Biblio
The Internet of Things enables interaction between IoT devices and users through the cloud. The cloud provides services such as account monitoring, device management, and device control. As the center of the IoT platform, the cloud provides services to IoT devices and IoT applications through APIs. Therefore, the permission verification of the API is essential. However, we found that some APIs are unverified, which allows unauthorized users to access cloud resources or control devices; it could threaten the security of devices and cloud. To check for unauthorized access to the API, we developed IoT-APIScanner, a framework to check the permission verification of the cloud API. Through observation, we found there is a large amount of interactive information between IoT application and cloud, which include the APIs and related parameters, so we can extract them by analyzing the code of the IoT application, and use this for mutating API test cases. Through these test cases, we can effectively check the permissions of the API. In our research, we extracted a total of 5 platform APIs. Among them, the proportion of APIs without permission verification reached 13.3%. Our research shows that attackers could use the API without permission verification to obtain user privacy or control of devices.
The popularity and demand of home automation has increased exponentially in recent years because of the ease it provides. Recently, development has been done in this domain and few systems have been proposed that either use voice assistants or application for controlling the electrical appliances. However; less emphasis is laid on power efficiency and this system cannot be integrated with the existing appliances and hence, the entire system needs to be upgraded adding to a lot of additional cost in purchasing new appliances. In this research, the objective is to design such a system that emphasises on power efficiency as well as can be integrated with the already existing appliances. NodeMCU, along with Raspberry Pi, Firebase realtime database, is used to create a system that accomplishes such endeavours and can control relays, which can control these appliances without the need of replacing them. The experiments in this paper demonstrate triggering of electrical appliances using voice assistant, fire alarm on the basis of flame sensor and temperature sensor. Moreover; use of android application was presented for operating electrical appliances from a remote location. Lastly, the system can be modified by adding security cameras, smart blinds, robot vacuums etc.
Advancements in computing, communication, and sensing technologies are making it possible to embed, control, and gather vital information from tiny devices that are being deployed and utilized in practically every aspect of our modernized society. From smart home appliances to municipal water and electric industrial facilities to our everyday work environments, the next Internet frontier, dubbed IoT, is promising to revolutionize our lives and tackle some of our nations' most pressing challenges. While the seamless interconnection of IoT devices with the physical realm is envisioned to bring a plethora of critical improvements in many aspects and diverse domains, it will undoubtedly pave the way for attackers that will target and exploit such devices, threatening the integrity of their data and the reliability of critical infrastructure. Further, such compromised devices will undeniably be leveraged as the next generation of botnets, given their increased processing capabilities and abundant bandwidth. While several demonstrations exist in the literature describing the exploitation procedures of a number of IoT devices, the up-to-date inference, characterization, and analysis of unsolicited IoT devices that are currently deployed "in the wild" is still in its infancy. In this article, we address this imperative task by leveraging active and passive measurements to report on unsolicited Internet-scale IoT devices. This work describes a first step toward exploring the utilization of passive measurements in combination with the results of active measurements to shed light on the Internet-scale insecurities of the IoT paradigm. By correlating results of Internet-wide scanning with Internet background radiation traffic, we disclose close to 14,000 compromised IoT devices in diverse sectors, including critical infrastructure and smart home appliances. To this end, we also analyze their generated traffic to create effective mitigation signatures that could be deployed in local IoT realms. To support largescale empirical data analytics in the context of IoT, we make available the inferred and extracted IoT malicious raw data through an authenticated front-end service. The outcomes of this work confirm the existence of such compromised devices on an Internet scale, while the generated inferences and insights are postulated to be employed for inferring other similarly compromised IoT devices, in addition to contributing to IoT cyber security situational awareness.
Training the future cybersecurity workforce to respond to emerging threats requires introduction of novel educational interventions into the cybersecurity curriculum. To be effective, these interventions have to incorporate trending knowledge from cybersecurity and other related domains while allowing for experiential learning through hands-on experimentation. To date, the traditional interdisciplinary approach for cybersecurity training has infused political science, law, economics or linguistics knowledge into the cybersecurity curriculum, allowing for limited experimentation. Cybersecurity students were left with little opportunity to acquire knowledge, skills, and abilities in domains outside of these. Also, students in outside majors had no options to get into cybersecurity. With this in mind, we developed an interdisciplinary course for experiential learning in the fields of cybersecurity and interaction design. The inaugural course teaches students from cybersecurity, user interaction design, and visual design the principles of designing for secure use - or secure design - and allows them to apply them for prototyping of Internet-of-Things (IoT) products for smart homes. This paper elaborates on the concepts of secure design and how our approach enhances the training of the future cybersecurity workforce.
This study has built a simulation of a smart home system by the Alibaba ECS. The architecture of hardware was based on edge computing technology. The whole method would design a clear classifier to find the boundary between regular and mutation codes. It could be applied in the detection of the mutation code of network. The project has used the dataset vector to divide them into positive and negative type, and the final result has shown the RBF-function SVM method perform best in this mission. This research has got a good network security detection in the IoT systems and increased the applications of machine learning.
Nowadays, the Internet of Things (IoT) is a consolidated reality. Smart homes are equipped with a growing number of IoT devices that capture more and more information about human beings lives. However, manufacturers paid little or no attention to security, so that various challenges are still in place. In this paper, we propose a novel approach to secure IoT systems that combines the concept of Security-by-Contract (S×C) with the Fog computing distributed paradigm. We define the pillars of our approach, namely the notions of IoT device contract, Fog node policy and contract-policy matching, the respective life-cycles, and the resulting S×C workflow. To better understand all the concepts of the S×C framework, and highlight its practical feasibility, we use a running case study based on a context-aware system deployed in a real smart home.
The proliferation of the Internet of Things (IoT) in the context of smart homes entails new security risks threatening the privacy and safety of end users. In this paper, we explore the design space of in-network security for smart home networks, which automatically complements existing security mechanisms with a rule-based approach, i. e., every IoT device provides a specification of the required communication to fulfill the desired services. In our approach, the home router as the central network component then enforces these communication rules with traffic filtering and anomaly detection to dynamically react to threats. We show that in-network security can be easily integrated into smart home networks based on existing approaches and thus provides additional protection for heterogeneous IoT devices and protocols. Furthermore, in-network security relieves users of difficult home network configurations, since it automatically adapts to the connected devices and services.
Internet of Things (IoT) is a contemporary concept for connecting the existing things in our environment with the Internet for a sake of making the objects information are accessible from anywhere and anytime to support a modern life style based on the Internet. With the rapid development of the IoT technologies and widely spreading in most of the fields such as buildings, health, education, transportation and agriculture. Thus, the IoT applications require increasing data collection from the IoT devices to send these data to the applications or servers which collect or analyze the data, so it is a very important to secure the data and ensure that do not reach a malicious adversary. This paper reviews some attacks in the IoT applications and the security weaknesses in the IoT environment. In addition, this study presents the challenges of IoT in terms of hardware, network and software. Moreover, this paper summarizes and points to some attacks on the smart car, smart home, smart campus, smart farm and healthcare.
We present an intelligent system that focus on how to ensure the stability of ZigBee network automatically. First, we discussed on the character of ZigBee compared with WIFI. Pointed out advantage of ZigBee resides in security, stability, low power consumption and better expandability. Second, figuring out the shortcomings of ZigBee on application is that physical limitation of the frequency band and weak ability on diffraction, especially coming across a wall or a door in the actual environment of home. The third, to put forward a method which can be used to ensure the strength of ZigBee signal. The method is to detect the strength of ZigBee relay in advance. And then, to compare it with the threshold value which had been defined in previous. The threshold value of strength of ZigBee is the minimal and tolerable value which can ensure stable transmission of ZigBee. If the detected value is out of the range of threshold, system will prompt up warning message which can be used to hint user to add ZigBee reply between the original ZigBee node and ZigBee gateway.
The Internet of Things (IoT) provides transparent and seamless incorporation of heterogeneous and different end systems. It has been widely used in many applications such as smart homes. However, people may resist the IOT as long as there is no public confidence that it will not cause any serious threats to their privacy. Effective secure key management for things authentication is the prerequisite of security operations. In this paper, we present an interactive key management protocol and a non-interactive key management protocol to minimize the communication cost of the things. The security analysis show that the proposed schemes are resilient to various types of attacks.