Assessment of security vulnerabilities in wearable devices

Wearable devices have proliferated in usage and human experience, and they provide convenience for personal information requirements. These devices are both sensory and immersive for the diverse global network that is generally termed the Internet of things (IoT). The immediacy of the two-way communication created in the IoT has made vulnerable human behaviour and raised debate around information ownership and privacy expectations. The legitimacy of ownership of information and its reuse are prevalent problems. In this research, we tested four wearable devices that share 44% of the current market, for security vulnerabilities. We found serious weaknesses that could result in the unplanned disclosure of information and recommend further research into users expectations for safety

Knock! Knock! Who Is There? Investigating Data Leakage from a Medical Internet of Things Hijacking Attack

The amalgamation of Medical Internet of Things (MIoT) devices into everyday life is influencing the landscape of modern medicine. The implementation of these devices potentially alleviates the pressures and physical demands of healthcare systems through the remote monitoring of patients. However, there are concerns that the emergence of MIoT ecosystems is introducing an assortment of security and privacy challenges. While previous research has shown that multiple vulnerabilities exist within MIoT devices, minimal research investigates potential data leakage from MIoT devices through hijacking attacks. The research contribution of this paper is twofold. First, it provides a proof of concept that certain MIoT devices and their accompanying smartphone applications are vulnerable to hijacking attacks. Second, it highlights the effectiveness of using digital forensics tools as a lens to identify patient and medical device information on a hijacker’s smartphone

A systematic review of crime facilitated by the consumer Internet of Things

The nature of crime is changing — estimates suggest that at least half of all crime is now committed online. Once everyday objects (e.g. televisions, baby monitors, door locks) that are now internet connected, collectively referred to as the Internet of Things (IoT), have the potential to transform society, but this increase in connectivity may generate new crime opportunities. Here, we conducted a systematic review to inform understanding of these risks. We identify a number of high-level mechanisms through which offenders may exploit the consumer IoT including profiling, physical access control and the control of device audio/visual outputs. The types of crimes identified that could be facilitated by the IoT were wide ranging and included burglary, stalking, and sex crimes through to state level crimes including political subjugation. Our review suggests that the IoT presents substantial new opportunities for offending and intervention is needed now to prevent an IoT crime harvest

Systematic Review of Internet of Things Security

The Internet of Things has become a new paradigm of current communications technology that requires a deeper overview to map its application domains, advantages, and disadvantages. There have been a number of in-depth research efforts to study various aspects of IoT. However, to the best of our knowledge, there is no literature that have discussed specifically and deeply about the security and privacy aspects of IoT. To that end, this paper aims at providing a more comprehensive and systematic review of IoT security based on the survey result of the most recent literature over the past three years (2015 to 2017). We have classified IoT security research based on the research objectives, application domains, vulner-abilities/threats, countermeasures, platforms, proto-cols, and performance measurements. We have also provided some security challenges for further research

Security for networked smart healthcare systems: A systematic review

Background and Objectives Smart healthcare systems use technologies such as wearable devices, Internet of Medical Things and mobile internet technologies to dynamically access health information, connect patients to health professionals and health institutions, and to actively manage and respond intelligently to the medical ecosystem's needs. However, smart healthcare systems are affected by many challenges in their implementation and maintenance. Key among these are ensuring the security and privacy of patient health information. To address this challenge, several mitigation measures have been proposed and some have been implemented. Techniques that have been used include data encryption and biometric access. In addition, blockchain is an emerging security technology that is expected to address the security issues due to its distributed and decentralized architecture which is similar to that of smart healthcare systems. This study reviewed articles that identified security requirements and risks, proposed potential solutions, and explained the effectiveness of these solutions in addressing security problems in smart healthcare systems. Methods This review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines and was framed using the Problem, Intervention, Comparator, and Outcome (PICO) approach to investigate and analyse the concepts of interest. However, the comparator is not applicable because this review focuses on the security measures available and in this case no comparable solutions were considered since the concept of smart healthcare systems is an emerging one and there are therefore, no existing security solutions that have been used before. The search strategy involved the identification of studies from several databases including the Cumulative Index of Nursing and Allied Health Literature (CINAL), Scopus, PubMed, Web of Science, Medline, Excerpta Medical database (EMBASE), Ebscohost and the Cochrane Library for articles that focused on the security for smart healthcare systems. The selection process involved removing duplicate studies, and excluding studies after reading the titles, abstracts, and full texts. Studies whose records could not be retrieved using a predefined selection criterion for inclusion and exclusion were excluded. The remaining articles were then screened for eligibility. A data extraction form was used to capture details of the screened studies after reading the full text. Of the searched databases, only three yielded results when the search strategy was applied, i.e., Scopus, Web of science and Medline, giving a total of 1742 articles. 436 duplicate studies were removed. Of the remaining articles, 801 were excluded after reading the title, after which 342 after were excluded after reading the abstract, leaving 163, of which 4 studies could not be retrieved. 159 articles were therefore screened for eligibility after reading the full text. Of these, 14 studies were included for detailed review using the formulated research questions and the PICO framework. Each of the 14 included articles presented a description of a smart healthcare system and identified the security requirements, risks and solutions to mitigate the risks. Each article also summarized the effectiveness of the proposed security solution. Results The key security requirements reported were data confidentiality, integrity and availability of data within the system, with authorisation and authentication used to support these key security requirements. The identified security risks include loss of data confidentiality due to eavesdropping in wireless communication mediums, authentication vulnerabilities in user devices and storage servers, data fabrication and message modification attacks during transmission as well as while the data is at rest in databases and other storage devices. The proposed mitigation measures included the use of biometric accessing devices; data encryption for protecting the confidentiality and integrity of data; blockchain technology to address confidentiality, integrity, and availability of data; network slicing techniques to provide isolation of patient health data in 5G mobile systems; and multi-factor authentication when accessing IoT devices, servers, and other components of the smart healthcare systems. The effectiveness of the proposed solutions was demonstrated through their ability to provide a high level of data security in smart healthcare systems. For example, proposed encryption algorithms demonstrated better energy efficiency, and improved operational speed; reduced computational overhead, better scalability, efficiency in data processing, and better ease of deployment. Conclusion This systematic review has shown that the use of blockchain technology, biometrics (fingerprints), data encryption techniques, multifactor authentication and network slicing in the case of 5G smart healthcare systems has the potential to alleviate possible security risks in smart healthcare systems. The benefits of these solutions include a high level of security and privacy for Electronic Health Records (EHRs) systems; improved speed of data transaction without the need for a decentralized third party, enabled by the use of blockchain. However, the proposed solutions do not address data protection in cases where an intruder has already accessed the system. This may be potential avenues for further research and inquiry

C-NEST: cloudlet based privacy preserving multidimensional data stream approach for healthcare electronics.

The Medical Internet of Things (MIoT) facilitates extensive connections between cyber and physical "things" allowing for effective data fusion and remote patient diagnosis and monitoring. However, there is a risk of incorrect diagnosis when data is tampered with from the cloud or a hospital due to third-party storage services. Most of the existing systems use an owner-centric data integrity verification mechanism, which is not computationally feasible for lightweight wearable-sensor systems because of limited computing capacity and privacy leakage issues. In this regard, we design a 2-step Privacy-Preserving Multidimensional Data Stream (PPMDS) approach based on a cloudlet framework with an Uncertain Data-integrity Optimization (UDO) model and Sparse-Centric SVM (SCS) model. The UDO model enhances health data security with an adaptive cryptosystem called Cloudlet-Nonsquare Encryption Secret Transmission (C-NEST) strategy by avoiding medical disputes during data streaming based on novel signature and key generation strategies. The SCS model effectively classifies incoming queries for easy access to data by solving scalability issues. The cloudlet server measures data integrity and authentication factors to optimize third-party verification burden and computational cost. The simulation outcomes show that the proposed system optimizes average data leakage error rate by 27%, query response time and average data transmission time are reduced by 31%, and average communication-computation cost are reduced by 61% when measured against state-of-the-art approaches

Heart failure patients monitoring using IoT-based remote monitoring system

Intelligent health monitoring systems are becoming more important and popular as technology advances. Nowadays, online services are replacing physical infrastructure in several domains including medical services as well. The COVID-19 pandemic has also changed the way medical services are delivered. Intelligent appliances, smart homes, and smart medical systems are some of the emerging concepts. The Internet of Things (IoT) has changed the way communication occurs alongside data collection sources aided by smart sensors. It also has deployed artificial intelligence (AI) methods for better decision-making provided by efficient data collection, storage, retrieval, and data management. This research employs health monitoring systems for heart patients using IoT and AI-based solutions. Activities of heart patients are monitored and reported using the IoT system. For heart disease prediction, an ensemble model ET-CNN is presented which provides an accuracy score of 0.9524. The investigative data related to this system is very encouraging in real-time reporting and classifying heart patients with great accuracy

Improving security of IoT using RIOTSS

As the Internet of Things grows in demand, various vendors continue to create new devices and products that exchange data and operate remotely. These new products and features may include security risks if not properly mitigated, potentially compromising personally identifiable information. Current literature reveals the need to utilize proper security measures and a process to maintain confidentiality, integrity, and availability to prevent and/or limit malicious actions. If information security is missing any part of the confidentiality, integrity, or availability triad, then the information system or device will not be fully secured. The approach discussed in this research project was to develop a new security framework entitled riskless Internet of Things security standard (RIOTSS). The intended purpose of the RIOTSS is to create a framework based on security standards, industry best practices, policies, and procedures that vendors and manufactures can implement into their production of IoT devices to prevent or limit security weaknesses being introduced into the productions of IoT device products while also offering mitigating procedures that the vendor or manufactures can implemented in a secure manner without restricting device functionality or capability

The Proceedings of 15th Australian Information Security Management Conference, 5-6 December, 2017, Edith Cowan University, Perth, Australia

Conference Foreword The annual Security Congress, run by the Security Research Institute at Edith Cowan University, includes the Australian Information Security and Management Conference. Now in its fifteenth year, the conference remains popular for its diverse content and mixture of technical research and discussion papers. The area of information security and management continues to be varied, as is reflected by the wide variety of subject matter covered by the papers this year. The papers cover topics from vulnerabilities in “Internet of Things” protocols through to improvements in biometric identification algorithms and surveillance camera weaknesses. The conference has drawn interest and papers from within Australia and internationally. All submitted papers were subject to a double blind peer review process. Twenty two papers were submitted from Australia and overseas, of which eighteen were accepted for final presentation and publication. We wish to thank the reviewers for kindly volunteering their time and expertise in support of this event. We would also like to thank the conference committee who have organised yet another successful congress. Events such as this are impossible without the tireless efforts of such people in reviewing and editing the conference papers, and assisting with the planning, organisation and execution of the conference. To our sponsors, also a vote of thanks for both the financial and moral support provided to the conference. Finally, thank you to the administrative and technical staff, and students of the ECU Security Research Institute for their contributions to the running of the conference