No Arabic abstract
Logic locking has emerged as a promising solution for protecting the semiconductor intellectual Property (IP) from the untrusted entities in the design and fabrication process. Logic locking hides the functionality of the IP by embedding additional key-gates in the circuit. The correct output of the chip is produced, once the correct key value is available at the input of the key-gates. The confidentiality of the key is imperative for the security of the locked IP as it stands as the lone barrier against IP infringement. Therefore, the logic locking is considered as a broken scheme once the key value is exposed. The research community has shown the vulnerability of the logic locking techniques against different classes of attacks, such as Oracle-guided and physical attacks. Although several countermeasures have already been proposed against such attacks, none of them is simultaneously impeccable against Oracle-guided, Oracle-less, and physical attacks. Under such circumstances, a defense-in-depth approach can be considered as a practical approach in addressing the vulnerabilities of logic locking. Defense-in-depth is a multilayer defense approach where several independent countermeasures are implemented in the device to provide aggregated protection against different attack vectors. Introducing such a multilayer defense model in logic locking is the major contribution of this paper. With regard to this, we first identify the core components of logic locking schemes, which need to be protected. Afterwards, we categorize the vulnerabilities of core components according to potential threats for the locking key in logic locking schemes. Furthermore, we propose several defense layers and countermeasures to protect the device from those vulnerabilities. Finally, we turn our focus to open research questions and conclude with suggestions for future research directions.
Logic locking is used to protect integrated circuits (ICs) from piracy and counterfeiting. An encrypted IC implements the correct function only when the right key is input. Many existing logic-locking methods are subject to the powerful satisfiability (SAT)-based attack. Recently, an Anti-SAT scheme has been developed. By adopting two complementary logic blocks that consist of AND/NAND trees, it makes the number of iterations needed by the SAT attack exponential to the number of input bits. Nevertheless, the Anti-SAT scheme is vulnerable to the later AppSAT and removal attacks. This paper proposes a generalized (G-)Anti-SAT scheme. Different from the Anti-SAT scheme, a variety of complementary or non-complementary functions can be adopted for the two blocks in our G-Anti-SAT scheme. The Anti-SAT scheme is just a special case of our proposed design. Our design can achieve higher output corruptibility, which is also tunable, so that better resistance to the AppSAT and removal attacks is achieved. Meanwhile, unlike existing AppSAT-resilient designs, our design does not sacrifice the resistance to the SAT attack.
Machine learning with deep neural networks (DNNs) has become one of the foundation techniques in many safety-critical systems, such as autonomous vehicles and medical diagnosis systems. DNN-based systems, however, are known to be vulnerable to adversarial examples (AEs) that are maliciously perturbed variants of legitimate inputs. While there has been a vast body of research to defend against AE attacks in the literature, the performances of existing defense techniques are still far from satisfactory, especially for adaptive attacks, wherein attackers are knowledgeable about the defense mechanisms and craft AEs accordingly. In this work, we propose a multilayer defense-in-depth framework for AE detection, namely MixDefense. For the first layer, we focus on those AEs with large perturbations. We propose to leverage the `noise features extracted from the inputs to discover the statistical difference between natural images and tampered ones for AE detection. For AEs with small perturbations, the inference result of such inputs would largely deviate from their semantic information. Consequently, we propose a novel learning-based solution to model such contradictions for AE detection. Both layers are resilient to adaptive attacks because there do not exist gradient propagation paths for AE generation. Experimental results with various AE attack methods on image classification datasets show that the proposed MixDefense solution outperforms the existing AE detection techniques by a considerable margin.
In dealing with altered visual multimedia content, also referred to as fake news, we present a ready-to-deploy extension of the current public key infrastructure (PKI), to provide an endorsement and integrity check platform for newsworthy visual multimedia content. PKI, which is primarily used for Web domain authentication, can directly be utilized with any visual multimedia file. Unlike many other fake news researches that focus on technical multimedia data processing and verification, we enable various news organizations to use our developed program to certify/endorse a multimedia news content when they believe this news piece is truthiness and newsworthy. Our program digitally signs the multimedia news content with the news organizations private key, and the endorsed news content can be posted not only by the endorser, but also by any other websites. By installing a web browser extension developed by us, an end user can easily verify whether a multimedia news content has been endorsed and by which organization. During verification, our browser extension will present to the end user a floating logo next to the image or video. This logo, in the shape of a shield, will show whether the image has been endorsed, by which news organization, and a few more pieces of essential text information of the news multimedia content. The proposed system can be easily integrated to other closed-web system such as social media networks and easily applied to other non-visual multimedia files.
Services on the public Internet are frequently scanned, then subject to brute-force and denial-of-service attacks. We would like to run such services stealthily, available to friends but hidden from adversaries. In this work, we propose a moving target defense named Chhoyhopper that utilizes the vast IPv6 address space to conceal publicly available services. The client and server to hop to different IPv6 addresses in a pattern based on a shared, pre-distributed secret and the time-of-day. By hopping over a /64 prefix, services cannot be found by active scanners, and passively observed information is useless after two minutes. We demonstrate our system with SSH, and show that it can be extended to other applications.
We propose a new simple emph{trace} logic that can be used to specify emph{local security properties}, i.e. security properties that refer to a single participant of the protocol specification. Our technique allows a protocol designer to provide a formal specification of the desired security properties, and integrate it naturally into the design process of cryptographic protocols. Furthermore, the logic can be used for formal verification. We illustrate the utility of our technique by exposing new attacks on the well studied protocol TMN.