User Monitor & Feedback Mechanism for Social Scientific Study on Laptop Energy Reduction

The dawn of the laptop era presents new challenges to the computing research community. Performance is no longer the end all be all of computing research because a new, significant requirement has cropped up: reducing the power consumption and improving battery usage. The key restriction to mobility is the constant need to be near a power outlet to recharge the laptop battery. Thus, extending battery life without compromising performance is a pressing concern.A research named as iGreen was proposed to stimulate power consumption awareness and behavioral change among laptop users via interactive energy-usage feedback with college students as the initial target group.This project is part of iGreen the project with an objective to analyze the users’ behavioral changes by examining their usage of laptops and their attitude towards the environmental issues for energy consumption. It also tries to find reasoning and provide a social feedback mechanism to improve the efficiency of energy consumption and reduce the waste of power

Remote dynamic partial reconfiguration: A threat to Internet-of-Things and embedded security applications

The advent of the Internet of Things has motivated the use of Field Programmable Gate Array (FPGA) devices with Dynamic Partial Reconfiguration (DPR) capabilities for dynamic non-invasive modifications to circuits implemented on the FPGA. In particular, the ability to perform DPR over the network is essential in the context of a growing number of Internet of Things (IoT)-based and embedded security applications. However, the use of remote DPR brings with it a number of security threats that could lead to potentially catastrophic consequences in practical scenarios. In this paper, we demonstrate four examples where the remote DPR capability of the FPGA may be exploited by an adversary to launch Hardware Trojan Horse (HTH) attacks on commonly used security applications. We substantiate the threat by demonstrating remotely-launched attacks on Xilinx FPGA-based hardware implementations of a cryptographic algorithm, a true random number generator, and two processor-based security applications - namely, a software implementation of a cryptographic algorithm and a cash dispensing scheme. The attacks are launched by on-the-fly transfer of malicious FPGA configuration bitstreams over an Ethernet connection to perform DPR and leak sensitive information. Finally, we comment on plausible countermeasures to prevent such attack

Mitigating Distributed Denial of Service Attacks in an Anonymous Routing Environment: Client Puzzles and Tor

Online intelligence operations use the Internet to gather information on the activities of U.S. adversaries. The security of these operations is paramount, and one way to avoid being linked to the Department of Defense (DoD) is to use anonymous communication systems. One such system, Tor, makes interactive TCP services anonymous. Tor uses the Transport Layer Security (TLS) protocol and is thus vulnerable to a distributed denial-of-service (DDoS) attack that can significantly delay data traversing the Tor network. This research uses client puzzles to mitigate TLS DDoS attacks. A novel puzzle protocol, the Memoryless Puzzle Protocol (MPP), is conceived, implemented, and analyzed for anonymity and DDoS vulnerabilities. Consequently, four new secondary DDoS and anonymity attacks are identified and defenses are proposed. Furthermore, analysis of the MPP identified and resolved two important shortcomings of the generalized client puzzle technique. Attacks that normally induce victim CPU utilization rates of 80-100% are reduced to below 70%. Also, the puzzle implementation allows for user-data latency to be reduced by close to 50% during a large-scale attack .Finally, experimental results show successful mitigation can occur without sending a puzzle to every requesting client. By adjusting the maximum puzzle strength, CPU utilization can be capped at 70% even when an arbitrary client has only a 30% chance of receiving a puzzle

Remote dynamic partial reconfiguration: A threat to Internet-of-Things and embedded security applications

The advent of the Internet of Things has motivated the use of Field Programmable Gate Array (FPGA) devices with Dynamic Partial Reconfiguration (DPR) capabilities for dynamic non-invasive modifications to circuits implemented on the FPGA. In particular, the ability to perform DPR over the network is essential in the context of a growing number of Internet of Things (IoT)-based and embedded security applications. However, the use of remote DPR brings with it a number of security threats that could lead to potentially catastrophic consequences in practical scenarios. In this paper, we demonstrate four examples where the remote DPR capability of the FPGA may be exploited by an adversary to launch Hardware Trojan Horse (HTH) attacks on commonly used security applications. We substantiate the threat by demonstrating remotely-launched attacks on Xilinx FPGA-based hardware implementations of a cryptographic algorithm, a true random number generator, and two processor-based security applications - namely, a software implementation of a cryptographic algorithm and a cash dispensing scheme. The attacks are launched by on-the-fly transfer of malicious FPGA configuration bitstreams over an Ethernet connection to perform DPR and leak sensitive information. Finally, we comment on plausible countermeasures to prevent such attack

Crowdfunding Non-fungible Tokens on the Blockchain

Non-fungible tokens (NFTs) have been used as a way of rewarding content creators. Artists publish their works on the blockchain as NFTs, which they can then sell. The buyer of an NFT then holds ownership of a unique digital asset, which can be resold in much the same way that real-world art collectors might trade paintings. However, while a deal of effort has been spent on selling works of art on the blockchain, very little attention has been paid to using the blockchain as a means of fundraising to help finance the artist’s work in the first place. Additionally, while blockchains like Ethereum are ideal for smaller works of art, additional support is needed when the artwork is larger than is feasible to store on the blockchain. In this paper, we propose a fundraising mechanism that will help artists to gain financial support for their initiatives, and where the backers can receive a share of the profits in exchange for their support. We discuss our prototype implementation using the SpartanGold framework. We then discuss how this system could be expanded to support large NFTs with the 0Chain blockchain, and describe how we could provide support for ongoing storage of these NFTs

Fake Malware Generation Using HMM and GAN

In the past decade, the number of malware attacks have grown considerably and, more importantly, evolved. Many researchers have successfully integrated state-of-the-art machine learning techniques to combat this ever present and rising threat to information security. However, the lack of enough data to appropriately train these machine learning models is one big challenge that is still present. Generative modelling has proven to be very efficient at generating image-like synthesized data that can match the actual data distribution. In this paper, we aim to generate malware samples as opcode sequences and attempt to differentiate them from the real ones with the goal to build fake malware data that can be used to effectively train the machine learning models. We use and compare different Generative Adversarial Networks (GAN) algorithms and Hidden Markov Models (HMM) to generate such fake samples obtaining promising results