March 09 ~ 10, 2024, Virtual Conference
Chandram Karri, Shravya Karri, Chandra rao, Venkatesh Kummari, and R.Y. Tedf, CMD, CSA research and Training Pvt Ltd, Hyderabad, INDIA
This article discusses current improvements in Blockchain technology for the Internet of Things (IoT). Blockchain is an exciting and groundbreaking technology. It is linked to cryptocurrencies and nonfungible tokens (NFTs). Blockchain technology has matured into a management solution for many types of global enterprises. In general, the blockchain can be thought of as a digital distributed database. Blockchain enables all IoT devices to improve security and transparency in their interconnected ecosystems. On the blockchain, sensitive user data such as biometrics, voice recognition, and facial recognition are kept. When data is saved on the blockchain, it becomes unchangeable and only a few people have access to it.
Blockchain Technology, Internet of things, Blockchain enabled IOT and Industrial applications.
Paul Addai1, Pedro Pinto2, and Tauheed Khan Mohd3, 1Dept of Math and Computer Science, Augustana College, Rock Island, Illinois, USA, 2Department of Electrical and Computer Eng, Instituto Politécnico de Viana do Castelo (IPVC), PT, Viana do Castelo, Portugal, 3School of Information Security and Applied Computing, Eastern Michigan University, Ypsilanti, Michigan, USA
Exploring and Identifying Anomalies in time-series data is very crucial in today’s world revolve around data. These data are being used to make important decisions; hence, an efficient and reliable anomaly detection system should be involved in this process to ensure that the best decisions are being made. The paper explores other types of anomalies and proposes efficient detection methods which can be used. Anomalies are patterns that deviate from usual expected behavior. These can come from system failures or unexpected activity. This research paper explores the vulnerabilities of commonly used anomaly detection algorithms such as the Z-Score and static threshold approach. Each method used in this paper has its unique capabilities and limitations. These methods range from using statistical methods and machine learning approaches to detecting anomalies in a time-series dataset. Furthermore, this paper explores other open-source libraries that can be used to detect anomalies, such as Greykite and Prophet Python library. This paper serves as a good source for anyone new to anomaly detection and willing to explore.
anomaly, forecasting, time series, data, libraries, machine learning.
Nuha Sabek, Joseph Loftus, Kati Sneath, Spencer Ames, and Tauheed Khan Mohd, School of Information Security and Applied Computing, Eastern Michigan University, Ypsilanti, Michigan, USA
The integration of wireless interfaces into vehicles has posed some challenges for the automotive industry over the years. While manufacturers strive to impress consumers with cutting-edge features, these features also bring security risks that cannot be ignored. To prevent potentially fatal incidents, a thorough protocol must be established to address system vulnerabilities. As the modern century moves towards an era of autonomous vehicles, security must be a top priority to avoid compliance breaches and delays in feature development. The significance of vehicle interfaces in the modern automotive industry cannot be overstated. The present study aims to explore the prospective advantages and challenges associated with the integration of wireless interfaces in the automotive industry. This analysis will primarily focus on the latest technological advancements in vehicle technology and the critical need to secure against possible cyber-attacks. A wide range of topics will be covered in this paper, from the evolution of vehicle interfaces to the industry’s hurdles and strategies to minimize the risks associated with cyber threats. The objective of this study is to provide a comprehensive understanding of wireless interfaces in the automotive sector, including the benefits of implementing such technology, the challenges that it poses, and the measures needed to maintain the security and safety of vehicles, as well as the passengers.
Vehicle Interfaces, Vehicular networks, Evolution of vehicle interfaces, Automotive cybersecurity, vehicle safety, technology of the future.
Brad Chardenet, Jaycen Jamssens, Richard Cummins, and Tauheed Khan Mohd, School of Information Security and Applied Computing, Eastern Michigan University, Ypsilanti, United States
This technical paper investigates the vulnerabilities and potential threats posed by emerging technologies, specifically Bluetoothenabled patient pacemakers. With the advancements in healthcare technology, pacemakers now utilize Bluetooth connectivity for real-time monitoring and data transmission, offering patients and healthcare providers an important convenience. However, this technology also introduces significant security risks, leaving these life-sustaining devices susceptible to malicious attacks. Through an in-depth analysis of existing research, real-life incidents, and vulnerabilities identified by experts in the field, this paper will underscore the critical vulnerabilities present in pacemaker systems. Examples, including findings from researchers such as Billy Rios, Jonathon Butts, and Marie Moe, demonstrate the potential severity of these vulnerabilities. From remote control manipulation to unauthorized access to sensitive medical data, the threats posed by these vulnerabilities are substantial and potentially life-threatening. Moreover, this paper outlines advanced mitigation strategies essential for protecting patient pacemakers against these security risks. Recommendations include end-to-end encryption, whitelist device pairing, intrusion detection systems, and regular firmware updates, highlight the collaborative efforts required from patients, healthcare providers, and manufacturers to mitigate these risks effectively. This paper’s findings underscore the urgent need for robust cybersecurity measures in the design, implementation, and maintenance of pacemaker systems. Addressing these vulnerabilities is key for ensuring patient safety, maintaining privacy, and building trust in healthcare technology. The implications of this research extend beyond pacemaker security, emphasizing the broader importance of cybersecurity in medical devices and the importance of ongoing research and regulatory initiatives to protect patient health. .
Attack Vectors, Pacemaker, Healthcare.
Anas Issa, Adam Schultz, David Renshaw and Tauheed Khan Mohd, ABC Institute, Rupert-Karls-University Heidelberg, Heidelberg, Germany
Integrating drones for package delivery in the logistics industry presents an innovative solution to expedite delivery times while simultaneously introducing a host of intricate challenges relating to security, privacy, network infrastructure, and operational management. The flourishing concept of utilizing IoT devices, particularly drones, in this domain, requires a comprehensive approach to mitigate complex concerns. Addressing these challenges requires a meticulous examination of several central aspects, including the strength of the network infrastructure employed for drone operations. Ensuring the security measures are implemented both onboard the drones and within the network infrastructure is crucial to safeguard against potential vulnerabilities and threats. Moreover, assessing the potential interconnectivity of drones with other IoT devices demands strict security protocols to shore up these interactions, preventing any unauthorized access or breaches. The deployment of cameras on drones introduces a critical aspect of privacy concerns, necessitating strict measures to protect the privacy of individuals within the drone’s vicinity. Additionally, ensuring the physical security of the drones throughout their journey and shielding them from malicious interference constitutes a great deal of consideration. Other essential factors that demand attention encompass the complexities of air traffic management within the drone delivery framework. This paper tackles an in-depth exploration of these challenges, drawing upon authoritative resources such as "Security of IoT Systems," "Agent-Oriented Cooperative Smart Objects," and other relevant references. By critically analyzing these aspects, this study aims to propose viable solutions and strategies to overcome these obstacles and advance the integration of drones for package delivery within the logistics industry.
Internet of Things (IoT), Security, Drones, Wireless networks, Malicious act.
Zhixin Ou1, Chunlan Deng2, 1Anhui Communications Vocational & Technical College, 2Department of Urban Rail Transit and Information Engineering; Hefei, Anhui 230051, china
Because the electric locomotive load has the nonlinear characteristic, the voltage distortion rate (THDH) of traction substation is high and the harmonic is high. Traction load absorbs the fundamental current from the grid, also injected a lot of harmonic current to the grid, generate voltage distortion threat power supply security. By establishing three-phase model of traction substation, collecting different experimental data, Study on voltage distortion rate caused by V/x type traction transformer in power system based on Matlab simulation, modifying parameters by active control fusion algorithm, reasonable control of original parameter model and state. The results show that active control can avoid the high distortion rate of local power grid, voltage flicker and harmonic current exceeding, in improving power quality and grid security effect is obvious.
Traction substation, Active control, Data fusion, V/x type connection model, Matlab Simulation.