arXiv subjects

N. Asokan

Publications and source records attributed to N. Asokan.

At least 73 records · Page 4Linked to original sources

arXiv2019

Text Analysis in Adversarial Settings: Does Deception Leave a Stylistic Trace?

Textual deception constitutes a major problem for online security. Many studies have argued that deceptiveness leaves traces in writing style, which could be detected using text classification techniques. By conducting an extensive literature review of existing empirical work, we demonstrate that while certain linguistic features have been indicative of deception in certain corpora, they fail to generalize across divergent semantic domains. We suggest that deceptiveness as such leaves no content-invariant stylistic trace, and textual similarity measures provide superior means of classifying texts as potentially deceptive. Additionally, we discuss forms of deception beyond semantic content, focusing on hiding author identity by writing style obfuscation. Surveying the literature on both author identification and obfuscation techniques, we conclude that current style transformation methods fail to achieve reliable obfuscation while simultaneously ensuring semantic faithfulness to the original text. We propose that future work in style transformation should pay particular attention to disallowing semantically drastic changes.

cs.CL↗

arXiv2019

DoubleEcho: Mitigating Context-Manipulation Attacks in Copresence Verification

Copresence verification based on context can improve usability and strengthen security of many authentication and access control systems. By sensing and comparing their surroundings, two or more devices can tell whether they are copresent and use this information to make access control decisions. To the best of our knowledge, all context-based copresence verification mechanisms to date are susceptible to context-manipulation attacks. In such attacks, a distributed adversary replicates the same context at the (different) locations of the victim devices, and induces them to believe that they are copresent. In this paper we propose DoubleEcho, a context-based copresence verification technique that leverages acoustic Room Impulse Response (RIR) to mitigate context-manipulation attacks. In DoubleEcho, one device emits a wide-band audible chirp and all participating devices record reflections of the chirp from the surrounding environment. Since RIR is, by its very nature, dependent on the physical surroundings, it constitutes a unique location signature that is hard for an adversary to replicate. We evaluate DoubleEcho by collecting RIR data with various mobile devices and in a range of different locations. We show that DoubleEcho mitigates context-manipulation attacks whereas all other approaches to date are entirely vulnerable to such attacks. DoubleEcho detects copresence (or lack thereof) in roughly 2 seconds and works on commodity devices.

cs.CR↗

arXiv2018

Scalable Byzantine Consensus via Hardware-assisted Secret Sharing

The surging interest in blockchain technology has revitalized the search for effective Byzantine consensus schemes. In particular, the blockchain community has been looking for ways to effectively integrate traditional Byzantine fault-tolerant (BFT) protocols into a blockchain consensus layer allowing various financial institutions to securely agree on the order of transactions. However, existing BFT protocols can only scale to tens of nodes due to their $O(n^2)$ message complexity. In this paper, we propose FastBFT, a fast and scalable BFT protocol. At the heart of FastBFT is a novel message aggregation technique that combines hardware-based trusted execution environments (TEEs) with lightweight secret sharing primitives. Combining this technique with several other optimizations (i.e., optimistic execution, tree topology and failure detection), FastBFT achieves low latency and high throughput even for large scale networks. Via systematic analysis and experiments, we demonstrate that FastBFT has better scalability and performance than previous BFT protocols.

cs.CR↗

arXiv2018

All You Need is "Love": Evading Hate-speech Detection

With the spread of social networks and their unfortunate use for hate speech, automatic detection of the latter has become a pressing problem. In this paper, we reproduce seven state-of-the-art hate speech detection models from prior work, and show that they perform well only when tested on the same type of data they were trained on. Based on these results, we argue that for successful hate speech detection, model architecture is less important than the type of data and labeling criteria. We further show that all proposed detection techniques are brittle against adversaries who can (automatically) insert typos, change word boundaries or add innocuous words to the original hate speech. A combination of these methods is also effective against Google Perspective -- a cutting-edge solution from industry. Our experiments demonstrate that adversarial training does not completely mitigate the attacks, and using character-level features makes the models systematically more attack-resistant than using word-level features.

cs.CL↗

arXiv2018

ASSURED: Architecture for Secure Software Update of Realistic Embedded Devices

Secure firmware update is an important stage in the IoT device life-cycle. Prior techniques, designed for other computational settings, are not readily suitable for IoT devices, since they do not consider idiosyncrasies of a realistic large-scale IoT deployment. This motivates our design of ASSURED, a secure and scalable update framework for IoT. ASSURED includes all stakeholders in a typical IoT update ecosystem, while providing end-to-end security between manufacturers and devices. To demonstrate its feasibility and practicality, ASSURED is instantiated and experimentally evaluated on two commodity hardware platforms. Results show that ASSURED is considerably faster than current update mechanisms in realistic settings.

cs.CR↗

arXiv2018

S-FaaS: Trustworthy and Accountable Function-as-a-Service using Intel SGX

Function-as-a-Service (FaaS) is a recent and already very popular paradigm in cloud computing. The function provider need only specify the function to be run, usually in a high-level language like JavaScript, and the service provider orchestrates all the necessary infrastructure and software stacks. The function provider is only billed for the actual computational resources used by the function invocation. Compared to previous cloud paradigms, FaaS requires significantly more fine-grained resource measurement mechanisms, e.g. to measure compute time and memory usage of a single function invocation with sub-second accuracy. Thanks to the short duration and stateless nature of functions, and the availability of multiple open-source frameworks, FaaS enables non-traditional service providers e.g. individuals or data centers with spare capacity. However, this exacerbates the challenge of ensuring that resource consumption is measured accurately and reported reliably. It also raises the issues of ensuring computation is done correctly and minimizing the amount of information leaked to service providers. To address these challenges, we introduce S-FaaS, the first architecture and implementation of FaaS to provide strong security and accountability guarantees backed by Intel SGX. To match the dynamic event-driven nature of FaaS, our design introduces a new key distribution enclave and a novel transitive attestation protocol. A core contribution of S-FaaS is our set of resource measurement mechanisms that securely measure compute time inside an enclave, and actual memory allocations. We have integrated S-FaaS into the popular OpenWhisk FaaS framework. We evaluate the security of our architecture, the accuracy of our resource measurement mechanisms, and the performance of our implementation, showing that our resource measurement mechanisms add less than 6.3% latency on standardized benchmarks.

cs.CR↗

arXiv2018

Stay On-Topic: Generating Context-specific Fake Restaurant Reviews

Automatically generated fake restaurant reviews are a threat to online review systems. Recent research has shown that users have difficulties in detecting machine-generated fake reviews hiding among real restaurant reviews. The method used in this work (char-LSTM ) has one drawback: it has difficulties staying in context, i.e. when it generates a review for specific target entity, the resulting review may contain phrases that are unrelated to the target, thus increasing its detectability. In this work, we present and evaluate a more sophisticated technique based on neural machine translation (NMT) with which we can generate reviews that stay on-topic. We test multiple variants of our technique using native English speakers on Amazon Mechanical Turk. We demonstrate that reviews generated by the best variant have almost optimal undetectability (class-averaged F-score 47%). We conduct a user study with skeptical users and show that our method evades detection more frequently compared to the state-of-the-art (average evasion 3.2/4 vs 1.5/4) with statistical significance, at level α = 1% (Section 4.3). We develop very effective detection tools and reach average F-score of 97% in classifying these. Although fake reviews are very effective in fooling people, effective automatic detection is still feasible.

cs.CR↗

arXiv2018

Keys in the Clouds: Auditable Multi-device Access to Cryptographic Credentials

Personal cryptographic keys are the foundation of many secure services, but storing these keys securely is a challenge, especially if they are used from multiple devices. Storing keys in a centralized location, like an Internet-accessible server, raises serious security concerns (e.g. server compromise). Hardware-based Trusted Execution Environments (TEEs) are a well-known solution for protecting sensitive data in untrusted environments, and are now becoming available on commodity server platforms. Although the idea of protecting keys using a server-side TEE is straight-forward, in this paper we validate this approach and show that it enables new desirable functionality. We describe the design, implementation, and evaluation of a TEE-based Cloud Key Store (CKS), an online service for securely generating, storing, and using personal cryptographic keys. Using remote attestation, users receive strong assurance about the behaviour of the CKS, and can authenticate themselves using passwords while avoiding typical risks of password-based authentication like password theft or phishing. In addition, this design allows users to i) define policy-based access controls for keys; ii) delegate keys to other CKS users for a specified time and/or a limited number of uses; and iii) audit all key usages via a secure audit log. We have implemented a proof of concept CKS using Intel SGX and integrated this into GnuPG on Linux and OpenKeychain on Android. Our CKS implementation performs approximately 6,000 signature operations per second on a single desktop PC. The latency is in the same order of magnitude as using locally-stored keys, and 20x faster than smart cards.

cs.CR↗

arXiv2018

SafeKeeper: Protecting Web Passwords using Trusted Execution Environments

Passwords are undoubtedly the most dominant user authentication mechanism on the web today. Although they are inexpensive and easy-to-use, security concerns of password-based authentication are serious. Phishing and theft of password databases are two critical concerns. The tendency of users to re-use passwords across different services exacerbates the impact of these two concerns. Current solutions addressing these concerns are not fully satisfactory: they typically address only one of the two concerns; they do not protect passwords from rogue servers; they do not provide any verifiable evidence of their (server-side) adoption to users; and they face deployability challenges in terms of the cost for service providers and/or ease-of-use for end users. We present SafeKeeper, a comprehensive approach to protect the confidentiality of passwords in web authentication systems. Unlike previous approaches, SafeKeeper protects user passwords against very strong adversaries, including rogue servers and sophisticated external phishers. It is relatively inexpensive to deploy as it (i) uses widely available hardware security mechanisms like Intel SGX, (ii) is integrated into popular web platforms like WordPress, and (iii) has small performance overhead. We describe a variety of challenges in designing and implementing such a system, and how we overcome them. Through an 86-participant user study, and systematic analysis and experiments, we demonstrate the usability, security and deployability of SafeKeeper, which is available as open-source.

cs.CR↗

arXiv2018

Migrating SGX Enclaves with Persistent State

Hardware-supported security mechanisms like Intel Software Guard Extensions (SGX) provide strong security guarantees, which are particularly relevant in cloud settings. However, their reliance on physical hardware conflicts with cloud practices, like migration of VMs between physical platforms. For instance, the SGX trusted execution environment (enclave) is bound to a single physical CPU. Although prior work has proposed an effective mechanism to migrate an enclave's data memory, it overlooks the migration of persistent state, including sealed data and monotonic counters; the former risks data loss whilst the latter undermines the SGX security guarantees. We show how this can be exploited to mount attacks, and then propose an improved enclave migration approach guaranteeing the consistency of persistent state. Our software-only approach enables migratable sealed data and monotonic counters, maintains all SGX security guarantees, minimizes developer effort, and incurs negligible performance overhead.

cs.CR↗

arXiv2018

HardScope: Thwarting DOP with Hardware-assisted Run-time Scope Enforcement

Widespread use of memory unsafe programming languages (e.g., C and C++) leaves many systems vulnerable to memory corruption attacks. A variety of defenses have been proposed to mitigate attacks that exploit memory errors to hijack the control flow of the code at run-time, e.g., (fine-grained) randomization or Control Flow Integrity. However, recent work on data-oriented programming (DOP) demonstrated highly expressive (Turing-complete) attacks, even in the presence of these state-of-the-art defenses. Although multiple real-world DOP attacks have been demonstrated, no efficient defenses are yet available. We propose run-time scope enforcement (RSE), a novel approach designed to efficiently mitigate all currently known DOP attacks by enforcing compile-time memory safety constraints (e.g., variable visibility rules) at run-time. We present HardScope, a proof-of-concept implementation of hardware-assisted RSE for the new RISC-V open instruction set architecture. We discuss our systematic empirical evaluation of HardScope which demonstrates that it can mitigate all currently known DOP attacks, and has a real-world performance overhead of 3.2% in embedded benchmarks.

cs.CR↗

arXiv2017

Towards Linux Kernel Memory Safety

The security of billions of devices worldwide depends on the security and robustness of the mainline Linux kernel. However, the increasing number of kernel-specific vulnerabilities, especially memory safety vulnerabilities, shows that the kernel is a popular and practically exploitable target. Two major causes of memory safety vulnerabilities are reference counter overflows (temporal memory errors) and lack of pointer bounds checking (spatial memory errors). To succeed in practice, security mechanisms for critical systems like the Linux kernel must also consider performance and deployability as critical design objectives. We present and systematically analyze two such mechanisms for improving memory safety in the Linux kernel: (a) an overflow-resistant reference counter data structure designed to accommodate typical reference counter usage in kernel source code, and (b) runtime pointer bounds checking using Intel MPX in the kernel.

cs.CR↗

arXiv2017

Practical Attacks Against Privacy and Availability in 4G/LTE Mobile Communication Systems

Mobile communication systems now constitute an essential part of life throughout the world. Fourth generation "Long Term Evolution" (LTE) mobile communication networks are being deployed. The LTE suite of specifications is considered to be significantly better than its predecessors not only in terms of functionality but also with respect to security and privacy for subscribers. We carefully analyzed LTE access network protocol specifications and uncovered several vulnerabilities. Using commercial LTE mobile devices in real LTE networks, we demonstrate inexpensive, and practical attacks exploiting these vulnerabilities. Our first class of attacks consists of three different ways of making an LTE device leak its location: A semi-passive attacker can locate an LTE device within a 2 sq.km area within a city whereas an active attacker can precisely locate an LTE device using GPS co-ordinates or trilateration via cell-tower signal strength information. Our second class of attacks can persistently deny some or all services to a target LTE device. To the best of our knowledge, our work constitutes the first publicly reported practical attacks against LTE access network protocols. We present several countermeasures to resist our specific attacks. We also discuss possible trade-offs that may explain why these vulnerabilities exist and recommend that safety margins introduced into future specifications to address such trade-offs should incorporate greater agility to accommodate subsequent changes in the trade-off equilibrium.

cs.CR↗

arXiv2017

CFI CaRE: Hardware-supported Call and Return Enforcement for Commercial Microcontrollers

With the increasing scale of deployment of Internet of Things (IoT), concerns about IoT security have become more urgent. In particular, memory corruption attacks play a predominant role as they allow remote compromise of IoT devices. Control-flow integrity (CFI) is a promising and generic defense technique against these attacks. However, given the nature of IoT deployments, existing protection mechanisms for traditional computing environments (including CFI) need to be adapted to the IoT setting. In this paper, we describe the challenges of enabling CFI on microcontroller (MCU) based IoT devices. We then present CaRE, the first interrupt-aware CFI scheme for low-end MCUs. CaRE uses a novel way of protecting the CFI metadata by leveraging TrustZone-M security extensions introduced in the ARMv8-M architecture. Its binary instrumentation approach preserves the memory layout of the target MCU software, allowing pre-built bare-metal binary code to be protected by CaRE. We describe our implementation on a Cortex-M Prototyping System and demonstrate that CaRE is secure while imposing acceptable performance and memory impact.

cs.CR↗

arXiv2017

LO-FAT: Low-Overhead Control Flow ATtestation in Hardware

Attacks targeting software on embedded systems are becoming increasingly prevalent. Remote attestation is a mechanism that allows establishing trust in embedded devices. However, existing attestation schemes are either static and cannot detect control-flow attacks, or require instrumentation of software incurring high performance overheads. To overcome these limitations, we present LO-FAT, the first practical hardware-based approach to control-flow attestation. By leveraging existing processor hardware features and commonly-used IP blocks, our approach enables efficient control-flow attestation without requiring software instrumentation. We show that our proof-of-concept implementation based on a RISC-V SoC incurs no processor stalls and requires reasonable area overhead.

cs.CR↗

arXiv2017

Profiling Users by Modeling Web Transactions

Users of electronic devices, e.g., laptop, smartphone, etc. have characteristic behaviors while surfing the Web. Profiling this behavior can help identify the person using a given device. In this paper, we introduce a technique to profile users based on their web transactions. We compute several features extracted from a sequence of web transactions and use them with one-class classification techniques to profile a user. We assess the efficacy and speed of our method at differentiating 25 users on a dataset representing 6 months of web traffic monitoring from a small company network.

cs.CR↗

arXiv2017

STASH: Securing transparent authentication schemes using prover-side proximity verification

Transparent authentication (TA) schemes are those in which a user is authenticated by a verifier without requiring explicit user interaction. By doing so, those schemes promise high usability and security simultaneously. The majority of TA implementations rely on the received signal strength as an indicator for the proximity of a user device (prover). However, such implicit proximity verification is not secure against an adversary who can relay messages over a larger distance. In this paper, we propose a novel approach for thwarting relay attacks in TA schemes: the prover permits access to authentication credentials only if it can confirm that it is near the verifier. We present STASH, a system for relay-resilient transparent authentication in which the prover does proximity verification by comparing its approach trajectory towards the intended verifier with known authorized reference trajectories. Trajectories are measured using low-cost sensors commonly available on personal devices. We demonstrate the security of STASH against a class of adversaries and its ease-of-use by analyzing empirical data, collected using a STASH prototype. STASH is efficient and can be easily integrated to complement existing TA schemes.

cs.CR↗

arXiv2017

SELint: an SEAndroid policy analysis tool

SEAndroid enforcement is now mandatory for Android devices. In order to provide the desired level of security for their products, Android OEMs need to be able to minimize their mistakes in writing SEAndroid policies. However, existing SEAndroid and SELinux tools are not very useful for this purpose. It has been shown that SEAndroid policies found in commercially available devices for multiple manufacturers contain mistakes and redundancies. In this paper we present a new tool, SELint, which aims to help OEMs to produce better SEAndroid policies. SELint is extensible and configurable to suit the needs of different OEMs. It is provided with a default configuration based on the AOSP SEAndroid policy, but can be customized by OEMs.

cs.CR↗