Can deep learning save us and itself from the avalanche of threats in cyberspace?

How to model and encode the semantics of human-written text and select the type of neural network to process it are not settled issues in sentiment analysis. Accuracy and transferability are critical issues in machine learning in general and are closely related to the viability the trained model. I present a computationally-efficient and accurate feedforward neural network for sentiment prediction capable of maintaining high transfer accuracy when coupled with an effective semantics model of the text. Experimental results on representative benchmark datasets and comparisons to other methods show the advantages of the new approach. Applications to security validation programs are discussed.

Leveraging Side-channel Information for Disassembly and Security.

With the rise of Internet of Things (IoT), devices such as smartphones, embedded medical devices, smart home appliances as well as traditional computing platforms such as personal computers and servers have been increasingly targeted with a variety of cyber attacks. Due to limited hardware resources for embedded devices and difficulty in wide-coverage and on-time software updates, software-only cyber defense techniques, such as traditional anti-virus and malware detectors, do not offer a silver-bullet solution. Hardware-based security monitoring and protection techniques, therefore, have gained significant attention. Monitoring devices using side channel leakage information, e.g. power supply variation and electromagnetic (EM) radiation, is a promising avenue that promotes multiple directions in security and trust applications. In this paper, we provide a taxonomy of hardware-based monitoring techniques against different cyber and hardware attacks, highlight the potentials and unique challenges, and display how power-based side-channel instruction-level monitoring can offer suitable solutions to prevailing embedded device security issues. Further, we delineate approaches for future research directions.

Electronics Supply Chain Integrity Enabled by Blockchain.

Electronic systems are ubiquitous today, playing an irreplaceable role in our personal lives as well as in critical infrastructures such as power grid, satellite communication, and public transportation. In the past few decades, the security of software running on these systems has received significant attention. However, hardware has been assumed to be trustworthy and reliable "by default" without really analyzing the vulnerabilities in the electronics supply chain. With the rapid globalization of the semiconductor industry, it has become challenging to ensure the integrity and security of hardware. In this paper, we discuss the integrity concerns associated with a globalized electronics supply chain. More specifically, we divide the supply chain into six distinct entities: IP owner/foundry (OCM), distributor, assembler, integrator, end user, and electronics recycler, and analyze the vulnerabilities and threats associated with each stage. To address the concerns of the supply chain integrity, we propose a blockchain-based certificate authority framework that can be used to manage critical chip information such as electronic chip identification (ECID), chip grade, transaction time, etc. The decentralized nature of the proposed framework can mitigate most threats of the electronics supply chain, such as recycling, remarking, cloning, and overproduction.

Psst, Can You Keep a Secret?

The security of encrypted data depends not only on the theoretical properties of cryptographic primitives but also on the robustness of their implementations in software and hardware. Threshold cryptography introduces a computational paradigm that enables higher assurance for such implementations.

Entropy-as-a-Service: Unlocking the Full Potential of Cryptography.

Securing the Internet requires strong cryptography, which depends on the availability of good entropy for generating unpredictable keys and accurate clocks. Attacks abusing weak keys or old inputs portend challenges for the Internet. EaaS is a novel architecture providing entropy and timestamps from a decentralized root of trust, scaling gracefully across diverse geopolitical locales and remaining trustworthy unless much of the collective is compromised.