The document provides an overview of cyber security and vulnerability scanning. It discusses the history of cyber security including early computer worms like Creeper and Reaper. The CIA triad of confidentiality, integrity and availability is introduced as a model for security policies. Types of attacks and how cyber security is implemented are covered. Vulnerability scanners are defined as tools that assess vulnerabilities across systems and networks. Their benefits, limitations, architecture and types including network-based and host-based are outlined.
This document discusses various web application security topics including SQL injection, cross-site request forgery (CSRF), cross-site scripting (XSS), session tokens, and cookies. It provides examples of each type of attack, how they work, their impact, and strategies for prevention. Specific topics covered include SQL injection examples using single quotes, comments, and dropping tables; CSRF examples using bank transfers and router configuration; and XSS examples using persistent, reflected, and DOM-based techniques.
Report: Study and Implementation of Advance Intrusion Detection and Preventio...Deepak Mishra
This document discusses building an intrusion detection system that combines network-based and log-based detection. It proposes using the Security Onion distribution and its included tools like Snort, Sguil, Squert and OSSEC. It describes configuring Security Onion sensors to monitor network traffic and logs, storing alerts in databases, and using the management consoles to analyze alerts. The goal is to create a comprehensive security monitoring platform through centralized log management and correlation of network and host-based events.
Detecting and Preventing Attacks Using Network Intrusion Detection SystemsCSCJournals
Intrusion detection is an important technology in business sector as well as an active area of research. It is an important tool for information security. A Network Intrusion Detection System is used to monitor networks for attacks or intrusions and report these intrusions to the administrator in order to take evasive action. Today computers are part of networked; distributed systems that may span multiple buildings sometimes located thousands of miles apart. The network of such a system is a pathway for communication between the computers in the distributed system. The network is also a pathway for intrusion. This system is designed to detect and combat some common attacks on network systems. It follows the signature based IDs methodology for ascertaining attacks. A signature based IDS will monitor packets on the network and compare them against a database of signatures or attributes from known malicious threats. It has been implemented in VC++. In this system the attack log displays the list of attacks to the administrator for evasive action. This system works as an alert device in the event of attacks directed towards an entire network.
This document discusses intrusion detection systems (IDS). It defines intrusion, intrusion detection, and intrusion prevention. It explains the components of an IDS including audit data, detection models, and detection and decision engines. It describes misuse detection using signatures and anomaly detection using statistical analysis. It also discusses host-based and network-based IDS, their advantages and disadvantages, and limitations of exploit-based signatures. The document emphasizes the importance of selecting and properly deploying the right IDS for an organization's needs.
The document provides a review of recent intrusion detection systems for wireless sensor networks. It begins with an introduction to wireless sensor networks and different types of intrusions. It then analyzes 14 recent intrusion detection systems, listing their advantages and disadvantages. Finally, it concludes that future work is needed to develop systems that can accurately detect intrusions in an energy-efficient manner.
The document provides an overview of cyber security and vulnerability scanning. It discusses the history of cyber security including early computer worms like Creeper and Reaper. The CIA triad of confidentiality, integrity and availability is introduced as a model for security policies. Types of attacks and how cyber security is implemented are covered. Vulnerability scanners are defined as tools that assess vulnerabilities across systems and networks. Their benefits, limitations, architecture and types including network-based and host-based are outlined.
This document discusses various web application security topics including SQL injection, cross-site request forgery (CSRF), cross-site scripting (XSS), session tokens, and cookies. It provides examples of each type of attack, how they work, their impact, and strategies for prevention. Specific topics covered include SQL injection examples using single quotes, comments, and dropping tables; CSRF examples using bank transfers and router configuration; and XSS examples using persistent, reflected, and DOM-based techniques.
Report: Study and Implementation of Advance Intrusion Detection and Preventio...Deepak Mishra
This document discusses building an intrusion detection system that combines network-based and log-based detection. It proposes using the Security Onion distribution and its included tools like Snort, Sguil, Squert and OSSEC. It describes configuring Security Onion sensors to monitor network traffic and logs, storing alerts in databases, and using the management consoles to analyze alerts. The goal is to create a comprehensive security monitoring platform through centralized log management and correlation of network and host-based events.
Detecting and Preventing Attacks Using Network Intrusion Detection SystemsCSCJournals
Intrusion detection is an important technology in business sector as well as an active area of research. It is an important tool for information security. A Network Intrusion Detection System is used to monitor networks for attacks or intrusions and report these intrusions to the administrator in order to take evasive action. Today computers are part of networked; distributed systems that may span multiple buildings sometimes located thousands of miles apart. The network of such a system is a pathway for communication between the computers in the distributed system. The network is also a pathway for intrusion. This system is designed to detect and combat some common attacks on network systems. It follows the signature based IDs methodology for ascertaining attacks. A signature based IDS will monitor packets on the network and compare them against a database of signatures or attributes from known malicious threats. It has been implemented in VC++. In this system the attack log displays the list of attacks to the administrator for evasive action. This system works as an alert device in the event of attacks directed towards an entire network.
This document discusses intrusion detection systems (IDS). It defines intrusion, intrusion detection, and intrusion prevention. It explains the components of an IDS including audit data, detection models, and detection and decision engines. It describes misuse detection using signatures and anomaly detection using statistical analysis. It also discusses host-based and network-based IDS, their advantages and disadvantages, and limitations of exploit-based signatures. The document emphasizes the importance of selecting and properly deploying the right IDS for an organization's needs.
The document provides a review of recent intrusion detection systems for wireless sensor networks. It begins with an introduction to wireless sensor networks and different types of intrusions. It then analyzes 14 recent intrusion detection systems, listing their advantages and disadvantages. Finally, it concludes that future work is needed to develop systems that can accurately detect intrusions in an energy-efficient manner.
Intrusion detection systems monitor computer networks and systems for unauthorized access or activity. There are two main types: network-based systems examine network traffic for attacks, while host-based systems check the integrity of individual systems. Methods include knowledge-based systems that detect known attacks and behavior-based systems that identify deviations from normal usage profiles. Regular auditing of systems, logs, user rights and files is needed to detect intrusions. While intrusion detection is important for security, intrusion prevention systems that can block attacks in real-time are increasingly replacing detection-only systems.
This document summarizes an article that proposes integrating conditional random fields (CRFs) and a layered approach to improve intrusion detection systems. CRFs can effectively model relationships between different features to increase attack detection accuracy. A layered approach reduces computation time by eliminating communication overhead between layers and using a small set of features in each layer. The proposed system aims to achieve both high attack detection accuracy using CRFs and high efficiency using the layered approach. It presents integrating these two methods for intrusion detection to address issues with limited coverage, high false alarms, and inefficiency in existing systems.
This document discusses various types of cyber attacks and threats such as viruses, worms, Trojan horses, botnets, trap doors, logic bombs, denial of service attacks, and spyware. It provides details on the characteristics and techniques of different attacks, including how viruses, worms, and Trojan horses infect systems. Distributed denial of service (DDoS) attacks are explained along with specific DDoS techniques like SYN floods and Smurf attacks. The document is a lecture on cryptography and network security that outlines different cyber threats.
This document discusses network intrusion detection systems (NIDS) and their ability to handle high-speed traffic. It introduces NIDS and their role in monitoring network traffic. The document presents an experiment that tests the open-source NIDS Snort under high-volume traffic. The experiment shows that Snort drops more packets as traffic speed and volume increases, demonstrating a weakness of NIDS in high-speed environments. It suggests using a parallel NIDS technique to help NIDS better handle high-speed network traffic and reduce packet dropping.
This document summarizes a proposed network attack alerting system that aims to reduce redundant alerts from intrusion detection systems (IDS). The system uses both network-based and host-based IDS to detect attacks launched using the Backtrack penetration testing tool on a virtual network environment. Well-known open source IDS tools from the Security Onion distribution are used to generate alerts. The system builds a database of alerts and defines rules to eliminate duplicate alerts for the same attack based on attributes like source/destination IP and port. It also establishes a severity classification scheme using threshold values of alerts and time to help administrators prioritize responses.
This document discusses implementing an Intrusion Detection System (IDS) for WiFi security. The IDS would detect vulnerable activities of devices connected to the network and alert the system.
The paper provides background on common WiFi security vulnerabilities and attacks. It then describes the components and methodology of an IDS, including using sensors to monitor network traffic, analyzers to evaluate the traffic for attacks, and user interfaces to manage the system. The proposed IDS would collect network information using Wireshark, detect intrusions, and respond to threats to improve security for wireless networks.
This document outlines topics to be discussed in a lecture on cryptography and network security. It includes two case studies of data breaches at government organizations and a hotel chain. It discusses security needs and objectives, why security is difficult to achieve, how security became an issue, threat modeling, risk assessment, the three aspects of security (attacks, mechanisms, services), and key points to remember around security including the trade-off between security and usability.
Intrusion Detection Systems (IDS) monitor network traffic and system activities for malicious activities or policy violations. IDS can be classified as anomaly-based, signature-based, host-based or network-based. Anomaly-based IDS detect novel attacks but generate many false alarms, while signature-based IDS detect known attacks but miss novel ones. Future IDS aim to integrate network and host-based detection and detect novel attacks rather than just specific signatures. IDS help secure networks from intrusions but also have drawbacks like false alarms, inability to detect new threats, and complexity.
A Collaborative Intrusion Detection System for Cloud Computingijsrd.com
Cloud computing is a computing paradigm that shifts drastically from traditional computing architecture. Although this new computing paradigm brings many advantages like utility computing model but the design in not flawless and hence suffers from not only many known computer vulnerabilities but also introduces unique information confidentiality, integrity and availability risks as well due its inherent design paradigm. To provide secure and reliable services in cloud computing environment is an important issue. To counter a variety of attacks, especially large-scale coordinated attacks, a framework of Collaborative Intrusion Detection System (IDS) is proposed. The proposed system could reduce the impact of these kinds of attacks through providing timely notifications about new intrusions to Cloud users' systems. To provide such ability, IDSs in the cloud computing regions both correlate alerts from multiple elementary detectors and exchange knowledge of interconnected Clouds with each other.
This document discusses intrusion detection systems (IDS), beginning with historical examples of cyber attacks. It describes the role of firewalls in network security and how IDS serve as a complementary technique to firewalls by monitoring network traffic and detecting intrusions. The document outlines different types of IDS, including host-based, network-based, and hybrid systems. It also covers common intrusion detection techniques and the limitations of IDS in providing comprehensive security.
IDS - Intrusion Detection System presentation designed for HNDIT semester 3 OS and Security assignment.
This describe Host,Network,Anomaly,Active,Passive Intrusion Detection Systems
Seminar Presentation | Network Intrusion Detection using Supervised Machine L...Jowin John Chemban
By:
Jowin John Chemban (jowinchemban@gmail.com)
HGW16CS022 (2016-2020 Batch)
S7 B.Tech Computer Science Engineering
Holy Grace Academy of Engineering, Mala
Date : September 2019
Network-based intrusion detection systems (NBIDS) monitor network traffic to detect security threats. They were developed in response to growing network attacks and as a complement to traditional defenses like firewalls and antivirus software. While NBIDS cannot prevent all attacks, they can trace activity, detect anomalies, and aid auditing and response. Common NBIDS implement pattern matching and work best combined with other techniques like anomaly detection.
The document discusses different types of intruders and intrusion detection systems. It describes three classes of intruders: masqueraders, misfeasors, and clandestine users. It then defines intrusion detection systems, intrusion prevention systems, and intrusion detection and prevention systems. The document outlines different types of attacks and intrusion detection mechanisms, including misuse detection, anomaly detection, and hybrid detection. It also discusses network-based and host-based intrusion detection systems. Honeypots are described as systems designed to deceive attackers in order to learn about their tools and methods.
This document summarizes intrusion detection systems (IDS), including that an IDS monitors network traffic to detect unwanted activity like illegal access. IDS can be classified based on anomaly detection, signature-based detection, host-based monitoring of operating systems, or network-based analysis of packet traffic. The document also discusses benefits of IDS like reduced costs and real-time detection, and notes the future includes better integrating network and host-based IDS to detect novel attacks.
CyberCrime in the Cloud and How to defend Yourself Alert Logic
The document discusses cybercrime threats in the cloud and how to defend against them. It notes that traditional on-premises threats are moving to the cloud, with web application attacks and brute force attacks being most common. Honeypots are used to gather intelligence on attacks by simulating vulnerable systems. Analysis of honeypot data found increases in brute force attacks and vulnerability scans in cloud environments. The document recommends best practices like secure coding, access management, patch management, log review, and tools like firewalls and intrusion detection to help secure cloud environments.
1. Vulnerability assessment and penetration testing (VAPT) involves identifying security vulnerabilities in an organization's network and systems through scanning and manual exploitation techniques.
2. The process includes information gathering, scanning to detect vulnerabilities, analysis of vulnerabilities found, and penetration testing to manually exploit vulnerabilities.
3. The final report documents the findings by risk level, technical details of vulnerabilities discovered, and recommendations for remediation.
Intrusion detection systems monitor computer networks and systems for unauthorized access or activity. There are two main types: network-based systems examine network traffic for attacks, while host-based systems check the integrity of individual systems. Methods include knowledge-based systems that detect known attacks and behavior-based systems that identify deviations from normal usage profiles. Regular auditing of systems, logs, user rights and files is needed to detect intrusions. While intrusion detection is important for security, intrusion prevention systems that can block attacks in real-time are increasingly replacing detection-only systems.
This document summarizes an article that proposes integrating conditional random fields (CRFs) and a layered approach to improve intrusion detection systems. CRFs can effectively model relationships between different features to increase attack detection accuracy. A layered approach reduces computation time by eliminating communication overhead between layers and using a small set of features in each layer. The proposed system aims to achieve both high attack detection accuracy using CRFs and high efficiency using the layered approach. It presents integrating these two methods for intrusion detection to address issues with limited coverage, high false alarms, and inefficiency in existing systems.
This document discusses various types of cyber attacks and threats such as viruses, worms, Trojan horses, botnets, trap doors, logic bombs, denial of service attacks, and spyware. It provides details on the characteristics and techniques of different attacks, including how viruses, worms, and Trojan horses infect systems. Distributed denial of service (DDoS) attacks are explained along with specific DDoS techniques like SYN floods and Smurf attacks. The document is a lecture on cryptography and network security that outlines different cyber threats.
This document discusses network intrusion detection systems (NIDS) and their ability to handle high-speed traffic. It introduces NIDS and their role in monitoring network traffic. The document presents an experiment that tests the open-source NIDS Snort under high-volume traffic. The experiment shows that Snort drops more packets as traffic speed and volume increases, demonstrating a weakness of NIDS in high-speed environments. It suggests using a parallel NIDS technique to help NIDS better handle high-speed network traffic and reduce packet dropping.
This document summarizes a proposed network attack alerting system that aims to reduce redundant alerts from intrusion detection systems (IDS). The system uses both network-based and host-based IDS to detect attacks launched using the Backtrack penetration testing tool on a virtual network environment. Well-known open source IDS tools from the Security Onion distribution are used to generate alerts. The system builds a database of alerts and defines rules to eliminate duplicate alerts for the same attack based on attributes like source/destination IP and port. It also establishes a severity classification scheme using threshold values of alerts and time to help administrators prioritize responses.
This document discusses implementing an Intrusion Detection System (IDS) for WiFi security. The IDS would detect vulnerable activities of devices connected to the network and alert the system.
The paper provides background on common WiFi security vulnerabilities and attacks. It then describes the components and methodology of an IDS, including using sensors to monitor network traffic, analyzers to evaluate the traffic for attacks, and user interfaces to manage the system. The proposed IDS would collect network information using Wireshark, detect intrusions, and respond to threats to improve security for wireless networks.
This document outlines topics to be discussed in a lecture on cryptography and network security. It includes two case studies of data breaches at government organizations and a hotel chain. It discusses security needs and objectives, why security is difficult to achieve, how security became an issue, threat modeling, risk assessment, the three aspects of security (attacks, mechanisms, services), and key points to remember around security including the trade-off between security and usability.
Intrusion Detection Systems (IDS) monitor network traffic and system activities for malicious activities or policy violations. IDS can be classified as anomaly-based, signature-based, host-based or network-based. Anomaly-based IDS detect novel attacks but generate many false alarms, while signature-based IDS detect known attacks but miss novel ones. Future IDS aim to integrate network and host-based detection and detect novel attacks rather than just specific signatures. IDS help secure networks from intrusions but also have drawbacks like false alarms, inability to detect new threats, and complexity.
A Collaborative Intrusion Detection System for Cloud Computingijsrd.com
Cloud computing is a computing paradigm that shifts drastically from traditional computing architecture. Although this new computing paradigm brings many advantages like utility computing model but the design in not flawless and hence suffers from not only many known computer vulnerabilities but also introduces unique information confidentiality, integrity and availability risks as well due its inherent design paradigm. To provide secure and reliable services in cloud computing environment is an important issue. To counter a variety of attacks, especially large-scale coordinated attacks, a framework of Collaborative Intrusion Detection System (IDS) is proposed. The proposed system could reduce the impact of these kinds of attacks through providing timely notifications about new intrusions to Cloud users' systems. To provide such ability, IDSs in the cloud computing regions both correlate alerts from multiple elementary detectors and exchange knowledge of interconnected Clouds with each other.
This document discusses intrusion detection systems (IDS), beginning with historical examples of cyber attacks. It describes the role of firewalls in network security and how IDS serve as a complementary technique to firewalls by monitoring network traffic and detecting intrusions. The document outlines different types of IDS, including host-based, network-based, and hybrid systems. It also covers common intrusion detection techniques and the limitations of IDS in providing comprehensive security.
IDS - Intrusion Detection System presentation designed for HNDIT semester 3 OS and Security assignment.
This describe Host,Network,Anomaly,Active,Passive Intrusion Detection Systems
Seminar Presentation | Network Intrusion Detection using Supervised Machine L...Jowin John Chemban
By:
Jowin John Chemban (jowinchemban@gmail.com)
HGW16CS022 (2016-2020 Batch)
S7 B.Tech Computer Science Engineering
Holy Grace Academy of Engineering, Mala
Date : September 2019
Network-based intrusion detection systems (NBIDS) monitor network traffic to detect security threats. They were developed in response to growing network attacks and as a complement to traditional defenses like firewalls and antivirus software. While NBIDS cannot prevent all attacks, they can trace activity, detect anomalies, and aid auditing and response. Common NBIDS implement pattern matching and work best combined with other techniques like anomaly detection.
The document discusses different types of intruders and intrusion detection systems. It describes three classes of intruders: masqueraders, misfeasors, and clandestine users. It then defines intrusion detection systems, intrusion prevention systems, and intrusion detection and prevention systems. The document outlines different types of attacks and intrusion detection mechanisms, including misuse detection, anomaly detection, and hybrid detection. It also discusses network-based and host-based intrusion detection systems. Honeypots are described as systems designed to deceive attackers in order to learn about their tools and methods.
This document summarizes intrusion detection systems (IDS), including that an IDS monitors network traffic to detect unwanted activity like illegal access. IDS can be classified based on anomaly detection, signature-based detection, host-based monitoring of operating systems, or network-based analysis of packet traffic. The document also discusses benefits of IDS like reduced costs and real-time detection, and notes the future includes better integrating network and host-based IDS to detect novel attacks.
CyberCrime in the Cloud and How to defend Yourself Alert Logic
The document discusses cybercrime threats in the cloud and how to defend against them. It notes that traditional on-premises threats are moving to the cloud, with web application attacks and brute force attacks being most common. Honeypots are used to gather intelligence on attacks by simulating vulnerable systems. Analysis of honeypot data found increases in brute force attacks and vulnerability scans in cloud environments. The document recommends best practices like secure coding, access management, patch management, log review, and tools like firewalls and intrusion detection to help secure cloud environments.
1. Vulnerability assessment and penetration testing (VAPT) involves identifying security vulnerabilities in an organization's network and systems through scanning and manual exploitation techniques.
2. The process includes information gathering, scanning to detect vulnerabilities, analysis of vulnerabilities found, and penetration testing to manually exploit vulnerabilities.
3. The final report documents the findings by risk level, technical details of vulnerabilities discovered, and recommendations for remediation.
Securing E-commerce networks in MIS and E-Commercehidivin652
An intrusion detection system (IDS) monitors network traffic to detect threats and sends alerts. An intrusion prevention system (IPS) also detects threats but can actively block or drop malicious traffic. Firewalls analyze network packet metadata to allow or block traffic based on rules. They create barriers between networks while IDS monitors and IPS detects and prevents threats. VPNs encrypt data to securely transmit over public networks and hide users' online activity and location. Together these tools enhance e-commerce security.
Tools and Mechanisms for Network Security in an Organization.
Physical Security, Administrative Security and Technical Security measures have been described.
Security Testing Tools are Nessus, THC Hydra, Kismet, Nikto, WireShark and NMAP.
Computer networks connect devices through communication systems. Network security aims to protect information and allow authorized access. It involves authentication of users, monitoring network traffic for intrusions, and other strategies. Intrusion detection systems monitor for suspicious activity and notify administrators. There are different types of intrusion detection including network-based and host-based systems. Penetration testing evaluates security by simulating attacks. Cryptography also helps secure networks through techniques like public key encryption, hashing, and key exchange algorithms.
This document discusses advanced persistent threats (APTs) and strategies for cyber defense. It describes APTs as advanced, persistent, and threatening adversaries that are formally tasked to accomplish missions. The document outlines the lifecycle of APT attacks, including establishing backdoors in networks, maintaining long-term control, and exfiltrating data using encryption. It provides examples of APT groups and tools they use, such as exploiting vulnerabilities to escalate privileges and dump cached credentials from Windows networks. The overall summary is that APTs are dangerous, organized adversaries requiring persistent cyber defense strategies.
Trisis in Perspective: Implications for ICS DefendersDragos, Inc.
Discovery of TRISIS/TRITON was a landmark event in the Industrial Control Systems (ICS) security community. It is the fifth known ICS-specific malware (following Stuxnet, Havex, BlackEnergy2, and CRASHOVERRIDE), and the first such malware to specifically target safety instrumented systems. Since identification and public disclosure in early December 2017, much has been written on TRISIS, its operation, and mitigations; however, such mitigations are usually too specific to TRISIS and fall short in assisting defenders with safety systems other than a Schneider Electric Triconex. In May, Dragos discovered that XENOTIME, the activity group behind TRISIS, had expanded its targeting to North America and other safety systems. Given this new data, a generalized approach to safety system defense is critical knowledge for ICS security personnel. This discussion aims to provide such an approach to guarding safety systems. We will provide an overview of the TRISIS malware, including its installation, execution and modification to the controller. Next, we will break down the TRISIS event's specific tactics, techniques and procedures (TTPs) and generalize them across the ICS kill chain. Using this model, we provide present-day actionable defense strategies for asset owners, as well as guidance for forensics, restoration, and recovery should an attack be discovered. We also look to the future and recommend ways in which the state of the art can be improved by vendors and ICS owners to empower defenders with the information they need to stop future attacks.
Learn more here: https://www.dragos.com/blog/trisis/
Cybersecurity involves protecting information systems and networks from attacks, accidents, and failures. It aims to protect corporate and national operations and assets. Some key aspects of cybersecurity include user accounts, configuration management, contingency plans, mobile device security, and incident response. Common cyber threats include viruses, hackers, identity theft, and spyware/adware. Basic cybersecurity actions people can take include installing updates, running antivirus software, using firewalls, avoiding spyware, backing up files, and protecting passwords. Education about cybersecurity risks and proper security practices is important for users at home and work.
The document discusses the basics of IT security including the CIA triad of confidentiality, integrity and availability. It also covers common security concepts such as assets, vulnerabilities, threats, countermeasures and risks. Additionally, it summarizes authentication, authorization and accounting (AAA) protocols, common attacks and how to implement secure network architecture.
Security Holes and Vulnerabilities in Corporate Network_Pre Null Meet Kolkataamiyadutta
This document summarizes security holes and vulnerabilities in corporate networks. It identifies two critical properties of systems: integrity and availability. It discusses how reducing the attack surface and protecting user computers are important for protecting corporate networks. The document then outlines several possible attack vectors that do not require administrator rights, including local attacks that get full access to user processes and domain attacks that allow access to network resources. Finally, it describes the typical stages an attack may progress through - gaining a foothold, analyzing the environment, and propagating malware - and identifies some common network vulnerabilities.
This document discusses network architecture and reliability. It describes the basic characteristics of fault tolerance, scalability, quality of service, and security that network architectures need to address. It then discusses fault tolerance in networks through packet switching and redundancy. Scalability in networks is achieved through following standards and protocols. Quality of service is important for real-time media like voice and video. The document also covers network security threats and the goals of confidentiality, integrity, and availability.
1. Cloud computing provides flexibility and economies of scale but introduces new security risks as sensitive data and infrastructure are placed outside traditional secure perimeters.
2. Traditional security measures like firewalls and intrusion detection become more difficult in cloud environments where virtual machines are dynamically allocated across shared physical servers.
3. Ensuring data integrity, updating security software, complying with regulations, and monitoring administrator access require new solutions to prove security and respond to vulnerabilities in cloud infrastructure and virtual environments.
IoT Device Security
The document discusses IoT device security. It defines IoT devices as electronic devices connected to the internet, with sensors, controllers, and ability to connect to the internet. Examples include smart home devices. There are growing security risks as the number of IoT devices surpasses the human population and more personal/industrial devices connect. Common vulnerabilities include weak passwords, unsecured network services/interfaces, lack of updates, and privacy/data issues. The document outlines defensive measures and analyzes the 2016 Dyn botnet DDoS attack, where the Mirai malware infected insecure IoT devices to launch large-scale attacks.
The document discusses various automated security assessment tools, including OpenVAS and Nessus, that can be used to test systems for vulnerabilities. It also covers intrusion detection systems (IDS), describing host-based IDS that monitor system events and network-based IDS that monitor network traffic. Honeypots are discussed as trap systems that gather attacker information. Firewalls and their use of policies, blacklists and whitelists to filter network traffic are also summarized.
The CBC machine is a common diagnostic tool used by doctors to measure a patient's red blood cell count, white blood cell count and platelet count. The machine uses a small sample of the patient's blood, which is then placed into special tubes and analyzed. The results of the analysis are then displayed on a screen for the doctor to review. The CBC machine is an important tool for diagnosing various conditions, such as anemia, infection and leukemia. It can also help to monitor a patient's response to treatment.
Discover the latest insights on Data Driven Maintenance with our comprehensive webinar presentation. Learn about traditional maintenance challenges, the right approach to utilizing data, and the benefits of adopting a Data Driven Maintenance strategy. Explore real-world examples, industry best practices, and innovative solutions like FMECA and the D3M model. This presentation, led by expert Jules Oudmans, is essential for asset owners looking to optimize their maintenance processes and leverage digital technologies for improved efficiency and performance. Download now to stay ahead in the evolving maintenance landscape.
artificial intelligence and data science contents.pptxGauravCar
What is artificial intelligence? Artificial intelligence is the ability of a computer or computer-controlled robot to perform tasks that are commonly associated with the intellectual processes characteristic of humans, such as the ability to reason.
› ...
Artificial intelligence (AI) | Definitio
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
3. Introduction
• Hacking incidents are increasing day by day. Security
has become a major concern in such a technological
environment. Companies are investing lots of money on
the safety and confidentiality of data.
• The existing signature based techniques [1][2][3] store
the attack signatures. It requires the huge maintenance
of signature database.
• Other security approaches (signature-
based/static/dynamic) [4][5] in traditional environment
can be directly installed into the monitored machine.
4. • The main drawback with traditional security
tools is that if the system gets compromised,
these security processes also get compromised.
• Ex. Torpig and Config malware can disable the
security tool like Sophos.
• Hence, traditional security tools are not
efficient in the virtualization environment.
• Semantic Gap Issue
• They do not support advanced features such as
Virtual Machine Introspection (VMI) [6].
5. Motivation
With increasing hacking incidents, people and organizations
lose lots and lots of money as well as confidential data. So
we decided to come up with an approach which deals with
them.
The Biggest Cybersecurity Disaster of 2017 so far [7]:
• Shadow Brokers- The mysterious hacking group known
as the Shadow Brokers first surfaced in August 2016,
claiming to have breached the spy tools of the elite NSA-
linked operation known as the Equation Group.
• WannaCry- On May 12 a strain of ransomware called
WannaCry spread around the world, walloping hundreds of
thousands of targets, including public utilities and large
corporations.
6. Objective
• The aim of this project is, “to design and
analyze a malware detection approach
(particularly dynamic analysis) to detect
attacks outside the Virtual Machine (VM) by
making use of Virtual Machine Introspection
(VMI) ”.
7. • Petya/NotPetya/Nyetya/Goldeneye- A month or
so after WannaCry, another wave of ransomware
infections that partially leveraged Shadow
Brokers Windows exploits hit targets worldwide.
• Cloudbleed- In February, the internet
infrastructure company Cloudflare announced
that a bug in its platform caused random leakage
of potentially sensitive customer data.
• Wikileaks CIA Vault 7- On March 7,
WikiLeaks published a data trove containing
8,761 documents allegedly stolen from the CIA
that contained extensive documentation of
alleged spying operations and hacking tools.
8. IDS – Intrusion Detection System [8]
• a device or software application
• monitors a network or systems for malicious
activity or policy violations
• detected activity reported to admin or collected
centrally using a security information and event
management (SIEM) system.
• A SIEM system combines outputs from multiple
sources, and uses alarm filtering techniques to
distinguish malicious activity from false alarms.
10. IDS Techniques [9]
• Signature-Based malware detection: Signature-based detection
works by scanning the contents of computer files and cross-
referencing their contents with the “code signatures” belonging to
known viruses.
• Specification-based malware detection: Specification based
detection makes use of certain rule set of what is considered as
normal in order to decide the maliciousness of the program
violating the predefined rule set.
• Behavioral based Detection: The behaviour-based malware
detection system is composed of several applications, which
together provide the resources and mechanisms needed to detect
malware on the Android platform.
11. VMI Techniques[10]
In-VM
• avoids the semantic gap problem
• in-VM agent monitors the guest OS from the
inside
• exposes guest OS activities to the hypervisor
• Hypervisor role is to enable enforcement of the
desired security policies
Eg. Lares, SIM framework
12. Out-of-VM delivered
• mainly covers early and passive VMI techniques
• bridges the semantic gap using delivered semantic
information
• knowledge about guest OS internals and
location/definition of OS data structures of
interest is:
i. incorporated explicitly in the VMI system
ii. extracted from OS source code
iii. obtained through kernel symbols if available.
eg. Livewire, VMwatcher, XenAccess, Virtuoso
13. Out-of-VM derived
• Hardware architectures provide functionalities
such as multi-tasking, user privileges, memory
management and protection, system virtualization
• makes use of these functionalities to inspect guest
OS activities
• observes and interprets hardware states and events
• OS-agnostic, resistant to kernel data attacks and
to malware evasion
• We classify these VMI techniques into two
subcategories:
i. Trap handling-based- eg. Antifarm, Lycosid
ii. Trap forcing-based- eg. Ether, Nitro, Hypertap
14. Hybrid techniques
• uses combination of in-VM, delivered and
derived techniques
• achieves more robustness and reliability
• Extends range of possible VMI applications
• Four types-
i. Trap forcing-based- eg. Secvisor
ii. Data redirection- eg. NICKLE, VMST
iii. Process transplanting- eg. Process out-grafting
iv. Function call injection- eg. Syringe, Hypershell
15. Types of hypervisors[11]
There are two types of hypervisors:
Type 1:
• run directly on the system hardware.
• referred to as a "native" or "bare metal" or "embedded"
• building the hypervisor into the firmware is proving to be
more efficient
• provide higher performance, availability, and security
Type 2:
• run on a host OS
• During virtualization they were most popular.
• Admins could buy the software and install it on a server they
already had
• used mainly on client systems where efficiency is less
critical.
17. VMI Tools[12]
Lares [13] An Architecture for Secure Active Monitoring
Using Virtualization
• Host-based security tools such as anti-virus and intrusion
detection systems are not adequately protected on today's
computers.
• Malware is often designed to immediately disable any security
tools upon installation, rendering them useless.
• While current research has focused on moving these
vulnerable security tools into an isolated virtual machine, this
approach cripples security tools by preventing them from
doing active monitoring.
• This tool describes an architecture that takes a hybrid
approach, giving security tools the ability to do active
monitoring while still benefiting from the increased security of
an isolated virtual machine.
18. Lycosid [14]
• detect running hidden process
• compares lengths of two process list views,
one built using VMI while the other one is
obtained with in-gest utilities
• In-gest utility: is a high-speed client-side DB2®
utility that streams data from files and pipes
into DB2 target tables.
• correlation of the two views of per process
CPU time consumption allows to identify the
hidden process
19. DRAKVUF[15]
• a virtualization based agentless black-box
binary analysis system
• allows for in-depth execution tracing of
arbitrary binaries
• no special software required within the virtual
machine used for analysis
20. LibVMI[16]
• a C library with Python bindings
• makes it easy to monitor the low-level details
of a running virtual machine
• views its memory
• traps on hardware events
• accesses the vCPU registers
21. Procedure
Installing all the required softwares within the system.
• Installation of LibVMI, Xen hypervisor, partition Ubuntu, DRAKVUF and utility
updates.
Bringing the virus within the VM
• Downloading the malware dataset and run executables in the VM to look up for its
system calls.
Extracting system calls through VMI
• Then we’ll extract the system calls through VMI via Xen hypervisor by giving
various commands within the host OS terminal
Preparation of dataset
• Now we’ll prepare a dataset of all the normal as well as infected filed for further
procedures.
Feature Extraction
• Feature extraction is done i.e. frequency of particular system calls, appearance of
byte codes and strings is recorded for further evaluation (Bag of words).
Classification using Machine learning
• Now we’ll apply Machine learning using Python to classify the given files as
malicious or normal
23. Bibliography
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comparative study of various routing protocols. in: Vehicular Technology Conference, IEEE, 2003.
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systems: A survey. In: Computer Communications- Elsevier, 2014.
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Communications Societies, 2005.
4. 2017 P. Mishra, E.S.Pilli, V.Varadharajana, U.Tupakaula , “Intrusion detection techniques in cloud environment: A
survey.Journal of Network and Computer Applications 77 (2017), PP. 18-47.
5. M Almorsy, J Grundy, I Müller. An analysis of the cloud computing security problem. in - arXiv preprint
arXiv:1609.01107, arxiv.org, 2016
6. Yacine Hebbal ; Sylvie Laniepce ; Jean-Marc Menaud. Virtual Machine Introspection: Techniques and
Applications. in: Availability, Reliability and Security (ARES), 2015 10th International Conference , 2015.
7. https://www.wired.com/story/2017-biggest-hacks-so-far/
8. https://en.wikipedia.org/wiki/Intrusion_detection_system
9. http://www.forum-intrusion.com/archive/Intrusion%20Detection%20Techniques%20and%20Approaches.htm
10. Yacine Hebbal ; Sylvie Laniepce ; Jean-Marc Menaud. Virtual Machine Introspection: Techniques and
Applications, in : Availability, Reliability and Security (ARES), 2015 10th International Conference on, IEEE, 2015
11. http://searchservervirtualization.techtarget.com/feature/Whats-the-difference-between-Type-1-and-Type-2-
hypervisors
12. Yacine Hebbal ; Sylvie Laniepce ; Jean-Marc Menaud. Virtual Machine Introspection: Techniques and
Applications, in : Availability, Reliability and Security (ARES), 2015 10th International Conference on, IEEE, 2015
13. B. Payne, M. Carbone, M. Sharif, and W. Lee, “Lares: An architecture for secure active monitoring using
virtualization,” in Security and Privacy, 2008. SP 2008. IEEE Symposium on, pp. 233–247, May 2008.
14. B. D. Payne, M. De Carbone, and W. Lee, “Secure and flexible monitoring of virtual machines,” in Computer
Security Applications Conference, 2007. ACSAC 2007. Twenty-Third Annual, pp. 385–397, IEEE, 2007.
15. https://drakvuf.com/
16. http://libvmi.com/