DRONE DELIVERY OF CBNRECy – DEW WEAPONS Emerging Threats of Mini-Weapons of Mass Destruction and Disruption (WMDD)

Drone Delivery of CBNRECy – DEW Weapons: Emerging Threats of Mini-Weapons of Mass Destruction and Disruption (WMDD) is our sixth textbook in a series covering the world of UASs and UUVs. Our textbook takes on a whole new purview for UAS / CUAS/ UUV (drones) – how they can be used to deploy Weapons of Mass Destruction and Deception against CBRNE and civilian targets of opportunity. We are concerned with the future use of these inexpensive devices and their availability to maleficent actors. Our work suggests that UASs in air and underwater UUVs will be the future of military and civilian terrorist operations. UAS / UUVs can deliver a huge punch for a low investment and minimize human casualties.https://newprairiepress.org/ebooks/1046/thumbnail.jp

Transmission gate based dual rail logic for differential power analysis resistant circuits

Cryptographic devices with hardware implementation of the algorithms are increasingly being used in various applications. As a consequence, there is an increased need for security against the attacks on the cryptographic system. Among various attack techniques, side channel attacks pose a significant threat to the hardware implementation. Power analysis attacks are a type of side channel attack where the power leakage from the underlying hardware is used to eavesdrop on the hardware operation. Wave pipelined differential and dynamic logic (WDDL) has been found to be an effective countermeasure to power analysis. This thesis studies the use of transmission gate based WDDL implementation for the differential and dynamic logic. Although WDDL is an effective defense against power analysis, the number of gates needed for the design of a secure implementation is double the number of gates used for non-secure operations. In this thesis we propose transmission gate based structures for implementation of wave pipelined dynamic and differential logic to minimize the overhead of this defense against power analysis attacks. A transmission gate WDDL design methodology is presented, and the design and analysis of a secure multiplier is given. The adder structures are compared in terms of security effectiveness and silicon area overhead for three cases: unsecured logic implementation, standard gate WDDL, and transmission gate WDDL. In simulation, the transmission gate WDDL design is seen to have similar power consumption results compared to the standard gate WDDL; however, the transmission gate based circuit uses 10-50% fewer gates compared to the static WDDL

An Empirical Analysis to Control Product Counterfeiting in the Automotive Industry\u27s Supply Chains in Pakistan

The counterfeits pose significant health and safety threat to consumers. The quality image of firms is vulnerable to the damage caused by the expanding flow of counterfeit products in today’s global supply chains. The counterfeiting markets are swelling due to globalization and customers’ willingness to buy counterfeits, fueling illicit activities to explode further. Buyers look for the original parts are deceived by the false (deceptive) signals’ communication. The counterfeiting market has become a multi-billion industry but lacks detailed insights into the supply side of counterfeiting (deceptive side). The study aims to investigate and assess the relationship between the anti-counterfeiting strategies and improvement in the firm’s supply performance within the internal and external supply chain quality management context in the auto-parts industry’s supply chains in Pakistan

How Physicality Enables Trust: A New Era of Trust-Centered Cyberphysical Systems

Multi-agent cyberphysical systems enable new capabilities in efficiency, resilience, and security. The unique characteristics of these systems prompt a reevaluation of their security concepts, including their vulnerabilities, and mechanisms to mitigate these vulnerabilities. This survey paper examines how advancement in wireless networking, coupled with the sensing and computing in cyberphysical systems, can foster novel security capabilities. This study delves into three main themes related to securing multi-agent cyberphysical systems. First, we discuss the threats that are particularly relevant to multi-agent cyberphysical systems given the potential lack of trust between agents. Second, we present prospects for sensing, contextual awareness, and authentication, enabling the inference and measurement of ``inter-agent trust" for these systems. Third, we elaborate on the application of quantifiable trust notions to enable ``resilient coordination," where ``resilient" signifies sustained functionality amid attacks on multiagent cyberphysical systems. We refer to the capability of cyberphysical systems to self-organize, and coordinate to achieve a task as autonomy. This survey unveils the cyberphysical character of future interconnected systems as a pivotal catalyst for realizing robust, trust-centered autonomy in tomorrow's world

Can LLM-Generated Misinformation Be Detected?

The advent of Large Language Models (LLMs) has made a transformative impact. However, the potential that LLMs such as ChatGPT can be exploited to generate misinformation has posed a serious concern to online safety and public trust. A fundamental research question is: will LLM-generated misinformation cause more harm than human-written misinformation? We propose to tackle this question from the perspective of detection difficulty. We first build a taxonomy of LLM-generated misinformation. Then we categorize and validate the potential real-world methods for generating misinformation with LLMs. Then, through extensive empirical investigation, we discover that LLM-generated misinformation can be harder to detect for humans and detectors compared to human-written misinformation with the same semantics, which suggests it can have more deceptive styles and potentially cause more harm. We also discuss the implications of our discovery on combating misinformation in the age of LLMs and the countermeasures.Comment: The code, dataset and more resources on LLMs and misinformation will be released on the project website: https://llm-misinformation.github.io