285 research outputs found
An Enhanced IP Trace Back Mechanism by using Particle Swarm System
Internet is the most powerful medium as on date, facilitating varied services to numerous users. It has also become the environment for cyber warfare where attacks of many types (financial, ideological, revenge) are being launched. �Network forensics is a sub-branch of digital forensics relating to the monitoring and analysis of computer network traffic for the purposes of information gathering, legal evidence, or intrusion detection.� Cloud Storage is a service where data is remotely maintained, managed, and backed up. The service is available to users over a network, which is usually the internet. It allows the user to store files online so that the user can access them from any location via the internet. The provider company makes them available to the user online by keeping the uploaded files on an external server. In this paper, a novel Digital Network Forensic Investigation Method is proposed. This paper will do changes in the analysis and investigation place of the network forensic. The investigation of the case will be based on the previous data collecting framework. The Spoofed IP address are classified by the previous framework and Enhanced IP trace back mechanism by Particle Swarm System is trace the real victim of the case in the network forensic
Packet analysis for network forensics: A comprehensive survey
Packet analysis is a primary traceback technique in network forensics, which, providing that the packet details captured are sufficiently detailed, can play back even the entire network traffic for a particular point in time. This can be used to find traces of nefarious online behavior, data breaches, unauthorized website access, malware infection, and intrusion attempts, and to reconstruct image files, documents, email attachments, etc. sent over the network. This paper is a comprehensive survey of the utilization of packet analysis, including deep packet inspection, in network forensics, and provides a review of AI-powered packet analysis methods with advanced network traffic classification and pattern identification capabilities. Considering that not all network information can be used in court, the types of digital evidence that might be admissible are detailed. The properties of both hardware appliances and packet analyzer software are reviewed from the perspective of their potential use in network forensics
Detecting and tracing slow attacks on mobile phone user service
The lower bandwidth of mobile devices has until recently filtered the range of attacks on the Internet. However, recent research shows that DOS and DDOS attacks, worms and viruses, and a whole range of social engineering attacks are impacting on broadband smartphone users. In our research we have developed a metric-based system to detect the traditional slow attacks that can be effective using limited resources, and then employed combinations of Internet trace back techniques to identify sources of attacks. Our research question asked: What defence mechanisms are effective? We critically evaluate the available literature to appraise the current state of the problem area and then propose an innovative solution for the detection and investigation of attacks
Wide spectrum attribution: Using deception for attribution intelligence in cyber attacks
Modern cyber attacks have evolved considerably. The skill level required to conduct
a cyber attack is low. Computing power is cheap, targets are diverse and plentiful.
Point-and-click crimeware kits are widely circulated in the underground economy, while
source code for sophisticated malware such as Stuxnet is available for all to download
and repurpose. Despite decades of research into defensive techniques, such as firewalls,
intrusion detection systems, anti-virus, code auditing, etc, the quantity of successful
cyber attacks continues to increase, as does the number of vulnerabilities identified.
Measures to identify perpetrators, known as attribution, have existed for as long as there
have been cyber attacks. The most actively researched technical attribution techniques
involve the marking and logging of network packets. These techniques are performed
by network devices along the packet journey, which most often requires modification of
existing router hardware and/or software, or the inclusion of additional devices. These
modifications require wide-scale infrastructure changes that are not only complex and
costly, but invoke legal, ethical and governance issues. The usefulness of these techniques
is also often questioned, as attack actors use multiple stepping stones, often innocent
systems that have been compromised, to mask the true source. As such, this thesis
identifies that no publicly known previous work has been deployed on a wide-scale basis
in the Internet infrastructure.
This research investigates the use of an often overlooked tool for attribution: cyber de-
ception. The main contribution of this work is a significant advancement in the field of
deception and honeypots as technical attribution techniques. Specifically, the design and
implementation of two novel honeypot approaches; i) Deception Inside Credential Engine
(DICE), that uses policy and honeytokens to identify adversaries returning from different
origins and ii) Adaptive Honeynet Framework (AHFW), an introspection and adaptive
honeynet framework that uses actor-dependent triggers to modify the honeynet envi-
ronment, to engage the adversary, increasing the quantity and diversity of interactions.
The two approaches are based on a systematic review of the technical attribution litera-
ture that was used to derive a set of requirements for honeypots as technical attribution
techniques. Both approaches lead the way for further research in this field
Impact of denial of service solutions on network quality of service
The Internet has become a universal communication network tool. It has evolved from a platform that supports best-effort traffic to one that now carries different traffic types including those involving continuous media with quality of service (QoS) requirements. As more services are delivered over the Internet, we face increasing risk to their availability given that malicious attacks on those Internet services continue to increase. Several networks have witnessed denial of service (DoS) and distributed denial of service (DDoS) attacks over the past few years which have disrupted QoS of network services, thereby violating the Service Level Agreement (SLA) between the client and the Internet Service Provider (ISP). Hence DoS or DDoS attacks are major threats to network QoS. In this paper we survey techniques and solutions that have been deployed to thwart DoS and DDoS attacks and we evaluate them in terms of their impact on network QoS for Internet services. We also present vulnerabilities that can be exploited for QoS protocols and also affect QoS if exploited. In addition, we also highlight challenges that still need to be addressed to achieve end-to-end QoS with recently proposed DoS/DDoS solutions
Preventing DDoS using Bloom Filter: A Survey
Distributed Denial-of-Service (DDoS) is a menace for service provider and
prominent issue in network security. Defeating or defending the DDoS is a prime
challenge. DDoS make a service unavailable for a certain time. This phenomenon
harms the service providers, and hence, loss of business revenue. Therefore,
DDoS is a grand challenge to defeat. There are numerous mechanism to defend
DDoS, however, this paper surveys the deployment of Bloom Filter in defending a
DDoS attack. The Bloom Filter is a probabilistic data structure for membership
query that returns either true or false. Bloom Filter uses tiny memory to store
information of large data. Therefore, packet information is stored in Bloom
Filter to defend and defeat DDoS. This paper presents a survey on DDoS
defending technique using Bloom Filter.Comment: 9 pages, 1 figure. This article is accepted for publication in EAI
Endorsed Transactions on Scalable Information System
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