Denial of Service attacks – Definitions, related surveys
Traceback of DDoS Attacks – Proposed method, advantages, future work
Detection methods with Shannon and Renyi cross entropy – Previous works, proposed method, dataset and results
The added value of entropy detection methods
References
This is a presentation i made about Denial of Service or a Distributed Denial of Service (DoS / DDoS) and the latest methods used to crash anything online and the future of such attacks which can disrupt the whole internet . Such attacks which are in TB's and can be launched from just single computer. And, there is not much that can be done to prevent them.
WPA2 Hole196 Vulnerability: Exploits and Remediation StrategiesAirTight Networks
This paper presents a vulnerability, called Hole1961, in the WPA2 protocol that makes all
implementations of WPA- and WPA2-secured Wi-Fi networks (regardless of the authentication
and encryption used) vulnerable to insider attacks. It discusses ways in which a malicious
insider can exploit Hole196 to attack other authorized Wi-Fi users in a WPA2-secured wireless
LAN (WLAN). It also explores remediation strategies at various levels that organizations can
implement to mitigate this threat.
Slides for a college course at City College San Francisco. Based on "Hands-On Ethical Hacking and Network Defense, Third Edition" by Michael T. Simpson, Kent Backman, and James Corley -- ISBN: 9781285454610.
Instructor: Sam Bowne
Class website: https://samsclass.info/123/123_S17.shtml
This is a presentation i made about Denial of Service or a Distributed Denial of Service (DoS / DDoS) and the latest methods used to crash anything online and the future of such attacks which can disrupt the whole internet . Such attacks which are in TB's and can be launched from just single computer. And, there is not much that can be done to prevent them.
WPA2 Hole196 Vulnerability: Exploits and Remediation StrategiesAirTight Networks
This paper presents a vulnerability, called Hole1961, in the WPA2 protocol that makes all
implementations of WPA- and WPA2-secured Wi-Fi networks (regardless of the authentication
and encryption used) vulnerable to insider attacks. It discusses ways in which a malicious
insider can exploit Hole196 to attack other authorized Wi-Fi users in a WPA2-secured wireless
LAN (WLAN). It also explores remediation strategies at various levels that organizations can
implement to mitigate this threat.
Slides for a college course at City College San Francisco. Based on "Hands-On Ethical Hacking and Network Defense, Third Edition" by Michael T. Simpson, Kent Backman, and James Corley -- ISBN: 9781285454610.
Instructor: Sam Bowne
Class website: https://samsclass.info/123/123_S17.shtml
Secure your network - Segmentation and segregationMagnus Jansson
The defense in depth value of segmenting your network into different security zones is widely recognized and should be a part of every company’s security strategy. A properly segmented network will reduce the attack surface, limit an attacker’s potential to move laterally in the network, and strongly limiting the potential damage of a cyber-attack. However, segmenting your network is a major project and will change how you are managing your network.
Cloudflare protects and accelerates any web property online. We stop hackers from reaching your web property and knocking it offline. In addition, we help your site visitors access your content as fast as possible no matter their location. Join us as we discuss evolving DDoS attack types and trends to be aware about in 2018.
What they are, steps you can take to prevent them, a brief overview.
3/13/2013 winter term 2013 at Portland State University for the Introduction to Databases class.
Presented by Stacy Watts and Tyler Fetters
Secure your network - Segmentation and segregationMagnus Jansson
The defense in depth value of segmenting your network into different security zones is widely recognized and should be a part of every company’s security strategy. A properly segmented network will reduce the attack surface, limit an attacker’s potential to move laterally in the network, and strongly limiting the potential damage of a cyber-attack. However, segmenting your network is a major project and will change how you are managing your network.
Cloudflare protects and accelerates any web property online. We stop hackers from reaching your web property and knocking it offline. In addition, we help your site visitors access your content as fast as possible no matter their location. Join us as we discuss evolving DDoS attack types and trends to be aware about in 2018.
What they are, steps you can take to prevent them, a brief overview.
3/13/2013 winter term 2013 at Portland State University for the Introduction to Databases class.
Presented by Stacy Watts and Tyler Fetters
Super Effective Denial of Service AttacksJan Seidl
Talk given on October 16th at Latinoware 2013 - Foz do Iguaçu - Brazil
This talk gave an introduction on denial of service attacks, going trough attacks in layer 3 to layer 7, introduced the concept of using load-balancing software for attacks with multiple IPs (Jericho Attack) and introduced the GoldenEye tool written in python and Android (Java), as well as a brief introduction to mitigate layer 7 denial-of-service attacks on most popular webservers.
Presentation Video (pt_BR) @ FISL 2014: https://www.youtube.com/watch?v=ozk0HiMjVNY
Black Hole Attack:
A malicious node advertises the wrong paths as good paths to the source node during the pathfinding process.
When the source selects the path including the attacker node, the traffic starts passing through the adversary node and this node starts dropping the packets selectively or in whole.
Black hole region is the entry point to a large number of harmful attacks.
Internet Worm Classification and Detection using Data Mining Techniquesiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
ADRISYA: A FLOW BASED ANOMALY DETECTION SYSTEM FOR SLOW AND FAST SCANIJNSA Journal
Attackers perform port scan to find reachability, liveness and running services in a system or network. Current day scanning tools provide different scanning options and capable of evading various security tools like firewall, IDS and IPS. So in order to detect and prevent attacks in the early stages, an accurate detection of scanning activity in real time is very much essential. In this paper we present a flow based protocol behaviour analysis system to detect TCP based slow and fast scan. This system provides scalable, accurate and generic solution to TCP based scanning by means of automatic behaviour analysis of the network traffic. Detection capability of proposed system is compared with SNORT and result proves the high detection rate of the system over SNORT.
Review of Intrusion and Anomaly Detection Techniques IJMER
Intrusion detection is the act of detecting actions that attempt to compromise the
confidentiality, integrity or availability of a resource. With the tremendous growth of network-based
services and sensitive information on networks, network security is getting more and more importance
than ever. Intrusion poses a serious security threat in a huge network environment. The increasing use of
internet has dramatically added to the growing number of threats that inhabit within it. Intrusion
detection does not, in general, include prevention of intrusions. Now a days Network intrusion detection
systems have become a standard component in the area of security infrastructure. This review paper tries
to discusses various techniques which are already being used for intrusion detection.
Network traffic analysis with cyber securityKAMALI PRIYA P
We are students from SRM University pursuing B.TECH in Computer Science Department. We took a small initiative to make a PPT about how network traffic can be analyzed through Cyber Security. We have also mentioned the known network analyzers and future scope for network traffic analysis with cyber security.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Network sniffers & injection tools
Network Threats Attack
Specific Attack Types
Network Sniffer
How does a Sniffer Work?
How can I detect a packet sniffer?
Packet Sniffer Mitigation
Injection Tools
Διαστάσεις Mobile Advertising
Τεχνολογίες Mobile Advertising showroom
Το παρόν και το μέλλον του Mobile Advertising
Μεθοδολογία Mobile Advertising
Διαδραστικότητα
Οφέλη-Προβλήματα του Mobile Advertising
Προκλήσεις: Ξεπερνώντας τις δυσκολίες του mobile advertising
Αποτελέσματα Προτάσεις
Εισαγωγή
Πρακτικές και πολιτικές customer care
Δωρεάν αποστολή και επιστροφή των προϊόντων από τη παραγγελία.
Επένδυση σε πρωτοποριακή τεχνολογία
Καινοτομίες στην εξυπηρέτηση πελατών
Πολιτική προσλήψεων και απολύσεις με bonus
Η αξιοποίηση των social media
Εταιρική κουλτούρα
ZapposInsights και εταιρική επικοινωνία
Συμπεράσματα
Εισαγωγικά στοιχεία για τα Social Media.
Η δυναμική των Social Media.
Social Media Marketing.
Social Media Newsroom και Πρακτικές Εφαρμογές.
Πρακτικές Συμβουλές για επιτυχία στα Social Media
Marketing στο Twitter
¨Καλές και Κακές¨ Πρακτικές για επιτυχία στα social media
Γιατί οι επιχειρήσεις αποτυγχάνουν με τα social media;
Δημιουργία Personal Brand στο Facebook
Σύνοψη
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
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However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
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Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
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Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
The Art of the Pitch: WordPress Relationships and Sales
Entropy and denial of service attacks
1. Master in Web Science
Mathematics Department
Aristotle University of Thessaloniki
“Entropy and Denial of Service
Attacks”
Zlatis Chris
2. Contents
• Denial of Service attacks – Definitions, related surveys
• Traceback of DDoS Attacks – Proposed method,
advantages, future work
• Detection methods with Shannon and Renyi cross
entropy – Previous works, proposed method, dataset
and results
• The added value of entropy detection methods
• References
3. Definitions
• Distributed Denial of Service Attacks (DDoS Attacks) are defined as
[4] “attempts to make a computer resource unavailable to its intended
users”.
– The attacker gains control of a huge number of independently owned
and geographically distributed computers, called “zombies”, almost
always without any knowledge of their owners.
• Ping flood is a type of DDoS attack directing a huge number of
“ping” requests to the target victim. It exploits the “Internet Control
Message Protocol” (ICMP). [4]
– Huge number of ping ‘echo requests’ from a very large number of
“zombies” unable to conduct any network activity other than
answering the ping ‘echo requests’ overloaded and standstill.
4. Recent surveys
• It has been a major threat to the Internet since year 2000, and a
recent survey on the largest 70 Internet operators in the world [4]
demonstrated that:
1. DDoS attacks are increasing dramatically, and individual attacks
are more strong and sophisticated
2. The network security community does not have effective and
efficient traceback methods to locate attackers as it is easy for
attackers to disguise themselves
3. The Mafiaboy attacks of February 2000 against Amazon, eBay
caused millions of dollars damage
There is a need to detect DDoS attacks as early as possible so that
proper countermeasures can be applied and damage can be
minimized.
5. Traceback of DDoS attacks
• IP traceback means the capability of identifying the actual source of
any packet sent across the Internet successful if they can identify
the zombies from which the DDoS attack packets entered the
Internet.
There are two major methods for IP traceback: [6]
1. The probabilistic packet marking (PPM) and
2. The deterministic packet marking (DPM).
• The PPM strategy can only operate in a local range of the Internet
(ISP network) we cannot traceback to the attack sources located
out of the ISP network. The DPM strategy requires all the Internet
routers to be updated for packet marking.
• Both of these strategies require routers to inject marks into
individual packets vulnerable to hacking, referred to as “packet
pollution”.
6. IP Traceback using entropy variations
• IP traceback using information theoretical parameters [6] there
is no packet marking in the proposed strategy avoid the inherited
shortcomings of the packet marking mechanisms.
• The packets that are passing through a router are categorized into
flows [6], which are defined by the upstream router where a packet
came from, and the destination address of the packet.
– During non attack periods, routers are required to observe and
record entropy variations of local flows.
– Once a DDoS attack has been identified, the victim initiates a
pushback process to identify the locations of zombies…
7. IP Traceback using entropy variations
• The pushback process: [6]
1. The victim first identifies which of its upstream routers are in the
attack tree based on the flow entropy variations it has
accumulated, and then
2. submits requests to the related immediate upstream routers.
3. The upstream routers identify where the attack flows came from
based on their local entropy variations that they have monitored.
4. Once the immediate upstream routers have identified the attack
flows,
5. they will forward the requests to their immediate upstream
routers, respectively, to identify the attacker sources further.
This procedure is repeated in a parallel and distributed fashion
until it reaches the attack source(s).
8. Advantages of traceback mechanism
The proposed traceback mechanism possesses the following
advantages: [6]
• It overcomes the inherited drawbacks of packet marking methods,
such as limited scalability, huge demands on storage space, and
vulnerability to packet pollutions.
• It brings no modifications on current routing software work
independently as an additional module on routers for monitoring
and recording flow information.
• It will be effective for future packet flooding DDoS attacks because
it is independent of traffic patterns.
It can archive real-time traceback to attackers. Once the short-
term flow information is in place at routers, and the victim notices
that it is under attack, it will start the traceback procedure.
9. Future work on Traceback methods
Future work could be carried out in the following promising directions: [6]
• 1. The metric for DDoS attack flows could be further explored. The
proposed method deals with the packet flooding type of attacks
perfectly.
The attacks with small number attack packet rates, e.g., if the attack
strength is less than seven times of the strength of non attack flows, the
current metric cannot discriminate it. Therefore, a metric of finer
granularity is required to deal with such situations.
• 2. Location estimation of attackers with partial information. When
the attack strength is less than seven times of the normal flow packet
rate, the proposed method cannot succeed at the moment.
The attack can be detected with the information that we have
accumulated so far using traditional methods or recently developed
tools.
10. Detection methods with Shannon and
Renyl cross entropy
An entropy-based method [1] is proposed to detect network attack:
• The Shannon entropy is used to analyze the distribution
characteristics of alert with five key attributes including source IP
address, destination IP address, source threat, destination threat
and datagram length that reflect the regularity of network status
– When the monitored network runs in normal way, the entropy values
are relatively smooth. Otherwise, the entropy value of one or more
features would change.
• Then, the Renyi cross entropy is employed to fuse the Shannon
entropy vector and detect the anomalies. The Renyi cross entropy
of these features is calculated to measure the network status and
detect network attacks.
11. Previous works on entropy
detection methods
• Gina investigated the extent of false alerts problem in Snort using
the 1999 DARPA IDS evaluation data.
– They found that 69% of total generated alerts are considered to be false
alerts. [1] These problems make it a frustrating task for security officers to
detect network attack quickly and accurately.
• Gu proposed an approach to detect anomalies in the network
traffic using Maximum Entropy estimation.
– The packet distribution of the benign traffic was estimated using
Maximum Entropy framework and used as a baseline to detect the
anomalies.
• Qin used Renyi cross entropy to detect dynamic changes in network
traffic of large enterprises. Three traffic features were proposed to
capture dynamic changes of traffic.
• A. Wagner and B Plattner applied entropy to detect worm and
anomaly in fast IP networks. The entropy contents of IP addresses
were used to indicate a massive network event.
12. Dataset and results
• Methodology: [1] Use of Snort to monitor 32 C-class subnets in the
campus network for two weeks, which include more than 3,000
end users.
– Alerts in Mar. 2nd as the experimental data: 1,147,906 alerts in this
day with 79 signatures, 32,409 source IP addresses, 12,642 destination
IP addresses two alerts sets collected from different time period in
Mar. 2nd as training and test data.
The statistical results of alerts suggest several interesting results:
1. More alerts were generated in daytime than that in night due to
people’s living habit. There were two peaks of alerts: 12:00 to
14:00 and 21:00 to 23:30 the end users are campus students.
2. The destination IP addresses change abruptly from 0:00 to 4:00,
6:00 to 10:00, 12:00 to 16:00 and 18:00 to 22:00. By analyzing the
alerts, they found many host scan attacks at these time periods.
13. The added value of Entropy methods
• The Shannon entropy is used to analyze the alerts to measure the
regularity of current network status.
– They are relative smooth when no attack occurs; otherwise, one or
some of the values would change abruptly.
• The Renyi cross entropy is employed to detect network attack.
– The Renyi cross entropy value is near 0 when the network runs in
normal, otherwise the value will change abruptly when attack occurs.
• However, although the Shannon entropies reflect the regularity of
network status, it is difficult to detect attack directly by using five
fixed thresholds [1], because the Shannon entropy value varies with
the activities of end users even the network runs in normal way.
14. References
[1] Zhiwen Wang, Qin Xia, “An Approach on Detecting Network Attack Based
on Entropy”, Xi’an Jiaotong University, China
[2] Hoa Dinh Nguyen, Sandeep Gutta, Qi Cheng, “An Active Distributed
Approach for Cyber Attack Detection”, Oklahoma State University
[3] Tsern-Huei Lee - Jyun-De He, “Entropy-Based Profiling of Network Traffic
for Detection of Security Attack”, National Chiao Tung University, Taiwan
[4] Anna T. Lawniczak, Bruno N. Di Stefano, Hao Wu, “Detection & Study of
DDoS Attacks Via Entropy in Data Network Models”, CISDA, 2009
[5] Stephen Schwab, Brett Wilson, Roshan Thomas, “Methodologies and
Metrics for the Testing and Analysis of Distributed Denial of Service
Attacks and Defenses”, SPARTA Inc.
[6] Shui Yu, Wanlei Zhou, Robin Doss, Weijia Jia, “Traceback of DDoS Attacks
Using Entropy Variations”, IEEE, March 2011