Honeyd is a tool that enables setting up multiple virtual honeypots on a single machine, each with different characteristics and services. It simulates entire networks and can claim up to 65,536 IP addresses. Honeyd responds appropriately to fingerprinting tools to emulate different operating systems. The document discusses implementing Honeyd to simulate virtual honeypots, along with Snort for intrusion detection and MySQL for logging. Results show Honeyd effectively collected information on attack sources and traffic to the virtual honeypots.
Honeypots are information systems designed to detect cyber threats. They emulate vulnerabilities to lure attackers and observe their behavior without authorization. There are two main types: low-interaction honeypots, which emulate services and capture limited data, and high-interaction honeypots, which use real systems and services to gather extensive information but pose higher risks. Honeypots help identify weaknesses, catch attackers, and design more secure networks by compiling logs of unauthorized activity without affecting authorized usage.
This document provides a summary of honeypots and honeynets. It discusses the history of honeypots dating back to 1991 publications. It describes low and high interaction honeypots, concepts like placement of honeypots inside or outside firewalls, and types of honeynets. The document aims to help students understand how to use honeypots and honeynets to track hackers and detect or prevent attacks on networks.
This document provides an overview of honeypots, which are security resources that are intended to be probed, attacked, or compromised in order to gather information about attackers. Honeypots can be used to learn about past attacks, detect currently occurring attacks, and identify new types of attacks. They work by monitoring any traffic to resources that are not expected to receive data. Honeypots have advantages like reducing false alarms and providing data for analysis, but also have disadvantages like narrow visibility and risks of the attacker using the honeypot to attack other systems. The document discusses different types of honeypots including low and high interaction honeypots, and specific honeypot tools like Honeyd and Honeynets.
This document describes the design and implementation of Honeyd to simulate virtual honeypots. Honeyd is a tool that enables multiple virtual honeypots to be created on a single machine, each with different characteristics and services. It simulates entire networks and can be configured to run services like FTP, HTTP, SMTP. Honeyd assigns IP addresses to the virtual honeypots and uses scripts to simulate different operating systems. The implementation uses Honeyd, Snort, MySQL and scripts to generate reports from the honeypot logs to analyze attacks on the virtual honeypots.
This document discusses honeypots, which are decoy computer systems used to gather intelligence about cyber attacks. It defines honeypots and classifies them based on interaction level, implementation, and purpose. Specific honeypot tools are also outlined, including Honeyd and Honeynet. Honeyd simulates entire networks on a single host using simple functionality. Honeynet involves deploying multiple high-interaction honeypots on a private network. Advantages of honeypots include collecting high value data at low cost while limiting false alarms. Risks and fingerprinting are challenges. Overall, honeypots provide a flexible security tool for monitoring attacks.
This document summarizes a technical report about a framework called Honeyd that allows for the creation of virtual honeypots. Honeyd simulates entire computer systems at the network level by emulating different operating system behaviors and can provide arbitrary routing topologies and services. It is designed to deceive network fingerprinting and mapping tools for security purposes such as detecting attacks and studying adversaries.
This document provides an introduction to honeypots, which are computing resources used to gather security information. It discusses different types of honeypots classified by interaction level (high or low), implementation (physical or virtual), and purpose (production or research). Specific honeypot tools are also outlined, including Honeyd, a low interaction virtual honeypot, and Honeynet, a high interaction network of honeypots. The advantages of honeypots include collecting high value data sets while reducing false positives. Disadvantages include limited visibility and potential risks. In conclusion, honeypots are effective for observing attackers and preparing defenses against future attacks.
This document provides an overview of honeypots, including what they are, how they are classified, examples like Honeyd and Honeynet, advantages and disadvantages. Honeypots are computer resources used to gather threat intelligence by allowing unauthorized access. They can be classified by interaction level, implementation method, and purpose. Examples discussed are Honeyd, an open source low interaction virtual honeypot, and Honeynet, a high interaction architecture using multiple honeypots on a private network. Honeypots provide benefits like collecting small high value data sets and reduced false positives, but have limitations such as a limited view of attacks.
Honeypots are information systems designed to detect cyber threats. They emulate vulnerabilities to lure attackers and observe their behavior without authorization. There are two main types: low-interaction honeypots, which emulate services and capture limited data, and high-interaction honeypots, which use real systems and services to gather extensive information but pose higher risks. Honeypots help identify weaknesses, catch attackers, and design more secure networks by compiling logs of unauthorized activity without affecting authorized usage.
This document provides a summary of honeypots and honeynets. It discusses the history of honeypots dating back to 1991 publications. It describes low and high interaction honeypots, concepts like placement of honeypots inside or outside firewalls, and types of honeynets. The document aims to help students understand how to use honeypots and honeynets to track hackers and detect or prevent attacks on networks.
This document provides an overview of honeypots, which are security resources that are intended to be probed, attacked, or compromised in order to gather information about attackers. Honeypots can be used to learn about past attacks, detect currently occurring attacks, and identify new types of attacks. They work by monitoring any traffic to resources that are not expected to receive data. Honeypots have advantages like reducing false alarms and providing data for analysis, but also have disadvantages like narrow visibility and risks of the attacker using the honeypot to attack other systems. The document discusses different types of honeypots including low and high interaction honeypots, and specific honeypot tools like Honeyd and Honeynets.
This document describes the design and implementation of Honeyd to simulate virtual honeypots. Honeyd is a tool that enables multiple virtual honeypots to be created on a single machine, each with different characteristics and services. It simulates entire networks and can be configured to run services like FTP, HTTP, SMTP. Honeyd assigns IP addresses to the virtual honeypots and uses scripts to simulate different operating systems. The implementation uses Honeyd, Snort, MySQL and scripts to generate reports from the honeypot logs to analyze attacks on the virtual honeypots.
This document discusses honeypots, which are decoy computer systems used to gather intelligence about cyber attacks. It defines honeypots and classifies them based on interaction level, implementation, and purpose. Specific honeypot tools are also outlined, including Honeyd and Honeynet. Honeyd simulates entire networks on a single host using simple functionality. Honeynet involves deploying multiple high-interaction honeypots on a private network. Advantages of honeypots include collecting high value data at low cost while limiting false alarms. Risks and fingerprinting are challenges. Overall, honeypots provide a flexible security tool for monitoring attacks.
This document summarizes a technical report about a framework called Honeyd that allows for the creation of virtual honeypots. Honeyd simulates entire computer systems at the network level by emulating different operating system behaviors and can provide arbitrary routing topologies and services. It is designed to deceive network fingerprinting and mapping tools for security purposes such as detecting attacks and studying adversaries.
This document provides an introduction to honeypots, which are computing resources used to gather security information. It discusses different types of honeypots classified by interaction level (high or low), implementation (physical or virtual), and purpose (production or research). Specific honeypot tools are also outlined, including Honeyd, a low interaction virtual honeypot, and Honeynet, a high interaction network of honeypots. The advantages of honeypots include collecting high value data sets while reducing false positives. Disadvantages include limited visibility and potential risks. In conclusion, honeypots are effective for observing attackers and preparing defenses against future attacks.
This document provides an overview of honeypots, including what they are, how they are classified, examples like Honeyd and Honeynet, advantages and disadvantages. Honeypots are computer resources used to gather threat intelligence by allowing unauthorized access. They can be classified by interaction level, implementation method, and purpose. Examples discussed are Honeyd, an open source low interaction virtual honeypot, and Honeynet, a high interaction architecture using multiple honeypots on a private network. Honeypots provide benefits like collecting small high value data sets and reduced false positives, but have limitations such as a limited view of attacks.
This document provides an overview of honeypots and their uses. It defines a honeypot as a decoy information system used to gather intelligence on attackers. Honeypots are classified by level of interaction (high or low), implementation (physical or virtual), and purpose (production or research). Popular honeypot tools include Honeyd, which can simulate entire networks, and Honeynet, which uses multiple high-interaction honeypots. The advantages of honeypots are that they can collect high value data with few false positives at low cost. Their disadvantages include limited visibility and risks if compromised. Overall, honeypots are a flexible security tool primarily used for detection and information gathering.
This document discusses honeypots and the honeyd software. Honeypots are decoy servers that are used to detect intruders by appearing as normal servers but containing fake data. Honeyd is a honeypot daemon that can simulate a large network using a single host by creating virtual hosts with different personalities. It is used for distraction, detecting suspicious traffic, and learning about attack techniques. The document describes how to configure honeyd by setting virtual host properties and firewall rules to forward traffic to it.
This paper proposes using a honeypot to improve the efficiency of intrusion detection systems (IDS) in detecting zero-day attacks. It presents a network architecture that deploys a honeypot and uses packet analysis tools to generate IDS signatures for new attacks. The honeypot records an attacker's activities without their knowledge. The recorded data is analyzed to write custom IDS rules matching payloads to detect similar future attacks. This allows the IDS to identify threats even without prior signatures.
An Approach to for Improving the Efficiency of IDS System Using HoneypotEditor Jacotech
This paper proposes using a honeypot to improve the efficiency of intrusion detection systems (IDS) in detecting zero-day attacks. It presents a network architecture that incorporates a honeypot server to log attacker activities. These logs are analyzed using tcpdump to generate custom IDS rules matching the payload. This allows the IDS to detect new attacks before they harm the internal network. The honeypot attracts attackers by emulating servers and records their interactions without affecting production systems.
This paper proposes using a honeypot to improve the efficiency of intrusion detection systems (IDS) in detecting zero-day attacks. It presents a network architecture that incorporates a honeypot server to log attacker activities. These logs are analyzed using tcpdump to generate custom IDS rules matching the payload. This allows the IDS to detect new attacks before they harm the internal network. The honeypot attracts attackers by emulating servers and records their interactions without affecting production systems.
1) The document proposes enhancing IDS systems with honeypot placement to detect zero-day attacks. A new network architecture is designed where honeypots attract attackers and log their activities to generate IDS signatures.
2) Experimental setup involves deploying a honeypot server using Honeyd and Arpd to monitor unused IP space and direct attacks. Tcpdump is used to analyze traffic and payloads directed at the honeypot.
3) Analysis of honeypot logs is used to write custom IDS rules matching observed payloads. This allows detection of new attacks before they can harm the internal network.
Node-RED and Minecraft - CamJam September 2015Boris Adryan
This workshop uses the Node-RED framework as development tool for JavaScript. Building on functionality available for generic programming challenges, we’re going to use the communication standard TCP (Transmission Control Protocol) to interact with the Minecraft API (Application Programming Interface). The material is aimed at people who have had first experience with the Minecraft API on a Raspberry Pi (say, using Python), who now want to understand what's going on behind the scenes and what TCP, API and all those other acronyms mean. It also introduces flow-based programming concepts.
Node red & IoT - IEDC Hardware Club, April 8th 2016Sebin Benjamin
Node-RED is a flow-based development tool for visual programming developed originally by IBM for wiring together hardware devices, APIs and online services as part of the Internet of Things. Node-RED provides a web browser-based flow editor, which can be used to create JavaScript functions.
RGB LED in Arduino with an Oscilloscope
• Generating QR Code
• 3D Printing
• Web Video Cam
• Digi Clock with Real Time Clock
• Android SeekBar to Arduino LED Matrix
1. The document discusses using an Arduino board to control an LED light via a web server and browser. It provides code to set up an HTTP server on the Arduino that can turn the LED on or off by sending GET requests from a browser to specific URLs.
2. The code creates an TIdCustomHTTPServer object to set up the web server on the Arduino. It configures the server port and IP address. GET requests to URLs like 127.0.0.1:8000/LED will turn the LED on, while 127.0.0.1:8000/DEL will turn it off.
3. The document provides background on topics like HTTP, TCP/IP, IP addresses
This document summarizes an Internet census conducted in 2012 that involved port scanning the entire IPv4 address space using insecure embedded devices accessed with default or empty credentials. Over 420,000 devices were accessed to build a distributed port scanner network. Various scanning methods were used including ICMP ping, reverse DNS, Nmap scans, service probes, and traceroutes to gather data on open ports, network services, and network topology. The data gathered is being released publicly to further the study of Internet infrastructure and device security.
This document provides an overview of honeypots, which are decoy computer systems used to detect attacks. It discusses different types of honeypots classified by interaction level (low, medium, high) and purpose (research, production). Low interaction honeypots have limited interaction, while high interaction honeypots provide a realistic experience for attackers but carry more risk. The document also outlines how honeypots work, describing their ability to lure attackers by emulating real systems and then monitoring their activities. Honeypots provide valuable data for analyzing attack techniques while posing minimal risk to organizations' real networks and systems.
Node-RED and getting started on the Internet of ThingsBoris Adryan
The document provides information about a Node-RED workshop that will teach participants how to use Node-RED to interact with a Ciseco Slice of Radio device connected to a Raspberry Pi. Node-RED is a visual tool for wiring the Internet of Things that allows non-programmers to create IoT workflows by connecting pre-defined nodes without complex coding. The workshop will have participants use Node-RED to receive sensor data from the Slice of Radio and send it to online IoT platforms, as well as control wireless actuators. Background is provided on the software and hardware setup already installed on the Raspberry Pis to be used. Step-by-step exercises are outlined to start Node-RED and create a simple flow
This document discusses honeypots, which are decoy computer systems used to gather intelligence about cyber attacks. Honeypots can be classified based on their level of interaction, implementation, and purpose. Low-interaction honeypots like Honeyd simulate some system aspects with minimal risk, while high-interaction honeypots like Honeynet aim to be fully compromised. Honeynets form a network of honeypots to capture extensive attack information for research. The document outlines the architecture and functionality of Honeyd and Honeynet honeypots. Honeypots provide benefits like reduced false alarms and insights into attacker techniques, but also pose risks if they are detected.
This document discusses honeypots, which are decoy computer systems used to gather intelligence about cyber attacks. Honeypots can be classified based on their level of interaction, implementation, and purpose. Low-interaction honeypots like Honeyd simulate some system aspects with minimal risk, while high-interaction honeypots like Honeynet aim to be fully compromised. Honeynets form a network of honeypots to capture extensive attack information for research. The document outlines the architecture and functionality of Honeyd and Honeynet honeypots. Honeypots provide benefits like reduced false alarms and insights into attacker techniques, but also pose risks if they are detected.
Here are three additional new security tools or techniques beyond what was discussed in the text, along with an analysis of their potential:
1. Deception technologies: Tools that deploy deceptive measures like honeypots, honeynets, and decoy documents/credentials to identify and study cyber attacks without putting real systems at risk. These have strong potential to gather threat intelligence and improve defenses.
2. Blockchain authentication: Using distributed ledger technologies like blockchain to securely store credentials and authenticate users. By distributing credential data across multiple nodes, it eliminates single points of failure and could help reduce identity theft if widely adopted.
3. AI-powered behavioral analytics: Leveraging machine learning to analyze patterns in user and system behavior over time
This document provides a study cheat sheet for the CEH v9 certification. It includes definitions and explanations of various cybersecurity topics like subnet addressing, types of network attacks (teardrop, SMURF, FRAGGLE), TCP/UDP ports, malware types (bot, worm), and network protocols (NTP, DNS). It also provides summaries of NIST risk assessment methodology, Microsoft SDL practices, and wireless security protocols (WPA, WPA2, CCMP). Finally, it includes questions about tools (Nmap, Nikto, NetStumbler), OS exploits (WebGoat), and compliance requirements (PCI DSS).
A significant proportion of developments in the Internet of Things (IoT) is driven by non-technical innovators and ambitious hobbyists. Node-RED targets this audience and offers a widely used rapid prototyping platform for IoT data plumbing on the basis of JavaScript. Data platforms for the IoT provide storage facilities and value in the form of visualisation & analytics to business and end users alike. This report details how Node-RED connects to 11 different platforms and what additional services these provide.
This document provides an overview of honeypots and the Honeynet Project. Honeypots are fake computer systems designed to attract and monitor hackers. They allow researchers to gather data on hacking techniques without endangering real systems. The document discusses low and high interaction honeypots, virtual versus physical honeypots, and how honeypots are used to collect information on attackers. It also provides an overview of the Honeynet Project, which uses entire networks of high interaction honeypots to obtain in-depth data on hacker tactics and tools.
The document proposes an idea for developing a personal robot (PR) industry by utilizing cloud computing. It suggests that a standard robot hardware platform like the PR2 could access different software algorithms stored on cloud servers to perform a variety of tasks, without needing to reprogram the robot each time. This could make the robots more affordable and capable by distributing computing power. The document outlines how a company could operate a cloud server offering algorithms to robots for various uses like housework or industrial tasks. It also discusses potential benefits, obstacles, and an industrial structure for this proposed PR industry model.
This document provides a technical review of secure banking using RSA and AES encryption methodologies. It discusses how RSA and AES are commonly used encryption standards for secure data transmission between ATMs and bank servers. The document first provides background on ATM security measures and risks of attacks. It then reviews related work analyzing encryption techniques. The document proposes using a one-time password in addition to a PIN for ATM authentication. It concludes that implementing encryption standards like RSA and AES can make transactions more secure and build trust in online banking.
This document analyzes the performance of various modulation schemes for achieving energy efficient communication over fading channels in wireless sensor networks. It finds that for long transmission distances, low-order modulations like BPSK are optimal due to their lower SNR requirements. However, as transmission distance decreases, higher-order modulations like 16-QAM and 64-QAM become more optimal since they can transmit more bits per symbol, outweighing their higher SNR needs. Simulations show lifetime extensions up to 550% are possible in short-range networks by using higher-order modulations instead of just BPSK. The optimal modulation depends on transmission distance and balancing the energy used by electronic components versus power amplifiers.
More Related Content
Similar to Design & Implementation of Honeyd to Simulate Virtual Honeypots
This document provides an overview of honeypots and their uses. It defines a honeypot as a decoy information system used to gather intelligence on attackers. Honeypots are classified by level of interaction (high or low), implementation (physical or virtual), and purpose (production or research). Popular honeypot tools include Honeyd, which can simulate entire networks, and Honeynet, which uses multiple high-interaction honeypots. The advantages of honeypots are that they can collect high value data with few false positives at low cost. Their disadvantages include limited visibility and risks if compromised. Overall, honeypots are a flexible security tool primarily used for detection and information gathering.
This document discusses honeypots and the honeyd software. Honeypots are decoy servers that are used to detect intruders by appearing as normal servers but containing fake data. Honeyd is a honeypot daemon that can simulate a large network using a single host by creating virtual hosts with different personalities. It is used for distraction, detecting suspicious traffic, and learning about attack techniques. The document describes how to configure honeyd by setting virtual host properties and firewall rules to forward traffic to it.
This paper proposes using a honeypot to improve the efficiency of intrusion detection systems (IDS) in detecting zero-day attacks. It presents a network architecture that deploys a honeypot and uses packet analysis tools to generate IDS signatures for new attacks. The honeypot records an attacker's activities without their knowledge. The recorded data is analyzed to write custom IDS rules matching payloads to detect similar future attacks. This allows the IDS to identify threats even without prior signatures.
An Approach to for Improving the Efficiency of IDS System Using HoneypotEditor Jacotech
This paper proposes using a honeypot to improve the efficiency of intrusion detection systems (IDS) in detecting zero-day attacks. It presents a network architecture that incorporates a honeypot server to log attacker activities. These logs are analyzed using tcpdump to generate custom IDS rules matching the payload. This allows the IDS to detect new attacks before they harm the internal network. The honeypot attracts attackers by emulating servers and records their interactions without affecting production systems.
This paper proposes using a honeypot to improve the efficiency of intrusion detection systems (IDS) in detecting zero-day attacks. It presents a network architecture that incorporates a honeypot server to log attacker activities. These logs are analyzed using tcpdump to generate custom IDS rules matching the payload. This allows the IDS to detect new attacks before they harm the internal network. The honeypot attracts attackers by emulating servers and records their interactions without affecting production systems.
1) The document proposes enhancing IDS systems with honeypot placement to detect zero-day attacks. A new network architecture is designed where honeypots attract attackers and log their activities to generate IDS signatures.
2) Experimental setup involves deploying a honeypot server using Honeyd and Arpd to monitor unused IP space and direct attacks. Tcpdump is used to analyze traffic and payloads directed at the honeypot.
3) Analysis of honeypot logs is used to write custom IDS rules matching observed payloads. This allows detection of new attacks before they can harm the internal network.
Node-RED and Minecraft - CamJam September 2015Boris Adryan
This workshop uses the Node-RED framework as development tool for JavaScript. Building on functionality available for generic programming challenges, we’re going to use the communication standard TCP (Transmission Control Protocol) to interact with the Minecraft API (Application Programming Interface). The material is aimed at people who have had first experience with the Minecraft API on a Raspberry Pi (say, using Python), who now want to understand what's going on behind the scenes and what TCP, API and all those other acronyms mean. It also introduces flow-based programming concepts.
Node red & IoT - IEDC Hardware Club, April 8th 2016Sebin Benjamin
Node-RED is a flow-based development tool for visual programming developed originally by IBM for wiring together hardware devices, APIs and online services as part of the Internet of Things. Node-RED provides a web browser-based flow editor, which can be used to create JavaScript functions.
RGB LED in Arduino with an Oscilloscope
• Generating QR Code
• 3D Printing
• Web Video Cam
• Digi Clock with Real Time Clock
• Android SeekBar to Arduino LED Matrix
1. The document discusses using an Arduino board to control an LED light via a web server and browser. It provides code to set up an HTTP server on the Arduino that can turn the LED on or off by sending GET requests from a browser to specific URLs.
2. The code creates an TIdCustomHTTPServer object to set up the web server on the Arduino. It configures the server port and IP address. GET requests to URLs like 127.0.0.1:8000/LED will turn the LED on, while 127.0.0.1:8000/DEL will turn it off.
3. The document provides background on topics like HTTP, TCP/IP, IP addresses
This document summarizes an Internet census conducted in 2012 that involved port scanning the entire IPv4 address space using insecure embedded devices accessed with default or empty credentials. Over 420,000 devices were accessed to build a distributed port scanner network. Various scanning methods were used including ICMP ping, reverse DNS, Nmap scans, service probes, and traceroutes to gather data on open ports, network services, and network topology. The data gathered is being released publicly to further the study of Internet infrastructure and device security.
This document provides an overview of honeypots, which are decoy computer systems used to detect attacks. It discusses different types of honeypots classified by interaction level (low, medium, high) and purpose (research, production). Low interaction honeypots have limited interaction, while high interaction honeypots provide a realistic experience for attackers but carry more risk. The document also outlines how honeypots work, describing their ability to lure attackers by emulating real systems and then monitoring their activities. Honeypots provide valuable data for analyzing attack techniques while posing minimal risk to organizations' real networks and systems.
Node-RED and getting started on the Internet of ThingsBoris Adryan
The document provides information about a Node-RED workshop that will teach participants how to use Node-RED to interact with a Ciseco Slice of Radio device connected to a Raspberry Pi. Node-RED is a visual tool for wiring the Internet of Things that allows non-programmers to create IoT workflows by connecting pre-defined nodes without complex coding. The workshop will have participants use Node-RED to receive sensor data from the Slice of Radio and send it to online IoT platforms, as well as control wireless actuators. Background is provided on the software and hardware setup already installed on the Raspberry Pis to be used. Step-by-step exercises are outlined to start Node-RED and create a simple flow
This document discusses honeypots, which are decoy computer systems used to gather intelligence about cyber attacks. Honeypots can be classified based on their level of interaction, implementation, and purpose. Low-interaction honeypots like Honeyd simulate some system aspects with minimal risk, while high-interaction honeypots like Honeynet aim to be fully compromised. Honeynets form a network of honeypots to capture extensive attack information for research. The document outlines the architecture and functionality of Honeyd and Honeynet honeypots. Honeypots provide benefits like reduced false alarms and insights into attacker techniques, but also pose risks if they are detected.
This document discusses honeypots, which are decoy computer systems used to gather intelligence about cyber attacks. Honeypots can be classified based on their level of interaction, implementation, and purpose. Low-interaction honeypots like Honeyd simulate some system aspects with minimal risk, while high-interaction honeypots like Honeynet aim to be fully compromised. Honeynets form a network of honeypots to capture extensive attack information for research. The document outlines the architecture and functionality of Honeyd and Honeynet honeypots. Honeypots provide benefits like reduced false alarms and insights into attacker techniques, but also pose risks if they are detected.
Here are three additional new security tools or techniques beyond what was discussed in the text, along with an analysis of their potential:
1. Deception technologies: Tools that deploy deceptive measures like honeypots, honeynets, and decoy documents/credentials to identify and study cyber attacks without putting real systems at risk. These have strong potential to gather threat intelligence and improve defenses.
2. Blockchain authentication: Using distributed ledger technologies like blockchain to securely store credentials and authenticate users. By distributing credential data across multiple nodes, it eliminates single points of failure and could help reduce identity theft if widely adopted.
3. AI-powered behavioral analytics: Leveraging machine learning to analyze patterns in user and system behavior over time
This document provides a study cheat sheet for the CEH v9 certification. It includes definitions and explanations of various cybersecurity topics like subnet addressing, types of network attacks (teardrop, SMURF, FRAGGLE), TCP/UDP ports, malware types (bot, worm), and network protocols (NTP, DNS). It also provides summaries of NIST risk assessment methodology, Microsoft SDL practices, and wireless security protocols (WPA, WPA2, CCMP). Finally, it includes questions about tools (Nmap, Nikto, NetStumbler), OS exploits (WebGoat), and compliance requirements (PCI DSS).
A significant proportion of developments in the Internet of Things (IoT) is driven by non-technical innovators and ambitious hobbyists. Node-RED targets this audience and offers a widely used rapid prototyping platform for IoT data plumbing on the basis of JavaScript. Data platforms for the IoT provide storage facilities and value in the form of visualisation & analytics to business and end users alike. This report details how Node-RED connects to 11 different platforms and what additional services these provide.
This document provides an overview of honeypots and the Honeynet Project. Honeypots are fake computer systems designed to attract and monitor hackers. They allow researchers to gather data on hacking techniques without endangering real systems. The document discusses low and high interaction honeypots, virtual versus physical honeypots, and how honeypots are used to collect information on attackers. It also provides an overview of the Honeynet Project, which uses entire networks of high interaction honeypots to obtain in-depth data on hacker tactics and tools.
The document proposes an idea for developing a personal robot (PR) industry by utilizing cloud computing. It suggests that a standard robot hardware platform like the PR2 could access different software algorithms stored on cloud servers to perform a variety of tasks, without needing to reprogram the robot each time. This could make the robots more affordable and capable by distributing computing power. The document outlines how a company could operate a cloud server offering algorithms to robots for various uses like housework or industrial tasks. It also discusses potential benefits, obstacles, and an industrial structure for this proposed PR industry model.
Similar to Design & Implementation of Honeyd to Simulate Virtual Honeypots (20)
This document provides a technical review of secure banking using RSA and AES encryption methodologies. It discusses how RSA and AES are commonly used encryption standards for secure data transmission between ATMs and bank servers. The document first provides background on ATM security measures and risks of attacks. It then reviews related work analyzing encryption techniques. The document proposes using a one-time password in addition to a PIN for ATM authentication. It concludes that implementing encryption standards like RSA and AES can make transactions more secure and build trust in online banking.
This document analyzes the performance of various modulation schemes for achieving energy efficient communication over fading channels in wireless sensor networks. It finds that for long transmission distances, low-order modulations like BPSK are optimal due to their lower SNR requirements. However, as transmission distance decreases, higher-order modulations like 16-QAM and 64-QAM become more optimal since they can transmit more bits per symbol, outweighing their higher SNR needs. Simulations show lifetime extensions up to 550% are possible in short-range networks by using higher-order modulations instead of just BPSK. The optimal modulation depends on transmission distance and balancing the energy used by electronic components versus power amplifiers.
This document provides a review of mobility management techniques in vehicular ad hoc networks (VANETs). It discusses three modes of communication in VANETs: vehicle-to-infrastructure (V2I), vehicle-to-vehicle (V2V), and hybrid vehicle (HV) communication. For each communication mode, different mobility management schemes are required due to their unique characteristics. The document also discusses mobility management challenges in VANETs and outlines some open research issues in improving mobility management for seamless communication in these dynamic networks.
This document provides a review of different techniques for segmenting brain MRI images to detect tumors. It compares the K-means and Fuzzy C-means clustering algorithms. K-means is an exclusive clustering algorithm that groups data points into distinct clusters, while Fuzzy C-means is an overlapping clustering algorithm that allows data points to belong to multiple clusters. The document finds that Fuzzy C-means requires more time for brain tumor detection compared to other methods like hierarchical clustering or K-means. It also reviews related work applying these clustering algorithms to segment brain MRI images.
1) The document simulates and compares the performance of AODV and DSDV routing protocols in a mobile ad hoc network under three conditions: when users are fixed, when users move towards the base station, and when users move away from the base station.
2) The results show that both protocols have higher packet delivery and lower packet loss when users are either fixed or moving towards the base station, since signal strength is better in those scenarios. Performance degrades when users move away from the base station due to weaker signals.
3) AODV generally has better performance than DSDV, with higher throughput and packet delivery rates observed across the different user mobility conditions.
This document describes the design and implementation of 4-bit QPSK and 256-bit QAM modulation techniques using MATLAB. It compares the two techniques based on SNR, BER, and efficiency. The key steps of implementing each technique in MATLAB are outlined, including generating random bits, modulation, adding noise, and measuring BER. Simulation results show scatter plots and eye diagrams of the modulated signals. A table compares the results, showing that 256-bit QAM provides better performance than 4-bit QPSK. The document concludes that QAM modulation is more effective for digital transmission systems.
The document proposes a hybrid technique using Anisotropic Scale Invariant Feature Transform (A-SIFT) and Robust Ensemble Support Vector Machine (RESVM) to accurately identify faces in images. A-SIFT improves upon traditional SIFT by applying anisotropic scaling to extract richer directional keypoints. Keypoints are processed with RESVM and hypothesis testing to increase accuracy above 95% by repeatedly reprocessing images until the threshold is met. The technique was tested on similar and different facial images and achieved better results than SIFT in retrieval time and reduced keypoints.
This document studies the effects of dielectric superstrate thickness on microstrip patch antenna parameters. Three types of probes-fed patch antennas (rectangular, circular, and square) were designed to operate at 2.4 GHz using Arlondiclad 880 substrate. The antennas were tested with and without an Arlondiclad 880 superstrate of varying thicknesses. It was found that adding a superstrate slightly degraded performance by lowering the resonant frequency and increasing return loss and VSWR, while decreasing bandwidth and gain. Specifically, increasing the superstrate thickness or dielectric constant resulted in greater changes to the antenna parameters.
This document describes a wireless environment monitoring system that utilizes soil energy as a sustainable power source for wireless sensors. The system uses a microbial fuel cell to generate electricity from the microbial activity in soil. Two microbial fuel cells were created using different soil types and various additives to produce different current and voltage outputs. An electronic circuit was designed on a printed circuit board with components like a microcontroller and ZigBee transceiver. Sensors for temperature and humidity were connected to the circuit to monitor the environment wirelessly. The system provides a low-cost way to power remote sensors without needing battery replacement and avoids the high costs of wiring a power source.
1) The document proposes a model for a frequency tunable inverted-F antenna that uses ferrite material.
2) The resonant frequency of the antenna can be significantly shifted from 2.41GHz to 3.15GHz, a 31% shift, by increasing the static magnetic field placed on the ferrite material.
3) Altering the permeability of the ferrite allows tuning of the antenna's resonant frequency without changing the physical dimensions, providing flexibility to operate over a wide frequency range.
This document summarizes a research paper that presents a speech enhancement method using stationary wavelet transform. The method first classifies speech into voiced, unvoiced, and silence regions based on short-time energy. It then applies different thresholding techniques to the wavelet coefficients of each region - modified hard thresholding for voiced speech, semi-soft thresholding for unvoiced speech, and setting coefficients to zero for silence. Experimental results using speech from the TIMIT database corrupted with white Gaussian noise at various SNR levels show improved performance over other popular denoising methods.
This document reviews the design of an energy-optimized wireless sensor node that encrypts data for transmission. It discusses how sensing schemes that group nodes into clusters and transmit aggregated data can reduce energy consumption compared to individual node transmissions. The proposed node design calculates the minimum transmission power needed based on received signal strength and uses a periodic sleep/wake cycle to optimize energy when not sensing or transmitting. It aims to encrypt data at both the node and network level to further optimize energy usage for wireless communication.
This document discusses group consumption modes. It analyzes factors that impact group consumption, including external environmental factors like technological developments enabling new forms of online and offline interactions, as well as internal motivational factors at both the group and individual level. The document then proposes that group consumption modes can be divided into four types based on two dimensions: vertical (group relationship intensity) and horizontal (consumption action period). These four types are instrument-oriented, information-oriented, enjoyment-oriented, and relationship-oriented consumption modes. Finally, the document notes that consumption modes are dynamic and can evolve over time.
The document summarizes a study of different microstrip patch antenna configurations with slotted ground planes. Three antenna designs were proposed and their performance evaluated through simulation: a conventional square patch, an elliptical patch, and a star-shaped patch. All antennas were mounted on an FR4 substrate. The effects of adding different slot patterns to the ground plane on resonance frequency, bandwidth, gain and efficiency were analyzed parametrically. Key findings were that reshaping the patch and adding slots increased bandwidth and shifted resonance frequency. The elliptical and star patches in particular performed better than the conventional design. Three antenna configurations were selected for fabrication and measurement based on the simulations: a conventional patch with a slot under the patch, an elliptical patch with slots
1) The document describes a study conducted to improve call drop rates in a GSM network through RF optimization.
2) Drive testing was performed before and after optimization using TEMS software to record network parameters like RxLevel, RxQuality, and events.
3) Analysis found call drops were occurring due to issues like handover failures between sectors, interference from adjacent channels, and overshooting due to antenna tilt.
4) Corrective actions taken included defining neighbors between sectors, adjusting frequencies to reduce interference, and lowering the mechanical tilt of an antenna.
5) Post-optimization drive testing showed improvements in RxLevel, RxQuality, and a reduction in dropped calls.
This document describes the design of an intelligent autonomous wheeled robot that uses RF transmission for communication. The robot has two modes - automatic mode where it can make its own decisions, and user control mode where a user can control it remotely. It is designed using a microcontroller and can perform tasks like object recognition using computer vision and color detection in MATLAB, as well as wall painting using pneumatic systems. The robot's movement is controlled by DC motors and it uses sensors like ultrasonic sensors and gas sensors to navigate autonomously. RF transmission allows communication between the robot and a remote control unit. The overall aim is to develop a low-cost robotic system for industrial applications like material handling.
This document reviews cryptography techniques to secure the Ad-hoc On-Demand Distance Vector (AODV) routing protocol in mobile ad-hoc networks. It discusses various types of attacks on AODV like impersonation, denial of service, eavesdropping, black hole attacks, wormhole attacks, and Sybil attacks. It then proposes using the RC6 cryptography algorithm to secure AODV by encrypting data packets and detecting and removing malicious nodes launching black hole attacks. Simulation results show that after applying RC6, the packet delivery ratio and throughput of AODV increase while delay decreases, improving the security and performance of the network under attack.
The document describes a proposed modification to the conventional Booth multiplier that aims to increase its speed by applying concepts from Vedic mathematics. Specifically, it utilizes the Urdhva Tiryakbhyam formula to generate all partial products concurrently rather than sequentially. The proposed 8x8 bit multiplier was coded in VHDL, simulated, and found to have a path delay 44.35% lower than a conventional Booth multiplier, demonstrating its potential for higher speed.
This document discusses image deblurring techniques. It begins by introducing image restoration and focusing on image deblurring. It then discusses challenges with image deblurring being an ill-posed problem. It reviews existing approaches to screen image deconvolution including estimating point spread functions and iteratively estimating blur kernels and sharp images. The document also discusses handling spatially variant blur and summarizes the relationship between the proposed method and previous work for different blur types. It proposes using color filters in the aperture to exploit parallax cues for segmentation and blur estimation. Finally, it proposes moving the image sensor circularly during exposure to prevent high frequency attenuation from motion blur.
This document describes modeling an adaptive controller for an aircraft roll control system using PID, fuzzy-PID, and genetic algorithm. It begins by introducing the aircraft roll control system and motivation for developing an adaptive controller to minimize errors from noisy analog sensor signals. It then provides the mathematical model of aircraft roll dynamics and describes modeling the real-time flight control system in MATLAB/Simulink. The document evaluates PID, fuzzy-PID, and PID-GA (genetic algorithm) controllers for aircraft roll control and finds that the PID-GA controller delivers the best performance.
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Project Management Semester Long Project - Acuityjpupo2018
Acuity is an innovative learning app designed to transform the way you engage with knowledge. Powered by AI technology, Acuity takes complex topics and distills them into concise, interactive summaries that are easy to read & understand. Whether you're exploring the depths of quantum mechanics or seeking insight into historical events, Acuity provides the key information you need without the burden of lengthy texts.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
Digital Marketing Trends in 2024 | Guide for Staying AheadWask
https://www.wask.co/ebooks/digital-marketing-trends-in-2024
Feeling lost in the digital marketing whirlwind of 2024? Technology is changing, consumer habits are evolving, and staying ahead of the curve feels like a never-ending pursuit. This e-book is your compass. Dive into actionable insights to handle the complexities of modern marketing. From hyper-personalization to the power of user-generated content, learn how to build long-term relationships with your audience and unlock the secrets to success in the ever-shifting digital landscape.
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceIndexBug
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
Design & Implementation of Honeyd to Simulate Virtual Honeypots
1. IOSR Journal of Computer Engineering (IOSRJCE)
ISSN: 2278-0661 Volume 3, Issue 1 (July-Aug. 2012), PP 28-34
www.iosrjournals.org
www.iosrjournals.org 28 | Page
Design & Implementation of Honeyd to Simulate Virtual
Honeypots
1
Bhumika, 2
Vivek Sharma
1,2
Department of Computer Science & Engineering
Abstract:Honeyd is an application which enables the setup of multiple virtual honeypots on a single machine,
each with different characteristics and services. It is a nice little tool which can be perfectly used to setup a low
to mid involvement honeypot. The possibility to generate different virtual honeypots on one machine with even
different simulated operating systems enhances the usability of this tool even further. It’s great for simulating
victims and collecting a lot of interesting information. Honeyd could be used as an early warning system in a
productive environment to catch some attacks and trigger an alert. Finding infected web or MS SQL servers can
be achieved. The mechanism of attaching a script to a certain port allows a very flexible setup with unlimited
capabilities and opportunities for tuning. Finally, the logs generated as well as attacks came on virtual systems
can be analyzed graphically using scripts and configuration files.
Keywords: Honeyd, honeypots, snort, virtualbox,
I. INTRODUCTION
Honeyd is an application which enables the setup of multiple virtual honeypots on a single machine,
each with different characteristics and services. Honeyd is a small daemon that runs both on UNIX-like and
Windows platforms. It is used to create multiple virtual honeypots on a single machine. Entire networks can be
simulated using honeyd. Honeyd can be configured to run a range of services like FTP, HTTP, or SMTP.
Furthermore, a personality can be configured to simulate a certain operating system. Honeyd allows a single
host to claim as many as 65536 IP addresses. Honeyd emulates operating systems by responding with
appropriate packets to Nmap and Xprobe fingerprinting packets. Thus the list of operating systems that honeyd
emulates can be found in nmap.prints and xprobe2.conf. But let’s start from the beginning i.e. the honeypot
technology before going to the details of honeyd.
II. HONEYPOT TECHNOLOGY
Honeypots aren’t something that new – the basic idea of a honeypot is quite old and was used already
for quite a long time. Although, the word “Honeypot” is a new one and the
technology is getting more and more important. But let’s first have a look at a possible definition of what a
honeypot is
“A honeypot is a resource which pretends to be a real target. A honeypot is expected to be attacked or
compromised.
A. Level of Interaction
The first category is installation and configuration effort, which defines the time and effort in installing
and configuring the honeypot. In general, if the level of interaction between the user and the honeypot is more
than the effort required to install and configure the honeypot is also significant.
The second category is deployment and mainteance. This category defines the time and effort involved
in deploying and maintaining the honeypot. Once again, the more functionality provided by the honeypot, the
more is the effort required to deploy and maintain the honeypot.
The third category is information gathering which means how much information can the honeypot gain
on attackers and their activities? High-interaction honeypots can gather vast amounts of information, whereas
low-interaction honeypots are highly limited. Finally, level of interaction impacts the amount of risk introduced.
The greater the level of interaction, the more functionality provided to the attacker and the greater the
complexity. Combined, these elements can introduce a great deal of risk. On the other hand, low-interaction
honeypots are very simple and offer a little interaction to attackers and thus a very little risk is associated with
them.
2. Design & Implementation of Honeyd to simulate Virtual Honeypots
www.iosrjournals.org 29 | Page
Table 1: Tradeoffs between Honeypot Levels of Interaction
III. HONEYD: A LOW INTERACTION HONEYPOT IN ACTION
Honeyd is a tool which simulates virtual hosts on a network, and is actively used in Honeynet research
today; it’s a thin daemon with lots of interesting features. It can assume the personality of any operating system,
and can be configured to offer different TCP/IP “services” like HTTP, SMTP, SSH etc. Honeyd is used in
honeynet research typically for setting up virtual honeypots to engage an attacker. One useful feature of Honeyd
is its ability to simulate an entire network topology within one machine – with multiple hops, packet losses and
latency. This lets us simulate complex networks in test labs; it could also present a make-believe network to an
attacker who gets snared in a honeynet.
Some of the features available in Honeyd for simulating networks are:
Simulation of large network topologies
Configurable network characteristics like latency, loss and bandwidth
Supports multiple entry routers to serve multiple networks
Integrate physical machines into the network topology
Asymmetric routing
GRE tunneling for setting up distributed networks
Another new concept is that Honeyd emulates an operating system not only at the application level but
at the IP stack level as well. For example, if one select his Honeyd system to emulate a Windows NT 4.0 Server
SP5-SP6 server, it not only emulates the services, such as an IIS Web server, but also the IP stack. In this case,
if one use Nmap to fingerprint the IP stack, the response will be that the IP stack is Windows NT 4.0 Server
SP5-SP6.
A. Setup details and Implementation
In our implementation, we have implemented the personality of various OS as virtual Honeypots. Using honeyd,
we can also simulate the large network topologies by writing scripts. In order to catch and categorize attacks, we
installed Snort in its latest version as well as Mysql for logging all snort events to the database for easier and
less time consuming analysis of collected attacks.
In this section, we discuss the design and implementation of Honeyd. Honeyd, developed by Neil Provis, is
implemented as a Unix daemon that runs on a workstation and listens to network traffic.
B. Proposed Design Overview
To implement the virtual Honeypot approach, we need the components listed below.
An active probing tool, such as Nmap.
A passive fingerprinting tool, such as P0f and Snort.
A low interaction honeypot used to simulate networks, such as Honeyd.
A collection of physical honeypots to receive redirected traffic. These honeypots are considered as a small but
representative sample of the most used operating systems on the network.
A Database, containing hosts’ description, and log information.
A Virtual software to implement redhat Linux.
An administrator’s interface to configure dynamic honeypot server in real time and view reports.
3. Design & Implementation of Honeyd to simulate Virtual Honeypots
www.iosrjournals.org 30 | Page
Fig. 1 Honeyd: A Low Interaction honeypot
A. Experimental Details
The experimental setup of our work is shown in the figure 2. Initially we assign a static IP addresses to
the window OS, virtual machine. We assign two unused IP address to two virtual honeypots respectively. We
assign 192.168.1.243 IP address to virtual honeypot1 and 192.168.1.244 IP address to virtual honeypot2.These
virtual honeypots corresponds to two different personalities as described in configuration file of honeyd named
honeyd.conf. The honeypot designed is proposed as a Low Interaction Honeypot which is integrated with Snort
and MySQL.
Fig.2 Experimental Setup
B. Oracle VM Virtual Box
Virtual Box is a cross-platform virtualization application. It can be installed on existing Intel or AMD-
based computers, whether they are running Windows, Mac, Linux or Solaris operating systems. It also extends
the capabilities of an existing computer so that it can run multiple operating systems (inside multiple virtual
machines) at the same time. For example, you can run Windows and Linux on your Mac, run Windows Server
2008 on your Linux server, run Linux on your Windows PC, and so on, all alongside your existing applications.
Virtual Box is deceptively simple yet also very powerful. It can run everywhere from small embedded systems
or desktop class machines all the way up to data center deployments and even Cloud environments.
C. Procedure
We start our work by writing personalities of virtual honeypots. We can write as many personalities in
honeyd.conf file. We have written two different personalities in our configuration file.
Then we write the command: arpd –d –i eth0 ”IP addresses in configuration file of honeyd”
Here we use the -d so that it does not run as a daemon or as a background process. Arpd daemon uses the
free address space and allocate the Mac address of the machine with each IP address.
After this honeyd is started by writing following command: honeyd -l /log/test –f honeyd.conf (IP
addresses in configuration file of honeyd). -f is used so that honeyd runs in foreground. By this command
honeyd is started as background process.
Then the MySQL database is started. In new tab snort is started by the command: snort -i eth0 –vc
/root/Desktop/honeyd/Latest_snort etc/snort.conf –l/var/log
Honeydsum.pl is used to generate a report from the packets logged by the honeyd. This is done by
following command: ./honeydsum.pl –c honeydsum.conf/root/Desktop/honeyd/log/test>report
Snortalog.pl is used to generate a report (graphically) from the alerts generated by snort. This is done by
the following command: perl snortalog.pl –file /var/log/alert –r N 30 – report
4. Design & Implementation of Honeyd to simulate Virtual Honeypots
www.iosrjournals.org 31 | Page
IV. HONEYD: IMPLEMENTATION DETAILS
First install the required libraries.
a. Libevent
b. Libdnet
c. Libpcap: used libpcap 0.7 and its dev file.
d. Libpcre
A “Honeyd.conf’ file is configured which contains virtual operating systems with emulated services. Each
system is designed with the following commands.
Create command create a new system.
Add command used to add services, therefore binding scripts to a certain port.
Set command assigns personality to a created system.
Install Honeyd
Downloaded honeyd-1.5c from http://www.citi.umich.edu/u/provos/honeyd/honeyd-1.5c.tar.gz
1) Running ARPD: The fake IP addresses are created with the help of Arpd daemon, which further
bind these IP addresses with different templates specified in “honeyd.conf” configuration file. In this file
The templates are created which are nothing but completely fake script modules for the different
operating systems. Some fake instances of different operating systems are created with fake IP addresses and
then bind the templates accordingly.
An Arpd ,also called farpd ,daemon can be installed which monitors the allocated IP address space and for any
IP address that no host respond with MAC address , farpd will respond with the Honeyd physical machine MAC
address.
2) Starting honeyd: Honeyd is a small daemon that runs both on UNIX-like and Windows platforms. It is used
to create multiple virtual honeypots on a single machine. Entire networks can be simulated using honeyd.
Honeyd can be configured to run a range of services like FTP, HTTP, or SMTP. Furthermore, a personality can
be configured to simulate a certain operating system.
Sample Honeyd Configuration File
create windows
set windows personality "Windows XP home edition"
add windows tcp port 80 "perl scripts/iis-0.95/iisemul8.pl"
add windows tcp port 139 open
add windows tcp port 137 open
add windows udp port 137 open
add windows udp port 135 open
set windows default tcp action reset
set windows default udp action reset
bind 192.168.1.243 windows
A sample honeyd configuration file named honeyd.conf is written above. In this file IP address
192.168.1.243 is assigned to virtual honeypot1.Similarly IP address 192.168.1.244 is assigned to the virtual
honeypot2.Then the packets are logged in a file named test. The command is
Honeyd –l/log/test –f honeyd.conf 192.168.1.243-192.168.1.244
Fig. 3 Honeyd: A Low Interaction honeypot
5. Design & Implementation of Honeyd to simulate Virtual Honeypots
www.iosrjournals.org 32 | Page
3) Starting MySQL services: MySQL is an Open Source Standard Query Language (SQL) database that is fast,
reliable, easy to use, and suitable for applications of any size. MySQL can easily be integrated into Perl
programs by using the Perl DBI (Database Independent interface) module. DBI is an Application Program
Interface (API) that allows Perl to connect to and query a number of SQL databases.MySQL is used here to
store the alerts generated by Snort. The command used to start the MYSQL is
service mysqld start;
4) Starting Snort: Snort is a libpcap-based packet sniffer/logger which can be used as a lightweight
network intrusion detection system. Snort has three primary uses: It can be used as a straight packet sniffer
like tcp dump, a packet logger or as a full blown network Intrusion prevention system. Snort is used here
to generate alerts and to capture more information about the attacks.
Command used to start snort is
Snort -i eth0 –vc etc/snort.conf –l/var/log.
After this command alerts generated by snort are stored in the file called log situated in var folder.
After initializing the snort we use sql query to display the number of alerts generated by snort in descending
order. The query is
Select s.sig_name,count(*)as count from event e,signature s where e.signature=s.sig_id group by e.signature
order by count desc;
Fig. 4 No. of alerts generated by snort
5) Starting Honeydsum: It is a script written in Perl designed to generate a text summary from Honeyd logs.
The summaries may be produced using different parameters as filters, such as ports, protocols, IP addresses or
networks. It shows the top source and port access and the number of connections per hour, and supports input
from multiple log files. The script can also correlate events from several honeypots. The output of this script
contains the information that provides several different summaries of all the traffic captured by the whole
Honeyd environment. The command to generate a report from the honeydsum is:
./honeydsum.pl –c honeydsum.conf /root/Desktop/honeyd/log/test>report.
It takes the packet logged by honeyd as input and generates the report.This report tells the total number
of connections on the honeypot and the IP addresses of the sources which attacked on the virtual honeypots.
V. RESULTS
It is not easy and intuitive for everyone to query MySQL database in order to find some information
about the honeypot’s runs so to facilitate easy view and searching of data in the MySQL database.
Honeydsum is a tool written in Perl designed to generate a summary from honeyd logs. The summaries
may be produced using different parameters as filters, such as ports, protocols, IP addresses or networks. This
tool is basically used for processing of honeyd log files to get the reports. You can say it is being used for report
generation by processing honeyd log files.
Further, the results produced by the two honepots are analyzed graphically.
Fig 5. Total no of packets received (results generated from honeyd logs by honeydsum.pl)
6. Design & Implementation of Honeyd to simulate Virtual Honeypots
www.iosrjournals.org 33 | Page
Fig 6 Total No. Of Connections established per hour (created from honeydsum.pl)
After performing the signature command using MYSQL as in fig 4, maximum alerts are ICMP attacks.
This proves that out of top 10 source hosts, first attacker performs ICMP attack. This proves the result.
Fig7 Resources at Virtual Honeypot2 by different IPs
Fig8 Top 10 source hosts
VI. CONCLUSIONS
As per the research done so far and literature study, Honeypots are a current research field in the sector
of network security. Currently there is a lot of ongoing research and discussions all around the world. Honeypots
are resources which give full freedom to attackers and every activities of the attacker will get logged. Honeypots
gives us the platform to gather the intelligent information about the attackers so that we can later study them and
can take the remedial actions to tighten the network security. Honeypots are being classified into different
categories such low interaction honeypots, high interaction honeypots etc. Low interaction honeypots provide
the emulated environment to the attackers which is not a real environment therefore the volume of attacks may
be less in case of low interaction honeypots whereas in case of high interaction honeypots which provide the
real environment to the attackers to get logged. A honeypot is a valuable resource, especially to collect
information about proceedings of attackers as well as their deployed tools. No other mechanism is comparable
in the efficiency of a honeypot if gathering information is a primary goal, especially if the tools an attacker uses
are of interest. But nevertheless, honeypots cannot be considered as a standard product with a fixed place in
every security aware environment as firewalls or intrusion detection systems are today. The involved risk and
need for tight supervision as well as time intensive analysis makes them difficult to use. Honeypots are in one’s
infancy and new ideas and technologies will surface in the next time. At the same time as honeypots are getting
more advanced, hackers will also develop methods to detect such systems. A regular arms race could start
between the good guys and the blackhat community.
7. Design & Implementation of Honeyd to simulate Virtual Honeypots
www.iosrjournals.org 34 | Page
REFERENCES
[1] “What Is the Difference: Viruses, Worms, and Trojans?”, http://www.cisco.com/web/about/security/intelligence/virus-worm-
diffs.html..
[2] Provos, N., “A Virtual Honeypot Framework”, SSYM’04 Proceedings of the 13th
conference on USENIX Security Symposium,
Volume 13, 2004.
[3] Lance Spitzner, Tracking Hackers. Addison Wesley, September 2002.
[4] Zanoramy, W. and Zakaria, A., “Deploying Virtual Honeypots on Virtual Machine Monitor” IEEE Proceedings, vol. 4 , pp.1-5, 26
Aug 2008.
[5] Spitzner, L., “Honeypot: Definitions and Values”, May 2002 http://www.spitzner.net.
[6] Levin, J. and Labella, R., “The Use of Honeynets to Detect Exploited Systems across Large Enterprise Networks”, IEEE
Proceedings, pp.92-99, 18 June 2003.
[7] Qassrawi, M. and Hongli, Z. “Deception methodology in virtual Honeypots”, Second International Conference on Network Security,
Wireless Communication and Trusted Computing, 2010.
[8] Bao, J. and Gao, M. “Research on network security of defense based on Honeypot”, International Conference on Computer
Applications and System Modeling, 2010.
[9] Levine, J. and Grizzard, J. “Using honeynets to protect large enterprise networks,” Security & Privacy Magazine, IEEE, vol. 2, pp.
73-75, 2004.
[10] Ryan Talabis,” Honeypots 101: What’s in it for me?”http://www.philippinehoneynet.org/, Fetched 21/06/2011.
[11] Tang, X. "The Generation of Attack Signatures Based on Virtual Honeypots”, International Conference on Parallel and Distributed
Computing, Applications and Technologies, 2010, pp.435-439.
[12] V.Maheswari, Dr. P. E. Sankaranarayanan, “Honeypots: Deployment and Data Forensic Analysis”, International Conference on
Computational Intelligence and Multimedia Applications 2007, 0-7695-3050-8/07, 2007 IEEE.
[13] Chao-Hsi Yeh and Chung-Huang Yang, “Design and Implementation of Honeypot Systems Based on Open-Source Software”, 1-
4244-2415-3/08/. 2008 IEEE.
[14] Zhang Li-juan, “Honeypot-based Defense System Research and Design”, 978-1-4244-4520-2/09/, 2009 IEEE.
[15] Xinyu Tang, “The Generation of Attack Signatures Based on Virtual Honeypots”, The 11th International Conference on Parallel
and Distributed Computing, Applications and Technologies, 978-0-7695-4287-4/10, 2010 IEEE.
[16] Abhay Nath Singh, R.C.Joshi, “A Honeypot System for Efficient Capture and Analysis of Network Attack Traffic”, International
Conference on Signal Processing, Communication, Computing and Networking Technologies, 978-1-61284-653-8/11, IEEE.
[17] Abdallah Ghourabi, Tarek Abbes, Adel Bouhoula, “Design and Implementation of Web Service Honeypot”, 1078-0-8495-4287-
4/11, 2011 IEEE.
[18] Meixing Le, Angelos Stavrou, Brent ByungHoon Kang, “DoubleGuard: Detecting Intrusions in Multitier Web Applications”, IEEE
TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, VOL. 9, NO. 4, JULY/AUGUST 2012, 1545-5971/12/,
IEEE.
[19] Liu Dongxia & Zhang Yongbo, “An Intrusion Detection System Based on Honeypot Technology”, 2012 International Conference
on Computer Science and Electronics Engineering, 978-0-7695-4647-6/12, 2012 IEEE
[20] “Snort”, http://www.snort.org/assets/166/snort_manual.pdf.
[21] John E. Canavan,” Fundamentals of Network Security” , http://www.artechhouse.com .
[22] Provos, N. “A Virtual Honeypot Framework”, SSYM’04 Proceedings of the 13th
conference on USENIX Security Symposium,
Vol. 13, 2004.
[23] Lance Spitzner, “Definitions and Value of Honeypots”, http://www.trackinghackers.com/papers/honeypots.html.
[24] Peter, E. et al., “A Practical Guide to Honeypots”, http://www.cse.wustl.edu/˜jain/cse571-09/ftp/honey/index.html, Fetched
20/06/2011.
[25] Spitzner, L.“ Know Your Enemy: Honeynets”, http://www.honeynet.org/papers/honeynet.