Sina Faezi (University of California, Irvine), Sujit Rokka Chhetri (University of California, Irvine), Arnav Vaibhav Malawade (University of California, Irvine), John Charles Chaput (University of California, Irvine), William Grover (University of California, Riverside), Philip Brisk (University of California, Riverside), Mohammad Abdullah Al Faruque (University of California, Irvine)

Synthetic biology is developing into a promising science and engineering field. One of the enabling technologies for this field is the DNA synthesizer. It allows researchers to custom-build sequences of oligonucleotides (short DNA strands) using the nucleobases: Adenine (A), Guanine (G), Cytosine (C), and Thymine (T). Incorporating these sequences into organisms can result in improved disease resistance and lifespan for plants, animals, and humans. Hence, many laboratories spend large amounts of capital researching and developing unique sequences of oligonucleotides. However, these DNA synthesizers are fully automated systems with cyber-domain processes and physical domain components. Hence, they may be prone to security breaches like any other computing system. In our work, we present a novel acoustic side-channel attack methodology which can be used on DNA synthesizers to breach their confidentiality and steal valuable oligonucleotide sequences.
Our proposed attack methodology achieves an average accuracy of 88.07% in predicting each base and is able to reconstruct short sequences with 100% accuracy by making less than 21 guesses out of $4^{15}$ possibilities. We evaluate our attack against the effects of the microphone's distance from the DNA synthesizer and show that our attack methodology can achieve over 80% accuracy when the microphone is placed as far as 0.7 meters from the DNA synthesizer despite the presence of common room noise. In addition, we reconstruct DNA sequences to show how effectively an attacker with biomedical-domain knowledge would be able to derive the intended functionality of the sequence using the proposed attack methodology. To the best of our knowledge, this is the first methodology that highlights the possibility of such an attack on systems used to synthesize DNA molecules.

View More Papers

coucouArray ( [post_type] => ndss-paper [post_status] => publish [posts_per_page] => 4 [orderby] => rand [tax_query] => Array ( [0] => Array ( [taxonomy] => category [field] => id [terms] => Array ( [0] => 34 ) ) ) [post__not_in] => Array ( [0] => 4590 ) )

Distinguishing Attacks from Legitimate Authentication Traffic at Scale

Cormac Herley (Microsoft), Stuart Schechter (Unaffiliated)

Read More

SABRE: Protecting Bitcoin against Routing Attacks

Maria Apostolaki (ETH Zurich), Gian Marti (ETH Zurich), Jan Müller (ETH Zurich), Laurent Vanbever (ETH Zurich)

Read More

ExSpectre: Hiding Malware in Speculative Execution

Jack Wampler (University of Colorado Boulder), Ian Martiny (University of Colorado Boulder), Eric Wustrow (University of Colorado Boulder)

Read More

OBFUSCURO: A Commodity Obfuscation Engine on Intel SGX

Adil Ahmad (Purdue), Byunggill Joe (KAIST), Yuan Xiao (Ohio State University), Yinqian Zhang (Ohio State University), Insik Shin (KAIST), Byoungyoung Lee (Purdue/SNU)

Read More

Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

Vision: Profiling Human Attackers: Personality and Behavioral Patterns in Deceptive Multi-Stage CTF Challenges

Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)