237,970 research outputs found
Password Cracking and Countermeasures in Computer Security: A Survey
With the rapid development of internet technologies, social networks, and
other related areas, user authentication becomes more and more important to
protect the data of the users. Password authentication is one of the widely
used methods to achieve authentication for legal users and defense against
intruders. There have been many password cracking methods developed during the
past years, and people have been designing the countermeasures against password
cracking all the time. However, we find that the survey work on the password
cracking research has not been done very much. This paper is mainly to give a
brief review of the password cracking methods, import technologies of password
cracking, and the countermeasures against password cracking that are usually
designed at two stages including the password design stage (e.g. user
education, dynamic password, use of tokens, computer generations) and after the
design (e.g. reactive password checking, proactive password checking, password
encryption, access control). The main objective of this work is offering the
abecedarian IT security professionals and the common audiences with some
knowledge about the computer security and password cracking, and promoting the
development of this area.Comment: add copyright to the tables to the original authors, add
acknowledgement to helpe
Cyber-crime Science = Crime Science + Information Security
Cyber-crime Science is an emerging area of study aiming to prevent cyber-crime by combining security protection techniques from Information Security with empirical research methods used in Crime Science. Information security research has developed techniques for protecting the confidentiality, integrity, and availability of information assets but is less strong on the empirical study of the effectiveness of these techniques. Crime Science studies the effect of crime prevention techniques empirically in the real world, and proposes improvements to these techniques based on this. Combining both approaches, Cyber-crime Science transfers and further develops Information Security techniques to prevent cyber-crime, and empirically studies the effectiveness of these techniques in the real world. In this paper we review the main contributions of Crime Science as of today, illustrate its application to a typical Information Security problem, namely phishing, explore the interdisciplinary structure of Cyber-crime Science, and present an agenda for research in Cyber-crime Science in the form of a set of suggested research questions
Flooding attacks to internet threat monitors (ITM): Modeling and counter measures using botnet and honeypots
The Internet Threat Monitoring (ITM),is a globally scoped Internet monitoring
system whose goal is to measure, detect, characterize, and track threats such
as distribute denial of service(DDoS) attacks and worms. To block the
monitoring system in the internet the attackers are targeted the ITM system. In
this paper we address flooding attack against ITM system in which the attacker
attempt to exhaust the network and ITM's resources, such as network bandwidth,
computing power, or operating system data structures by sending the malicious
traffic. We propose an information-theoretic frame work that models the
flooding attacks using Botnet on ITM. Based on this model we generalize the
flooding attacks and propose an effective attack detection using Honeypots
On Non-Parallelizable Deterministic Client Puzzle Scheme with Batch Verification Modes
A (computational) client puzzle scheme enables a client to prove to a server that a certain amount of computing resources (CPU cycles and/or Memory look-ups) has been dedicated to solve a puzzle. Researchers have identified a number of potential applications, such as constructing timed cryptography, fighting junk emails, and protecting critical infrastructure from DoS attacks. In this paper, we first revisit this concept and formally define two properties, namely deterministic computation and parallel computation resistance. Our analysis show that both properties are crucial for the effectiveness of client puzzle schemes in most application scenarios. We prove that the RSW client puzzle scheme, which is based on the repeated squaring technique, achieves both properties. Secondly, we introduce two batch verification modes for the RSW client puzzle scheme in order to improve the verification efficiency of the server, and investigate three methods for handling errors in batch verifications. Lastly, we show that client puzzle schemes can be integrated with reputation systems to further improve the effectiveness in practice
Discriminative models for multi-instance problems with tree-structure
Modeling network traffic is gaining importance in order to counter modern
threats of ever increasing sophistication. It is though surprisingly difficult
and costly to construct reliable classifiers on top of telemetry data due to
the variety and complexity of signals that no human can manage to interpret in
full. Obtaining training data with sufficiently large and variable body of
labels can thus be seen as prohibitive problem. The goal of this work is to
detect infected computers by observing their HTTP(S) traffic collected from
network sensors, which are typically proxy servers or network firewalls, while
relying on only minimal human input in model training phase. We propose a
discriminative model that makes decisions based on all computer's traffic
observed during predefined time window (5 minutes in our case). The model is
trained on collected traffic samples over equally sized time window per large
number of computers, where the only labels needed are human verdicts about the
computer as a whole (presumed infected vs. presumed clean). As part of training
the model itself recognizes discriminative patterns in traffic targeted to
individual servers and constructs the final high-level classifier on top of
them. We show the classifier to perform with very high precision, while the
learned traffic patterns can be interpreted as Indicators of Compromise. In the
following we implement the discriminative model as a neural network with
special structure reflecting two stacked multi-instance problems. The main
advantages of the proposed configuration include not only improved accuracy and
ability to learn from gross labels, but also automatic learning of server types
(together with their detectors) which are typically visited by infected
computers
The Case for Quantum Key Distribution
Quantum key distribution (QKD) promises secure key agreement by using quantum
mechanical systems. We argue that QKD will be an important part of future
cryptographic infrastructures. It can provide long-term confidentiality for
encrypted information without reliance on computational assumptions. Although
QKD still requires authentication to prevent man-in-the-middle attacks, it can
make use of either information-theoretically secure symmetric key
authentication or computationally secure public key authentication: even when
using public key authentication, we argue that QKD still offers stronger
security than classical key agreement.Comment: 12 pages, 1 figure; to appear in proceedings of QuantumComm 2009
Workshop on Quantum and Classical Information Security; version 2 minor
content revision
Actor-network procedures: Modeling multi-factor authentication, device pairing, social interactions
As computation spreads from computers to networks of computers, and migrates
into cyberspace, it ceases to be globally programmable, but it remains
programmable indirectly: network computations cannot be controlled, but they
can be steered by local constraints on network nodes. The tasks of
"programming" global behaviors through local constraints belong to the area of
security. The "program particles" that assure that a system of local
interactions leads towards some desired global goals are called security
protocols. As computation spreads beyond cyberspace, into physical and social
spaces, new security tasks and problems arise. As networks are extended by
physical sensors and controllers, including the humans, and interlaced with
social networks, the engineering concepts and techniques of computer security
blend with the social processes of security. These new connectors for
computational and social software require a new "discipline of programming" of
global behaviors through local constraints. Since the new discipline seems to
be emerging from a combination of established models of security protocols with
older methods of procedural programming, we use the name procedures for these
new connectors, that generalize protocols. In the present paper we propose
actor-networks as a formal model of computation in heterogenous networks of
computers, humans and their devices; and we introduce Procedure Derivation
Logic (PDL) as a framework for reasoning about security in actor-networks. On
the way, we survey the guiding ideas of Protocol Derivation Logic (also PDL)
that evolved through our work in security in last 10 years. Both formalisms are
geared towards graphic reasoning and tool support. We illustrate their workings
by analysing a popular form of two-factor authentication, and a multi-channel
device pairing procedure, devised for this occasion.Comment: 32 pages, 12 figures, 3 tables; journal submission; extended
references, added discussio
Quantum attacks on Bitcoin, and how to protect against them
The key cryptographic protocols used to secure the internet and financial
transactions of today are all susceptible to attack by the development of a
sufficiently large quantum computer. One particular area at risk are
cryptocurrencies, a market currently worth over 150 billion USD. We investigate
the risk of Bitcoin, and other cryptocurrencies, to attacks by quantum
computers. We find that the proof-of-work used by Bitcoin is relatively
resistant to substantial speedup by quantum computers in the next 10 years,
mainly because specialized ASIC miners are extremely fast compared to the
estimated clock speed of near-term quantum computers. On the other hand, the
elliptic curve signature scheme used by Bitcoin is much more at risk, and could
be completely broken by a quantum computer as early as 2027, by the most
optimistic estimates. We analyze an alternative proof-of-work called Momentum,
based on finding collisions in a hash function, that is even more resistant to
speedup by a quantum computer. We also review the available post-quantum
signature schemes to see which one would best meet the security and efficiency
requirements of blockchain applications.Comment: 21 pages, 6 figures. For a rough update on the progress of Quantum
devices and prognostications on time from now to break Digital signatures,
see https://www.quantumcryptopocalypse.com/quantum-moores-law
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