DICOM Images Have Been Hacked! Now What?

Desjardins, Benoı̂t; Mirsky, Yisroel; Ortiz, Markel Picado; Glozman, Zeev; Tarbox, Lawrence; Horn, Robert J; Horii, Steven C.

doi:10.2214/ajr.19.21958

Cited by 39 publications

(25 citation statements)

References 6 publications

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“…While there are many guidelines and implementation guides for generic IT cybersecurity, little practical help is available so far for the practitioner who wants to bring the security of a PACS network up to the state of the art. A recent draft publication by the U.S. NIST entitled "Securing Picture Archiving and Communication System À Cybersecurity for the Healthcare Sector" (29) and a publication by Desjardins et al (30) that provides recommendations to the DICOM committee, vendors and users, are first steps in this direction, but…”

Section: Discussionmentioning

confidence: 99%

Cybersecurity Challenges for PACS and Medical Imaging

Eichelberg

Kleber²,

Kämmerer³

2020

Academic Radiology

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Cybersecurity issues have been on the rise for years, increasingly affecting the healthcare sector. In 2019, several attacks have been published that specifically aim at medical network protocols and file formats, in particular digital imaging and communications in medicine. This article describes five attack scenarios on picture archiving and communications systems (PACS) and medical imaging networks: the import of patient data from storage media containing malware, a compromise of the hospital network, malware embedded in digital imaging and communications in medicine images or reports, a malicious manipulation of medical images and a network infiltration of malicious health level seven messages. Prevention and mitigation measures for each of these attacks exist, some of which can be implemented by the system user (e.g., hospital), while others require implementation in the PACS and medical imaging devices by the vendors. In practice, however, many of these are not in common use. What is missing today are PACS network security guidelines for practitioners that support users in keeping their network secure. Furthermore, integrating the healthcare enterprise integration profiles and test tools might be needed to address the deployment of public key infrastructure and digital signatures in the PACS environment.

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Section: Discussionmentioning

confidence: 99%

Cybersecurity Challenges for PACS and Medical Imaging

Eichelberg

Kleber²,

Kämmerer³

2020

Academic Radiology

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“…This is because health records are some of the most sensitive information out there and continues to be the victim of cyber attacks constantly [6]. Medical imaging devices in particular are the latest target of hackers [16] due to the lack of proper security measures taken around them [17]. Recent experiments by Israeli researchers show how easily MRI and CT scans can be tampered without any trace [18].…”

Section: Introductionmentioning

confidence: 99%

Towards developing a secure medical image sharing system based on zero trust principles and blockchain technology

Sultana¹,

Hossain²,

Laila³

et al. 2020

BMC Med Inform Decis Mak

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Background Data security has been a critical topic of research and discussion since the onset of data sharing in e-health systems. Although digitalization of data has increased efficiency and speed, it has also made data vulnerable to cyber attacks. Medical records in particular seem to be the regular victims of hackers. Several data breach incidents throughout history have warranted the invention of security measures against these threats. Although various security procedures like firewalls, virtual private networks, encryption, etc are present, a mix of these approaches are required for maximum security in medical image and data sharing. Methods Relatively new, blockchain has become an effective tool for safeguarding sensitive information. However, to ensure overall protection of medical data (images), security measures have to be taken at each step, from the beginning, during and even after transmission of medical images which is ensured by zero trust security model. In this research, a number of studies that deal with these two concepts were studied and a decentralized and trustless framework was proposed by combining these two concepts for secured medical data and image transfer and storage. Results Research output suggested blockchain technology ensures data integrity by maintaining an audit trail of every transaction while zero trust principles make sure the medical data is encrypted and only authenticated users and devices interact with the network. Thus the proposed model solves a lot of vulnerabilities related to data security. Conclusions A system to combat medical/health data vulnerabilities has been proposed. The system makes use of the immutability of blockchain, the additional security of zero trust principles, and the scalability of off chain data storage using Inter Planetary File Systems (IPFS). The adoption of this system suggests to enhance the security of medical or health data transmission.

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“…There have been almost 3,000 breaches (involving more than 500 medical records) in the United States within the past 10 years. This includes high-profile cases such as the 2015 breach of the Anthem medical insurance company that potentially exposed the medical records of 78 million Americans and led to a $115 million settlement [5]. Hospitals and clinics have been held hostage when their data were corrupted by a third party that demanded payment (ransom) to release the data [5].…”

mentioning

confidence: 99%

“…This includes high-profile cases such as the 2015 breach of the Anthem medical insurance company that potentially exposed the medical records of 78 million Americans and led to a $115 million settlement [5]. Hospitals and clinics have been held hostage when their data were corrupted by a third party that demanded payment (ransom) to release the data [5]. In 2017, ransomware WannaCry and NotPetya spread through thousands of institutions worldwide, including many hospitals, and caused $18 billion in damages [5].…”

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confidence: 99%

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The Potential Dangers of Artificial Intelligence for Radiology and Radiologists

Chu

Anandkumar

Shin

et al. 2020

Journal of the American College of Radiology

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With the advent of artificial intelligence (AI) across many fields and subspecialties, there are considerable expectations for transformative impact. However, there are also concerns regarding the potential abuse of AI. Many scientists have been worried about the dangers of AI leading to "biased" conclusions, in part because of the enthusiasm of the inventor or overenthusiasm among the general public. Here, though, we consider some scenarios in which people may intend to cause potential errors within data sets of analyzed information, resulting in incorrect conclusions and leading to potential problems with patient care and outcomes.A generative adversarial network (GAN) is a recently developed deeplearning model aimed at creating new images. It simultaneously trains a generator and a discriminator network, which serves to generate artificial images and to discriminate real from artificial images, respectively. We have recently described how GANs can produce artificial images of people and audio content that fool the recipient into believing that they are authentic. As applied to medical imaging, GANs can generate synthetic images that can alter lesion size, location, and transpose abnormalities onto normal examinations (Fig. 1) [1]. GANs have the potential to improve image quality, reduce radiation dose, augment data for training algorithms,

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DICOM Images Have Been Hacked! Now What?

Cited by 39 publications

References 6 publications

Cybersecurity Challenges for PACS and Medical Imaging

Cybersecurity Challenges for PACS and Medical Imaging

Towards developing a secure medical image sharing system based on zero trust principles and blockchain technology

The Potential Dangers of Artificial Intelligence for Radiology and Radiologists

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