We propose and implement Directory-Based Access Control (DBAC), a flexible and systematic access control approach for geographically distributed multi-administration IoT systems. DBAC designs and relies on a particular module, IoT directory, to store device metadata, manage federated identities, and assist with cross-domain authorization. The directory service decouples IoT access into two phases: discover device information from directories and operate devices through discovered interfaces. DBAC extends attribute-based authorization and retrieves diverse attributes of users, devices, and environments from multi-faceted sources via standard methods, while user privacy is protected. To support resource-constrained devices, DBAC assigns a capability token to each authorized user, and devices only validate tokens to process a request. 
                        more » 
                        « less   
                    
                            
                            GOLDIE: Harmonization and Orchestration Towards a Global Directory for IoT
                        
                    
    
            To scale the Internet of Things (IoT) beyond a single home or enterprise, we need an effective mechanism to manage the growth of data, facilitate resource discovery and name resolution, encourage data sharing, and foster cross-domain services. To address these needs, we propose a GlObaL Directory for Internet of Everything (GOLDIE). GOLDIE is a hierarchical location-based IoT directory architecture featuring diverse user-oriented modules and federated identity management. IoT-specific features include discoverability, aggregation and geospatial queries, and support for global access. We implement and evaluate the prototype on a Raspberry Pi and Intel mini servers. We show that a global implementation of GOLDIE could decrease service access latency by 87% compared to a centralized-server solution. 
        more » 
        « less   
        
    
                            - Award ID(s):
- 1932418
- PAR ID:
- 10317809
- Date Published:
- Journal Name:
- IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
- 
            
- 
            The rapid adoption of Internet-of-Medical-Things (IoMT) has revolutionized e-health systems, particularly in remote patient monitoring. With the growing adoption of Internet-of-Medical-Things (IoMT) in delivering technologically advanced health services, the security of Medtronic devices is pivotal as the security and privacy of data from these devices are directly related to patient safety. PUF has been the most widely adopted hardware security primitive which has been successfully integrated with various Internet-of-Things (IoT) based applications, particularly in smart healthcare for facilitating device security. To facilitate security and access control to IoMT devices, this work proposes a novel cybersecurity solution using PUF for facilitating global access to IoMT devices. The proposed framework presents an approach that enables the patient’s body area network devices supported by PUF to be securely accessible and controllable globally. The proposed cybersecurity solution has been experimentally validated using state-of-the-art SRAM PUF, a delay based PUF, and a trusted platform module (TPM) primitive.more » « less
- 
            The internet of Things (IoT) refers to a network of physical objects that are equipped with sensors, software, and other technologies in order to communicate with other devices and systems over the internet. IoT has emerged as one of the most important technologies of this century over the past few years. To ensure IoT systems' sustainability and security over the long term, several researchers lately motivated the need to incorporate the recently proposed zero trust (ZT) cybersecurity paradigm when designing and implementing access control models for IoT systems. This poster proposes a hybrid access control approach incorporating traditional and deep learning-based authorization techniques toward score-based ZT authorization for IoT systems.more » « less
- 
            null (Ed.)The number of Internet-of-Things (IoT) devices actively communicating across the Internet is continually increasing, as these devices are deployed across a variety of sectors, constantly transferring private data across the Internet. Due to the extensive deployment of such devices, the continuous discovery and persistence of IoT-centric vulnerabilities in protocols, applications, hardware, and the improper management of such IoT devices has resulted in the rampant, uncontrolled spread of malware threatening consumer IoT devices. To this end, this work adopts a novel, macroscopic methodology for fingerprinting Internet-scale compromised IoT devices, revealing crucial cyber threat intelligence on the insecurity of consumer IoT devices. By developing data-driven techniques rooted in machine learning methods and analyzing 3.6 TB of network traffic data, we discover 855,916 compromised IP addresses, with 310,164 fingerprinted as IoT. Further analysis reveals China and Brazil to be hosting the most significant population of compromised IoT devices (100,000 and 55,000, respectively). Additionally, we provide a longitudinal analysis on data from one year ago against this work, revealing the evolving trends of IoT exploitation, such as the increased number of vendors targeted by malware, rising from 50 to 131. Moreover, countries such as China (420% increased infected IoT count) and Indonesia (177% increased infected IoT count) have seen notably high increases in infection rates. Last, we compare our geographic results against Global Cybersecurity Index (GCI) ratings, verifying that countries with high GCI ratings, such as the Netherlands and Germany, had relatively low infection rates. However, upon further inspection, we find that the GCI rate does not accurately represent the consumer IoT market, with countries such as China and Russia being rated with “high” CGI scores, yet hosting a large population of infected consumer IoT devices.more » « less
- 
            Abstract—Internet of Things (IoT) has become a pervasive and diverse concept in recent years. IoT applications and services have given rise to a number of sub-fields in the IoT space. Wearable technology, with its particular set of characteristics and application domains, has formed a rapidly growing subfield of IoT, viz., Wearable Internet of Things (WIoT). While numerous wearable devices are available in the market today, security and privacy are key factors for wide adoption of WIoT. Wearable devices are resource constrained by nature with limited storage, power, and computation. A Cloud-Enabled IoT (CEIoT) architecture, a dominant paradigm currently shaping the industry and suggested by many researchers, needs to be adopted for WIoT. In this paper, we develop an access control framework for cloud-enabled WIoT (CEWIoT) based on the Access Control Oriented (ACO) architecture recently developed for CEIoT in general. We first enhance the ACO architecture from the perspective of WIoT by adding an Object Abstraction Layer, and then develop our framework based on interactions between different layers of this enhanced ACO architecture. We present a general classification and taxonomy of IoT devices, along with brief introduction to various application domains of IoT and WIoT. We then present a remote health and fitness monitoring use case to illustrate different access control aspects of our framework and outline its possible enforcement in a commercial CEIoT platform, viz., AWS IoT. Finally, we discuss the objectives of our access control framework and relevant open problems.more » « less
 An official website of the United States government
An official website of the United States government 
				
			 
					 
					
 
                                    