Presentaciones Usenix 2018
La 27 edición de la conferencia sobre seguridad USENIX 2018 se acaba de celebrar en Baltimore, MD esta pasada semana. Lo que característica a esta conferencia es que es una conferencia sobre seguridad desde ámbito académico.
El número de presentaciones es bastante amplio y ya podemos acceder tanto a la investigación académica, así, como las diapositivas de la mayoría de dichas presentaciones:
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Why Do Keynote Speakers Keep Suggesting That Improving Security Is Possible? Keynote
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Fear the Reaper: Characterization and Fast Detection of Card Skimmers
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BlackIoT: IoT Botnet of High Wattage Devices Can Disrupt the Power Grid
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CommanderSong: A Systematic Approach for Practical Adversarial Voice Recognition
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HeapHopper: Bringing Bounded Model Checking to Heap Implementation Security
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Fp-Scanner: The Privacy Implications of Browser Fingerprint Inconsistencies
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Who Left Open the Cookie Jar? A Comprehensive Evaluation of Third-Party Cookie Policies
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Effective Detection of Multimedia Protocol Tunneling using Machine Learning
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Quack: Scalable Remote Measurement of Application-Layer Censorship
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Better managed than memorized? Studying the Impact of Managers on Password Strength and Reuse
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The Rewards and Costs of Stronger Passwords in a University: Linking Password Lifetime to Strength
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Rethinking Access Control and Authentication for the Home Internet of Things (IoT)
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ATtention Spanned: Comprehensive Vulnerability Analysis of AT Commands Within the Android Ecosystem
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Charm: Facilitating Dynamic Analysis of Device Drivers of Mobile Systems
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Inception: System-Wide Security Testing of Real-World Embedded Systems Software
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Acquisitional Rule-based Engine for Discovering Internet-of-Thing Devices
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Donna Dodson, Chief Cybersecurity Advisor, National Institute of Standards and Technology
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Freezing the Web: A Study of ReDoS Vulnerabilities in JavaScript-based Web Servers
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NAVEX: Precise and Scalable Exploit Generation for Dynamic Web Applications
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Rampart: Protecting Web Applications from CPU-Exhaustion Denial-of-Service Attacks
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BurnBox: Self-Revocable Encryption in a World Of Compelled Access
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Unveiling and Quantifying Facebook Exploitation of Sensitive Personal Data for Advertising Purposes
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AttriGuard: A Practical Defense Against Attribute Inference Attacks via Adversarial Machine Learning
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Polisis: Automated Analysis and Presentation of Privacy Policies Using Deep Learning
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Efail: Breaking S/MIME and OpenPGP Email Encryption using Exfiltration Channels
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One&Done: A Single-Decryption EM-Based Attack on OpenSSL’s Constant-Time Blinded RSA
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DATA – Differential Address Trace Analysis: Finding Address-based Side-Channels in Binaries
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Chipmunk or Pepe? Using Acoustical Analysis to Detect Voice-Channel Fraud at Scale
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The Battle for New York: A Case Study of Applied Digital Threat Modeling at the Enterprise Level
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SAQL: A Stream-based Query System for Real-Time Abnormal System Behavior Detection
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MoonShine: Optimizing OS Fuzzer Seed Selection with Trace Distillation
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QSYM : A Practical Concolic Execution Engine Tailored for Hybrid Fuzzing
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FUZE: Towards Facilitating Exploit Generation for Kernel Use-After-Free Vulnerabilities
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The Broken Shield: Measuring Revocation Effectiveness in the Windows Code-Signing PKI
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Debloating Software through Piece-Wise Compilation and Loading
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Understanding the Reproducibility of Crowd-reported Security Vulnerabilities
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Malicious Management Unit: Why Stopping Cache Attacks in Software is Harder Than You Think
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Translation Leak-aside Buffer: Defeating Cache Side-channel Protections with TLB Attacks
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Foreshadow: Extracting the Keys to the Intel SGX Kingdom with Transient Out-of-Order Execution
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Plug and Prey? Measuring the Commoditization of Cybercrime via Online Anonymous Markets
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Schrödinger’s RAT: Profiling the Stakeholders in the Remote Access Trojan Ecosystem
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The aftermath of a crypto-ransomware attack at a large academic institution
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From Spam to Speech: Policing the Next Generation of “Unwanted Traffic”
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Amit Elazari Bar On, Doctoral Candidate, Berkeley Law, Center for Long-Term Cybersecurity Grantee
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We Still Don’t Have Secure Cross-Domain Requests: an Empirical Study of CORS
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End-Users Get Maneuvered: Empirical Analysis of Redirection Hijacking in Content Delivery Networks
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SAD THUG: Structural Anomaly Detection for Transmissions of High-value Information Using Graphics
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FANCI : Feature-based Automated NXDomain Classification and Intelligence
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An Empirical Study of Web Resource Manipulation in Real-world Mobile Applications
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Fast and Service-preserving Recovery from Malware Infections Using CRIU
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Susan Landau, Bridge Professor of Cyber Security and Policy, Tufts University
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The Guard’s Dilemma: Efficient Code-Reuse Attacks Against Intel SGX
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A Bad Dream: Subverting Trusted Platform Module While You Are Sleeping
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Discovering Flaws in Security-Focused Static Analysis Tools for Android using Systematic Mutation
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With Great Training Comes Great Vulnerability: Practical Attacks against Transfer Learning
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When Does Machine Learning FAIL? Generalized Transferability for Evasion and Poisoning Attacks
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teEther: Gnawing at Ethereum to Automatically Exploit Smart Contracts
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Enter the Hydra: Towards Principled Bug Bounties and Exploit-Resistant Smart Contracts
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Erays: Reverse Engineering Ethereum’s Opaque Smart Contracts
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DelegaTEE: Brokered Delegation Using Trusted Execution Environments
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Security Namespace: Making Linux Security Frameworks Available to Containers
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Vetting Single Sign-On SDK Implementations via Symbolic Reasoning
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WPSE: Fortifying Web Protocols via Browser-Side Security Monitoring
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Man-in-the-Machine: Exploiting Ill-Secured Communication Inside the Computer
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All Your GPS Are Belong To Us: Towards Stealthy Manipulation of Road Navigation Systems
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Modelling and Analysis of a Hierarchy of Distance Bounding Attacks
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Off-Path TCP Exploit: How Wireless Routers Can Jeopardize Your Secrets
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Formal Security Analysis of Neural Networks using Symbolic Intervals
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Turning Your Weakness Into a Strength: Watermarking Deep Neural Networks by Backdooring
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A4NT: Author Attribute Anonymity by Adversarial Training of Neural Machine Translation
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GAZELLE: A Low Latency Framework for Secure Neural Network Inference
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FlowCog: Context-aware Semantics Extraction and Analysis of Information Flow Leaks in Android Apps
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Enabling Refinable Cross-Host Attack Investigation with Efficient Data Flow Tagging and Tracking
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Dependence-Preserving Data Compaction for Scalable Forensic Analysis
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