471 research outputs found
Practical Volume-Based Attacks on Encrypted Databases
Recent years have seen an increased interest towards strong security
primitives for encrypted databases (such as oblivious protocols), that hide the
access patterns of query execution, and reveal only the volume of results.
However, recent work has shown that even volume leakage can enable the
reconstruction of entire columns in the database. Yet, existing attacks rely on
a set of assumptions that are unrealistic in practice: for example, they (i)
require a large number of queries to be issued by the user, or (ii) assume
certain distributions on the queries or underlying data (e.g., that the queries
are distributed uniformly at random, or that the database does not contain
missing values).
In this work, we present new attacks for recovering the content of individual
user queries, assuming no leakage from the system except the number of results
and avoiding the limiting assumptions above. Unlike prior attacks, our attacks
require only a single query to be issued by the user for recovering the
keyword. Furthermore, our attacks make no assumptions about the distribution of
issued queries or the underlying data. Instead, our key insight is to exploit
the behavior of real-world applications.
We start by surveying 11 applications to identify two key characteristics
that can be exploited by attackers: (i) file injection, and (ii) automatic
query replay. We present attacks that leverage these two properties in concert
with volume leakage, independent of the details of any encrypted database
system. Subsequently, we perform an attack on the real Gmail web client by
simulating a server-side adversary. Our attack on Gmail completes within a
matter of minutes, demonstrating the feasibility of our techniques. We also
present three ancillary attacks for situations when certain mitigation
strategies are employed.Comment: IEEE EuroS&P 202
DIFFERENTIALLY PRIVATE TRAFFIC PADDING FOR WEB APPLICATIONS
The wide adoption of Web applications in various sectors of our society, such as government, finance, education, health care, media, etc., has implicitly introduced new security
challenges. Among such challenges are side channel attacks that may disclose private user inputs from encrypted raffic. Such attacks might have a serious impact upon user privacy in such applications. In this thesis, we propose a new concept and algorithms that can preserve user privacy in Web applications. In order to achieve this, we define a new privacy
model based on a well known concept, namely, differential privacy. The intent is to make
padded traffic differentially private such that adversaries cannot infer private user inputs
even when they possess prior knowlege about such inputs. At the same time, we intent
to achieve a balance bewteen privacy and the incurred communication overhead. In order
to demonstrate the usefulness of our model, we implement the proposed algorithms and
conduct experiments based on data collected from well known Web applications
Ensuring compliance with data privacy and usage policies in online services
Online services collect and process a variety of sensitive personal data that is subject to complex privacy and usage policies. Complying with the policies is critical, often legally binding for service providers, but it is challenging as applications are prone to many disclosure threats. We present two compliance systems, Qapla and Pacer, that ensure efficient policy compliance in the face of direct and side-channel disclosures, respectively. Qapla prevents direct disclosures in database-backed applications (e.g., personnel management systems), which are subject to complex access control, data linking, and aggregation policies. Conventional methods inline policy checks with application code. Qapla instead specifies policies directly on the database and enforces them in a database adapter, thus separating compliance from the application code. Pacer prevents network side-channel leaks in cloud applications. A tenant’s secrets may leak via its network traffic shape, which can be observed at shared network links (e.g., network cards, switches). Pacer implements a cloaked tunnel abstraction, which hides secret-dependent variation in tenant’s traffic shape, but allows variations based on non-secret information, enabling secure and efficient use of network resources in the cloud. Both systems require modest development efforts, and incur moderate performance overheads, thus demonstrating their usability.Onlinedienste sammeln und verarbeiten eine Vielzahl sensibler persönlicher Daten, die komplexen Datenschutzrichtlinien unterliegen. Die Einhaltung dieser Richtlinien ist häufig rechtlich bindend für Dienstanbieter und gleichzeitig eine Herausforderung, da Fehler in Anwendungsprogrammen zu einer unabsichtlichen Offenlegung führen können. Wir präsentieren zwei Compliance-Systeme, Qapla und Pacer, die Richtlinien effizient einhalten und gegen direkte und indirekte Offenlegungen durch Seitenkanäle schützen. Qapla verhindert direkte Offenlegungen in datenbankgestützten Anwendungen. Herkömmliche Methoden binden Richtlinienprüfungen in Anwendungscode ein. Stattdessen gibt Qapla Richtlinien direkt in der Datenbank an und setzt sie in einem Datenbankadapter durch. Die Konformität ist somit vom Anwendungscode getrennt. Pacer verhindert Netzwerkseitenkanaloffenlegungen in Cloud-Anwendungen. Geheimnisse eines Nutzers können über die Form des Netzwerkverkehr offengelegt werden, die bei gemeinsam genutzten Netzwerkelementen (z. B. Netzwerkkarten, Switches) beobachtet werden kann. Pacer implementiert eine Tunnelabstraktion, die Geheimnisse im Netzwerkverkehr des Nutzers verbirgt, jedoch Variationen basier- end auf nicht geheimen Informationen zulässt und eine sichere und effiziente Nutzung der Netzwerkressourcen in der Cloud ermöglicht. Beide Systeme erfordern geringen Entwicklungsaufwand und verursachen einen moderaten Leistungsaufwand, wodurch ihre Nützlichkeit demonstriert wird
Padding Ain't Enough: Assessing the Privacy Guarantees of Encrypted DNS
DNS over TLS (DoT) and DNS over HTTPS (DoH) encrypt DNS to guard user privacy
by hiding DNS resolutions from passive adversaries. Yet, past attacks have
shown that encrypted DNS is still sensitive to traffic analysis. As a
consequence, RFC 8467 proposes to pad messages prior to encryption, which
heavily reduces the characteristics of encrypted traffic. In this paper, we
show that padding alone is insufficient to counter DNS traffic analysis. We
propose a novel traffic analysis method that combines size and timing
information to infer the websites a user visits purely based on encrypted and
padded DNS traces. To this end, we model DNS sequences that capture the
complexity of websites that usually trigger dozens of DNS resolutions instead
of just a single DNS transaction. A closed world evaluation based on the Alexa
top-10k websites reveals that attackers can deanonymize at least half of the
test traces in 80.2% of all websites, and even correctly label all traces for
32.0% of the websites. Our findings undermine the privacy goals of
state-of-the-art message padding strategies in DoT/DoH. We conclude by showing
that successful mitigations to such attacks have to remove the entropy of
inter-arrival timings between query responses
A Critical Analysis of Payload Anomaly-Based Intrusion Detection Systems
Examining payload content is an important aspect of network security, particularly in today\u27s volatile computing environment. An Intrusion Detection System (IDS) that simply analyzes packet header information cannot adequately secure a network from malicious attacks. The alternative is to perform deep-packet analysis using n-gram language parsing and neural network technology. Self Organizing Map (SOM), PAYL over Self-Organizing Maps for Intrusion Detection (POSEIDON), Anomalous Payload-based Network Intrusion Detection (PAYL), and Anagram are next-generation unsupervised payload anomaly-based IDSs. This study examines the efficacy of each system using the design-science research methodology. A collection of quantitative data and qualitative features exposes their strengths and weaknesses
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