ﻻ يوجد ملخص باللغة العربية
In todays integrated circuit (IC) ecosystem, owning a foundry is not economically viable, and therefore most IC design houses are now working under a fabless business model. In order to overcome security concerns associated with the outsorcing of IC fabrication, the Split Manufacturing technique was proposed. In Split Manufacturing, the Front End of Line (FEOL) layers (transistors and lower metal layers) are fabricated at an untrusted high-end foundry, while the Back End of Line (BEOL) layers (higher metal layers) are manufactured at a trusted low-end foundry. This approach hides the BEOL connections from the untrusted foundry, thus preventing overproduction and piracy threats. However, many works demonstrate that BEOL connections can be derived by exploiting layout characteristics that are introduced by heuristics employed in typical floorplanning, placement, and routing algorithms. Since straightforward Split Manufacturing may not afford a desirable security level, many authors propose defense techniques to be used along with Split Manufacturing. In our survey, we present a detailed overview of the technique, the many types of attacks towards Split Manufacturing, as well as possible defense techniques described in the literature. For the attacks, we present a concise discussion on the different threat models and assumptions, while for the defenses we classify the studies into three categories: proximity perturbation, wire lifting, and layout obfuscation. The main outcome of our survey is to highlight the discrepancy between many studies -- some claim netlists can be reconstructed with near perfect precision, while others claim marginal success in retrieving BEOL connections. Finally, we also discuss future trends and challenges inherent to Split Manufacturing, including the fundamental difficulty of evaluating the efficiency of the technique.
Deep Neural Network (DNN), one of the most powerful machine learning algorithms, is increasingly leveraged to overcome the bottleneck of effectively exploring and analyzing massive data to boost advanced scientific development. It is not a surprise t
Additive manufacturing (AM) is growing as fast as anyone can imagine, and it is now a multi-billion-dollar industry. AM becomes popular in a variety of sectors, such as automotive, aerospace, biomedical, and pharmaceutical, for producing parts/ compo
Malware remains a big threat to cyber security, calling for machine learning based malware detection. While promising, such detectors are known to be vulnerable to evasion attacks. Ensemble learning typically facilitates countermeasures, while attack
Nowadays, the usage of smartphones and their applications have become rapidly increasing popular in peoples daily life. Over the last decade, availability of mobile money services such as mobile-payment systems and app markets have significantly incr
Anonymity networks are becoming increasingly popular in todays online world as more users attempt to safeguard their online privacy. Tor is currently the most popular anonymity network in use and provides anonymity to both users and services (hidden