anything you can put on the web,” he said. In a video from the forum, Weisshaar talked about how even his company’s robot demonstration in London had been hacked within 24 hours. They even tried to drive his robots into the ground. “If everything is on the internet,” he said, “then everything is vulnerable to attack.”
Industrial robotics cyber security challenges are only one part of what many are calling Industry 4.0. It’s a trending concept — especially in Germany — and it’s another way of referring to the Fourth Industrial Revolution. To understand what this is about, we should first reach back in the dim recesses of our minds to what we learned in history class in school.
The Industrial Revolution, as it was originally called, took place in the 18th and 19th centuries. It started in Great Britain and involved the harnessing of steam and tremendous advances in production methods – the 1st. Next came the 2nd roughly from 1870 until World War I in the USA. This involved the use of electricity to develop mass production processes. Th 3rd brought us into the digital age. Part four is upon us now.
A video from Deloitte University Press introduces us to the Fourth Industrial Revolution — Industry 4.0. It gives a good summary of the four “revolutions”, and it talks about some of the new technologies that now define our age:
- Internet of Things (IoT)
- Machine Learning
- Augmented Reality
- Mobile and Edge Computing
- 3D Printing
- Big Data Processing
“These technologies,” says the narrator, “will enable the construction of new solutions to some of the oldest and toughest challenges manufacturers face in growing and operating their business.” They also make up the environment in which hackers flourish.
Industrial Robots Cyber Security Challenges for IoT Data and Devices
In this space we have already discussed the security vulnerabilities of IoT devices. We told you how white hat hackers proved that they could commandeer a Jeep Cherokee remotely by rewriting the firmware on an embedded chip. Imagine what hackers with more sinister motives might be planning for the millions of robotic devices taking over the manufacturing shop floor — supposing they are all connected.
Some researchers tackled the issue in a study called “Hacking Robots Before Skynet”. (You will remember from your science fiction watching that Skynet is the global network that linked robots and other computerized devices in the Terminator movie franchise.) The authors had a lot to say about the current state of cybersecurity in the industrial robotics industry. We can borrow directly from the paper’s table of contents to list what they call “Cybersecurity Problems in Today’s Robots”:
- Insecure communications
- Authentication issues
- Missing authorization
- Weak cryptography
- Privacy issues
- Weak default configuration
- Vulnerable Open Source Industrial Robotics cyber security Frameworks and Libraries
Each of these topics could probably merit a full article on its own. The researchers explained further: “We’re already experiencing some of the consequences of substantial cybersecurity problems with Internet of Things (IoT) devices that are impacting the Internet, companies and commerce, and individual consumers alike, Cybersecurity problems for industrial robotics could have a much greater impact.”
What might that impact be? Well, to start with, robots have moving parts. They tell how a robot security guard knocked over a child at a shopping mall. A robot cannon killed nine soldiers and injured 14 in 2007. And robotic surgery has been linked to 144 deaths. It’s not Skynet yet, but connecting robots has its risks.
How we communicate with machines and how they communicate with each other are matters that require significant attention. Arlen Nipper of Cirrus Link Solutions talks about MQTT, which is a protocol for machine-to-machine (M2M) messaging. Manufacturing designers and operators send instructions to one-armed industrial robotics, who work in a variety of industries from automotive to aerospace to agriculture to packing and logistics. All this talking back-and-forth with industrial robotics cyber security has to be regulated. NIST’s Guide to Industrial Control Systems (ICS) Security has a few references to robots. But maybe not enough.
Cyber Security with Artificial Intelligence Elements and Ai Platforms
Cyber-security has always been a major concern for providers, vendors and operators of IT systems and services. Despite increased investments in security technology, this has not changed, as evident in several notorious cyber-attacks and related security incidents that have taken place during the last couple of years. It’s time to revolutionize cyber security with artificial intelligence.
For instance, earlier this year, the global “WannaCry” ransomware attack has severely affected the operations of numerous organizations worldwide, including major organizations such as Britain’s National Health Service (NHS). “WannaCry” has manifested the potential scale and physical consequences of cyber-crime incidents, while confirming the importance of proper cyber security measures.
Beyond their financial and business implications, cyber-attacks have a significant socio-economic impact as well, as they reduce citizens’ and businesses trust in IT systems and services. This lack of trust is a major issue in an increasingly connected world and in an era where IT systems are a primarily vehicle for increased competitiveness and productivity. It’s therefore important to understand the factors that increase the number and scale of cyber security attacks, along with options for alleviating security incidents against IT infrastructures, such as phishing, botnets, ransomware and DDoS (Distributed Denial of Service) incidents.
Drivers of Advanced Cyber Security
Effective cyber-protection requires modern, advanced and intelligent cyber-security systems. The scale, complexity and sophistication of these systems are driven by the following factors:Technology Evolution: The evolving technological complexity of cyber infrastructures renders their protection more challenging. For example, the rise and expanded use of Internet-of-Things (IoT) technologies provides cyber-crime opportunities based on the hacking of individual devices. Such hacking was hardly possible before the advent of the IoT paradigm. This is evident in the emergence of large scale IoT attacks, such as last year’s IoT-based massive Distributed Denial of Service (DDoS) attack that brought down the Dyn’s Domain Name System (DNS) and affected major internet sites like Twitter, Amazon and Spotify.Complex Regulatory Environment: Nowadays, IT infrastructures’ operators and IT service providers need to adhere to quite complex regulatory requirements, including sector specific requirements (e.g., regulations for financial institutions) and general-purpose regulations such as EU’s general data protection regulation. The implementation of security policies and controls that address these regulatory requirements contributes to the rising complexity of cyber-security systems.Convergence of Physical and Cyber Security: IT systems are increasingly becoming connected and interdependent to physical systems and processes. This is for example the case with most industrial organizations, which converge their cyber physical infrastructures as part of their digital transformation in the Industry4.0 era. Industry4.0 infrastructures in sectors like energy, manufacturing and oil & gas form large scale cyber-physical systems. This cyber-physical nature leads gradually to a convergence of physical security and cyber-security measures and policies towards greater effectiveness and economies of scale. Converged cyber and physical security measures are more appropriate for identifying and mitigating complex, asymmetric security incidents, which are likely to attack both cyber and physical systems at the same time. Overall, while this convergence is beneficial for industrial organizations, it leads to a widening complexity for the respective security systems.New Business Models and Opportunities: The increased reliance of products and services on cyber infrastructures provides new business opportunities for providers of cyber-security solutions and services. As a prominent example, a new wave of cyber-insurance services is currently designed to support the emerging connected cars and semi-autonomous driving paradigms. These include for example, insurance business models that consider IT-derived information about the driver’s behavior as a means of adapting the car insurance fees. Supporting these opportunities implies additional security measures concerning for example the secure and trustworthy transmission of information that supports them.
Novel Approaches and Paradigm Shifts in Cyber Security
Confronting the recent wave of sophisticated cyber-attacks requires new approaches to threat identification, assessment and mitigation. Some of the main characteristics of these approaches, include:
- Integrated and holistic nature: Instead of protecting specific devices and IT systems, there is a need for holistic, cross-cutting mechanisms that span all the different layers of modern cyber-security infrastructures, including individual device, fog/edge computing nodes, as well as cloud infrastructures. The implementation of holistic, cross-cutting mechanisms must be driven by integrated approaches to threat modelling, which identify, assess and rate vulnerabilities/threats across all different layers of a cyber-infrastructure. Assessment and rating is a key to prioritizing the deployment of specific security measures at the most appropriate places of the infrastructure. This is very important given that organizations operate based on quite constrained budgets for IT security, which makes it impossible to provide full protection against all possible vulnerabilities.
- Intelligence and dynamism: To cope with the emerging complex, large scale, dynamic and asymmetric attacks, there is a need for intelligent and dynamic mechanisms that can correlate information from multiple sources to timely identify security incidents and vulnerabilities. In practice, this requires the deployment of advanced data-driven techniques to security identification and assessment, based on machine learning and data mining models that implement a data-driven approach to cyber-security.
- Adherence to latest security standards: Fortunately, security standards have been evolving in-line with the rising sophistication of cyber-security attacks. This means that adhere to standards can be a safe path to designing and deploying systems that support the above-mentioned holistic approach to cyber-security. Organizations are therefore implementing security standards from the popular ISO/IEC 27001 on Information security management to the Security Framework of the Industrial Internet Consortium for securing cyber infrastructures that support industrial processes.
- User Friendly and Human Centric: Novel approaches to cyber-security should consider the human factor, to alleviate the need for end-users to understand security systems and processes. This is particularly important for organizations (such as Small Medium Businesses), which lack the knowledge and equity needed to invest in security training of their personnel.
- New delivery models: Organizations are increasingly adopting new delivery models for security services, such as Managed Security Systems and Security-as-a-Service. These models obviate the need for on premise installations and enable enterprises to leverage security services in a flexible pay-as-you go fashion.
The implementation of solutions with the above-listed characteristics signals a paradigm shift in the way security is designed, deployed and provided. This shift is destined to increase the cyber-resilience of organizations, including large enterprises and SMBs.
How to Revolutionize Cyber Security with Artificial Intelligence
In quest for dynamic, intelligence and holistic cyber-security mechanisms, security experts are nowadays considering the employment of AI based mechanisms. This consideration is largely motivated by recent advances in deep neural learning and AI, which facilitate the identification of very complex patterns based on human like reasoning.
Relevant technology advances have empowered Google’s Alpha AI to defeat grandmasters in the Go game, which is considered a milestone in the evolution of AI technologies. Likewise, AI techniques can be used to detect and assess complex attack patterns, as a means of preventing or alleviating large scale security incidents such as “Wannacy”.
The idea to deploy or revolutionize cyber security with artificial intelligence can provide some compelling advantages, including:
- Detecting complex attacks: Deep learning techniques based on advanced neural networks enable the detection of non-conventional, non-trivial security incidents that can be hardly detected based on commonly used rules and conventional reasoning.
- Predictive Security Analytics: AI is a perfect enabler for predictive security, through employing predictive data analytics based on deep learning. This can enable a paradigm shift from reactive to predictive security. Based on predictive security, organizations can anticipate the occurrence of threats to timely prepare and apply proper mitigation strategies.
- Security Automation: AI systems can increase the automation of security measures, through triggering mitigation actions automatically, upon the detection of cyber-security threats. While human involvement is always necessary and desirable, one way to revolutionize cyber security with artificial intelligence is to increase security automation, while delivering advanced protection functionalities at a lower cost.
Current and Future Status to Revolutionize Cyber Security with Artificial Intelligence
Despite these benefits, AI security implementations are still in their early stages. This is because there are several challenges to be addressed towards effective AI deployments. For example, there is a need for collecting and using large amounts of data, which are not always readily available. Therefore, AI systems are usually supported by the deployment of additional security monitoring probes, at the device, fog, edge and cloud layers of the cyber-security infrastructure.
Likewise, the effective deployment to revolutionize cyber security with artificial intelligence requires domain knowledge to avoid failures of the deep learning networks, such as failures due to overfitting on the training data. Such domain knowledge requires the collaboration of security experts, data scientists and experts in field processes, which is not always easy to achieve. Finally, there is also a need for aligning the operation of AI-based security systems with the business objectives and security policies of the organization, which can be extremely challenging.
In order to alleviate these challenges, enterprises need to consistently collect and manage security datasets, while at the same time assembling a security team with proper skills including both data science and security expertise.
Moreover, they need to leverage emerging AI-based tools in order to revolutionize cyber security with artificial intelligence for extracting knowledge from datasets, such as TensorFlow and H2O.ai.
Finally, it’s good to adopt an incremental deployment approach, which boosts the acquisition of knowledge and experience in the AI field, while gradually meeting business objectives. As enterprises face unprecedented security challenges, new approaches are required. AI will be certainly among the most useful tools in organizations’ cyber-resilience arsenal. Despite early challenges, the best means to revolutionize cyber security with artificial intelligence are still to come.
Cyber Security Recruitment for Enterprise – Network – Mobile – Cloud – IoT – Ai
Many companies that develop machine learning platforms and utilize artificial intelligence are discovering potential issues with cyber security within deep learning networks, especially within FinTech, AdTech, and augmented reality for consumers. If you need help to identify and recruit key cyber security or Ai engineers, sales management, functional leaders, or senior executives, take a look at NextGen Executive Search. For further information on our cyber security executive search firm or to contact us directly, click the image below.