30,317 research outputs found
Hidden and Uncontrolled - On the Emergence of Network Steganographic Threats
Network steganography is the art of hiding secret information within innocent
network transmissions. Recent findings indicate that novel malware is
increasingly using network steganography. Similarly, other malicious activities
can profit from network steganography, such as data leakage or the exchange of
pedophile data. This paper provides an introduction to network steganography
and highlights its potential application for harmful purposes. We discuss the
issues related to countering network steganography in practice and provide an
outlook on further research directions and problems.Comment: 11 page
Distributed Information Retrieval using Keyword Auctions
This report motivates the need for large-scale distributed approaches to information retrieval, and proposes solutions based on keyword auctions
Email Babel: Does Language Affect Criminal Activity in Compromised Webmail Accounts?
We set out to understand the effects of differing language on the ability of
cybercriminals to navigate webmail accounts and locate sensitive information in
them. To this end, we configured thirty Gmail honeypot accounts with English,
Romanian, and Greek language settings. We populated the accounts with email
messages in those languages by subscribing them to selected online newsletters.
We hid email messages about fake bank accounts in fifteen of the accounts to
mimic real-world webmail users that sometimes store sensitive information in
their accounts. We then leaked credentials to the honey accounts via paste
sites on the Surface Web and the Dark Web, and collected data for fifteen days.
Our statistical analyses on the data show that cybercriminals are more likely
to discover sensitive information (bank account information) in the Greek
accounts than the remaining accounts, contrary to the expectation that Greek
ought to constitute a barrier to the understanding of non-Greek visitors to the
Greek accounts. We also extracted the important words among the emails that
cybercriminals accessed (as an approximation of the keywords that they searched
for within the honey accounts), and found that financial terms featured among
the top words. In summary, we show that language plays a significant role in
the ability of cybercriminals to access sensitive information hidden in
compromised webmail accounts
On Web User Tracking: How Third-Party Http Requests Track Users' Browsing Patterns for Personalised Advertising
On today's Web, users trade access to their private data for content and
services. Advertising sustains the business model of many websites and
applications. Efficient and successful advertising relies on predicting users'
actions and tastes to suggest a range of products to buy. It follows that,
while surfing the Web users leave traces regarding their identity in the form
of activity patterns and unstructured data. We analyse how advertising networks
build user footprints and how the suggested advertising reacts to changes in
the user behaviour.Comment: arXiv admin note: substantial text overlap with arXiv:1605.0653
ToyArchitecture: Unsupervised Learning of Interpretable Models of the World
Research in Artificial Intelligence (AI) has focused mostly on two extremes:
either on small improvements in narrow AI domains, or on universal theoretical
frameworks which are usually uncomputable, incompatible with theories of
biological intelligence, or lack practical implementations. The goal of this
work is to combine the main advantages of the two: to follow a big picture
view, while providing a particular theory and its implementation. In contrast
with purely theoretical approaches, the resulting architecture should be usable
in realistic settings, but also form the core of a framework containing all the
basic mechanisms, into which it should be easier to integrate additional
required functionality.
In this paper, we present a novel, purposely simple, and interpretable
hierarchical architecture which combines multiple different mechanisms into one
system: unsupervised learning of a model of the world, learning the influence
of one's own actions on the world, model-based reinforcement learning,
hierarchical planning and plan execution, and symbolic/sub-symbolic integration
in general. The learned model is stored in the form of hierarchical
representations with the following properties: 1) they are increasingly more
abstract, but can retain details when needed, and 2) they are easy to
manipulate in their local and symbolic-like form, thus also allowing one to
observe the learning process at each level of abstraction. On all levels of the
system, the representation of the data can be interpreted in both a symbolic
and a sub-symbolic manner. This enables the architecture to learn efficiently
using sub-symbolic methods and to employ symbolic inference.Comment: Revision: changed the pdftitl
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