4,331 research outputs found
OnionBots: Subverting Privacy Infrastructure for Cyber Attacks
Over the last decade botnets survived by adopting a sequence of increasingly
sophisticated strategies to evade detection and take overs, and to monetize
their infrastructure. At the same time, the success of privacy infrastructures
such as Tor opened the door to illegal activities, including botnets,
ransomware, and a marketplace for drugs and contraband. We contend that the
next waves of botnets will extensively subvert privacy infrastructure and
cryptographic mechanisms. In this work we propose to preemptively investigate
the design and mitigation of such botnets. We first, introduce OnionBots, what
we believe will be the next generation of resilient, stealthy botnets.
OnionBots use privacy infrastructures for cyber attacks by completely
decoupling their operation from the infected host IP address and by carrying
traffic that does not leak information about its source, destination, and
nature. Such bots live symbiotically within the privacy infrastructures to
evade detection, measurement, scale estimation, observation, and in general all
IP-based current mitigation techniques. Furthermore, we show that with an
adequate self-healing network maintenance scheme, that is simple to implement,
OnionBots achieve a low diameter and a low degree and are robust to
partitioning under node deletions. We developed a mitigation technique, called
SOAP, that neutralizes the nodes of the basic OnionBots. We also outline and
discuss a set of techniques that can enable subsequent waves of Super
OnionBots. In light of the potential of such botnets, we believe that the
research community should proactively develop detection and mitigation methods
to thwart OnionBots, potentially making adjustments to privacy infrastructure.Comment: 12 pages, 8 figure
PeerHunter: Detecting Peer-to-Peer Botnets through Community Behavior Analysis
Peer-to-peer (P2P) botnets have become one of the major threats in network
security for serving as the infrastructure that responsible for various of
cyber-crimes. Though a few existing work claimed to detect traditional botnets
effectively, the problem of detecting P2P botnets involves more challenges. In
this paper, we present PeerHunter, a community behavior analysis based method,
which is capable of detecting botnets that communicate via a P2P structure.
PeerHunter starts from a P2P hosts detection component. Then, it uses mutual
contacts as the main feature to cluster bots into communities. Finally, it uses
community behavior analysis to detect potential botnet communities and further
identify bot candidates. Through extensive experiments with real and simulated
network traces, PeerHunter can achieve very high detection rate and low false
positives.Comment: 8 pages, 2 figures, 11 tables, 2017 IEEE Conference on Dependable and
Secure Computin
Botnet Detection using Social Graph Analysis
Signature-based botnet detection methods identify botnets by recognizing
Command and Control (C\&C) traffic and can be ineffective for botnets that use
new and sophisticate mechanisms for such communications. To address these
limitations, we propose a novel botnet detection method that analyzes the
social relationships among nodes. The method consists of two stages: (i)
anomaly detection in an "interaction" graph among nodes using large deviations
results on the degree distribution, and (ii) community detection in a social
"correlation" graph whose edges connect nodes with highly correlated
communications. The latter stage uses a refined modularity measure and
formulates the problem as a non-convex optimization problem for which
appropriate relaxation strategies are developed. We apply our method to
real-world botnet traffic and compare its performance with other community
detection methods. The results show that our approach works effectively and the
refined modularity measure improves the detection accuracy.Comment: 7 pages. Allerton Conferenc
Master of Puppets: Analyzing And Attacking A Botnet For Fun And Profit
A botnet is a network of compromised machines (bots), under the control of an
attacker. Many of these machines are infected without their owners' knowledge,
and botnets are the driving force behind several misuses and criminal
activities on the Internet (for example spam emails). Depending on its
topology, a botnet can have zero or more command and control (C&C) servers,
which are centralized machines controlled by the cybercriminal that issue
commands and receive reports back from the co-opted bots.
In this paper, we present a comprehensive analysis of the command and control
infrastructure of one of the world's largest proprietary spamming botnets
between 2007 and 2012: Cutwail/Pushdo. We identify the key functionalities
needed by a spamming botnet to operate effectively. We then develop a number of
attacks against the command and control logic of Cutwail that target those
functionalities, and make the spamming operations of the botnet less effective.
This analysis was made possible by having access to the source code of the C&C
software, as well as setting up our own Cutwail C&C server, and by implementing
a clone of the Cutwail bot. With the help of this tool, we were able to
enumerate the number of bots currently registered with the C&C server,
impersonate an existing bot to report false information to the C&C server, and
manipulate spamming statistics of an arbitrary bot stored in the C&C database.
Furthermore, we were able to make the control server inaccessible by conducting
a distributed denial of service (DDoS) attack. Our results may be used by law
enforcement and practitioners to develop better techniques to mitigate and
cripple other botnets, since many of findings are generic and are due to the
workflow of C&C communication in general
Master of puppets: analyzing and attacking a botnet for fun and profit
A botnet is a network of compromised machines (bots),
under the control of an attacker. Many of these machines
are infected without their owners’ knowledge, and botnets
are the driving force behind several misuses and criminal
activities on the Internet (for example spam emails). Depending
on its topology, a botnet can have zero or more
command and control (C&C) servers, which are centralized
machines controlled by the cybercriminal that issue
commands and receive reports back from the co-opted
bots.
In this paper, we present a comprehensive analysis of
the command and control infrastructure of one of the
world’s largest proprietary spamming botnets between
2007 and 2012: Cutwail/Pushdo. We identify the key
functionalities needed by a spamming botnet to operate
effectively. We then develop a number of attacks against
the command and control logic of Cutwail that target
those functionalities, and make the spamming operations
of the botnet less effective. This analysis was made possible
by having access to the source code of the C&C software,
as well as setting up our own Cutwail C&C server,
and by implementing a clone of the Cutwail bot. With the
help of this tool, we were able to enumerate the number
of bots currently registered with the C&C server, impersonate
an existing bot to report false information to the
C&C server, and manipulate spamming statistics of an arbitrary
bot stored in the C&C database. Furthermore, we
were able to make the control server inaccessible by conducting
a distributed denial of service (DDoS) attack. Our
results may be used by law enforcement and practitioners
to develop better techniques to mitigate and cripple other
botnets, since many of findings are generic and are due to
the workflow of C&C communication in general.First author draf
A Threat to Cyber Resilience : A Malware Rebirthing Botnet
This paper presents a threat to cyber resilience in the form of a conceptual model of a malware rebirthing botnet which can be used in a variety of scenarios. It can be used to collect existing malware and rebirth it with new functionality and signatures that will avoid detection by AV software and hinder analysis. The botnet can then use the customized malware to target an organization with an orchestrated attack from the member machines in the botnet for a variety of malicious purposes, including information warfare applications. Alternatively, it can also be used to inject known malware signatures into otherwise non malicious code and traffic to overloading the sensors and processing systems employed by intrusion detection and prevention systems to create a denial of confidence of the sensors and detection systems. This could be used as a force multiplier in asymmetric warfare applications to create confusion and distraction whilst attacks are made on other defensive fronts
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