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Network Time Protocol (NTP) servers are specialized timekeeping devices that provide synchronized and accurate time information to networked devices, ensuring precise coordination and reliability in various critical applications. CSIR-NPL is the National Metrology Institute of India which has the responsibility of time dissemination to the nation. Network time dissemination is one of the services which provide the time synchronization facility over the network via NTP servers. These NTP servers are designated as stratum 1 NTP servers in the network hierarchy as they are taking time from the authoritative atomic clock. NTP servers at CSIR-NPL are available in public domain for time dissemination. Many critical stakeholders such as internet service providers, data centres, various government organizations are the primary customers of CSIR-NPL for time services over the network. Hence, to understand the traffic dynamics coming towards the NTP servers is essential. This study aims to analyze Ethernet traffic patterns directed towards NTP servers at CSIR NPL using open-source monitoring software, i.e., Zabbix and Grafana. The study captures Ethernet traffic throughput in bits per second (bps) coming on NTP servers located at CSIR-NPL. These NTP servers are part of stacks of NTP servers responsible for disseminating Indian Standard Time over the internet. The study involves an investigation of Ethernet throughput to understand the NTP requests (packets per second) arriving for time synchronization and the pattern of incoming NTP request traffic on these servers. To evaluate NTP requests from Ethernet throughput, the conversion of Ethernet traffic from bps to packets per second (pps) is done and validation of the captured Ethernet throughput with actual traffic values obtained from the OEM software is accomplished. The investigation further explores incoming NTP traffic patterns and identifies regions where traffic reaches maximum and minimum loads, as well as its respective peaks and troughs, utilizing 5-day Ethernet datasets. The Savitzky–Golay filter is employed for data smoothing, and the gradient of the smoothed data is calculated to determine distinct regions of the traffic pattern. The results provide a comprehensive understanding of the traffic behaviour directed towards NTP servers for time synchronization, enabling the monitoring of anomalies associated with cybersecurity and contributing to the optimization of network resource allocation. [ABSTRACT FROM AUTHOR]

With large-scale Cyber-Physical Systems (Internet of Things) deployments, the low-cost networked devices are becoming ubiquitous. Time stamping of events is a basic requirement and it is crucial for distributed/isolated systems/devices to work in unison. The system clocks of these devices are not very stable and their behaviour is affected by ageing and environmental conditions. A clock’s timing behaviour is generally analysed independently by comparison to a highly stable standard reference clock using specialized instruments. Network Time Protocol (NTP) is widely used for time synchronization over computer networks. As the NTP server clock is more stable in comparison to a client’s system clock, the variation in the end device’s clock offset values with respect to the NTP server clock over a long time can be considered for analysing the behaviour of the end device’s clock. This paper presents a method for analysing clock behaviour based on NTP messages. A computer programme is developed, which utilizes an open-source NTP client library to exchange NTP messages and records end device’s system clock’s offset variations over time for a given periodicity to analyse the behaviour. This black box analysis approach does not require any direct access to the end device’s clock circuit. The solution may be useful for analysing clock behaviour for long-term stability under actual environmental conditions, for deciding time synchronization periodicity to optimize the number of synchronization packet exchanges, and for pre-deployment timing stability assessment of devices for deployment scenarios having intermittent/non-availability of periodic time synchronization. [ABSTRACT FROM AUTHOR]

The objective of the research is to provide a deep understanding of the concepts and algorithms applied for clock synchronization among the nodes of a distributed system (DS). This article describes the main algorithms related to solving the problem of time discrepancy in the clocks of a loosely coupled distributed system. It starts from the logical synchronization proposed by Lamport, which establishes a theoretical basis for temporal coordination in distributed systems, to Mills' contributions implemented in the versions of the Network Time Protocol (NTP) currently used on the Internet and the Precision Time Protocol (PTP) standardized by the IEEE, which allows for greater synchronization precision. The methodology used includes a thorough review of the literature, analyzing both centralized and decentralized algorithms. The proposals by Gusella and Zatti, which introduce innovative approaches to clock synchronization, as well as the algorithm by Cristian Flaviu, known for its simplicity and effectiveness, are addressed. The results obtained show that each algorithm has specific advantages depending on the scenario and requirements of the distributed system in question. [ABSTRACT FROM AUTHOR]

The On The Job Training (OJT) program which will be implemented in 2022-2023 also includes collaboration with the LPPNPI Jakarta Air Traffic Service Center (JATSC) Branch Office. On the Job Training (OJT) involves various divisions that handle various equipment and facilities that support aviation safety, including equipment such as the Network Time Protocol (NTP) Server used to synchronize the time of equipment connected to the server network at the Jakarta Air Traffic Services Center (JATSC), thereby ensuring accurate operating times for all connected equipment. All of these efforts aim to improve safety and efficiency in aviation at the national and international levels. However, in this case, in operation, not all equipment always runs well, as does Network Time Protocol (NTP) server 1 at the LPPNPI Jakarta Air Traffic Services Center (JATSC) Branch. The purpose of this research is that the author wants to solve the problems that occur in On the Job Training (OJT) activities at Perum LPPNPI Jakarta Air Traffic Services Center (JATSC) Branch [ABSTRACT FROM AUTHOR]

The Network Time Protocol (NTP) is one of the oldest Internet protocols, in use by millions of devices today. It performs the important function of synchronizing a host’s system clock to that of an accurate time server across a network — usually the public Internet. The objective of this study was to quantify the risk of a time spoofing attack on unsecured NTP and find out exactly what it takes for such an attack to be successful, through practical experiments with four popular NTP implementations: ntpd, NTPSec, chrony, and OpenNTPD. Results showed that an in-path (man-in-the-middle) attacker will always succeed in impersonating an NTP server; an on-path attacker will only succeed if their responses reach the client first; and an off-path attacker has little to no chance of succeeding. Results also showed that with default settings and no authentication, a chrony NTP client is the most difficult to attack, followed by OpenNTPD, then NTPSec, and finally ntpd (least secure). A novel formula is presented which can be used to determine — given a particular NTP client’s settings — how much time it would take for an attacker to successfully alter the victim’s clock by a given magnitude. As an example, altering an ntpd or NTPSec client’s clock by 1 hour takes around 12 minutes, whereas doing the same to a chrony or OpenNTPD client would take around 10 hours. Finally, symmetric-key and Network Time Security (NTS) authentication are proven to thwart even the strongest attacker.

Time synchronization is vital for accurate data collection and processing in sensor networks. Sensors in these networks often operate under fluctuating conditions. However, an accurate timekeeping mechanism is critical even in varying network conditions. Consequently, a synchronization method is required in sensor networks to ensure reliable timekeeping for correlating data accurately across the network. In this research, we present a novel dynamic NTP (Network Time Protocol) algorithm that significantly enhances the precision and reliability of the generalized NTP protocol. It incorporates a dynamic mechanism to determine the Round-Trip Time (RTT), which allows accurate timekeeping even in varying network conditions. The proposed approach has been implemented on an FPGA and a comprehensive performance analysis has been made, comparing three distinct NTP methods: dynamic NTP (DNTP), static NTP (SNTP), and GPS-based NTP (GNTP). As a result, key performance metrics such as variance, standard deviation, mean, and median accuracy have been evaluated. Our findings demonstrate that DNTP is markedly superior in dynamic network scenarios, a common characteristic in sensor networks. This adaptability is important for sensors installed in time-critical networks, such as real-time industrial IoTs, where precise and reliable time synchronization is necessary. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) aims to revolutionize users' daily lives by enabling seamless data exchange among various ubiquitous devices over the Internet. However, achieving this broad objective can pose significant challenges for applications that require synchronized timing, such as ensuring the temporal sequencing of data or synchronized performance of activities. IoT networks typically comprise entities with varying resources, making it challenging to implement existing time synchronization methods like N.T.P. (Network Time Protocol) on resource-constrained devices. On the other hand, solutions that work for constrained systems may not be scalable across diverse IoT deployments. This survey paper delves into the clock synchronization issues in IoT installations where applications require a unified perception of time. The article describes clock synchronization solutions for various models and their associated performance and discusses several research challenges related to clock synchronization. Additionally, a review of time synchronization techniques is provided to aid IoT practitioners in selecting the most relevant aspects for deployment.

Time synchronization is vital for accurate data collection and processing in sensor networks. Sensors in these networks often operate under fluctuating conditions. However, an accurate timekeeping mechanism is critical even in varying network conditions. Consequently, a synchronization method is required in sensor networks to ensure reliable timekeeping for correlating data accurately across the network. In this research, we present a novel dynamic NTP (Network Time Protocol) algorithm that significantly enhances the precision and reliability of the generalized NTP protocol. It incorporates a dynamic mechanism to determine the Round-Trip Time (RTT), which allows accurate timekeeping even in varying network conditions. The proposed approach has been implemented on an FPGA and a comprehensive performance analysis has been made, comparing three distinct NTP methods: dynamic NTP (DNTP), static NTP (SNTP), and GPS-based NTP (GNTP). As a result, key performance metrics such as variance, standard deviation, mean, and median accuracy have been evaluated. Our findings demonstrate that DNTP is markedly superior in dynamic network scenarios, a common characteristic in sensor networks. This adaptability is important for sensors installed in time-critical networks, such as real-time industrial IoTs, where precise and reliable time synchronization is necessary.

This paper describes BigBen, a network telemetry processing system designed to enable accurate and timely reporting of Internet events (e.g., outages, attacks and configuration changes). BigBen is distinct from other Internet-wide event detection systems in its use of passive measurements of Network Time Protocol (NTP) traffic. We describe the architecture of BigBen, and a cloud-based implementation developed to process large NTP data sets and provide accurate daily event reporting. We demonstrate BigBen on a 15.5TB corpus of NTP data. We show that BigBen identifies a wide range of Internet events characterized by their location, scope and duration. We compare the events detected by BigBen vs. events detected by a large active probe-based detection system. We find only modest overlap between the two datasets and show how BigBen provides details on events that are not available from active measurements. Finally, we report on the perspective that BigBen provides on Internet events that were reported by third parties. In each case, BigBen confirms the event and provides details that were not available in prior reports, highlighting the utility of the passive, NTP-based approach. [ABSTRACT FROM AUTHOR]

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Copyright of Techno.com is the property of Universitas Dian Nuswantoro, Fakultas Ilmu Komputer and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Domain name system (DNS) plays a critical part in the functioning of the Internet. But since DNS queries are sent using UDP, it is vulnerable to Distributed Denial of Service (DDoS) attacks. The attacker can take advantage of this and spoof the source IP address and direct the response towards the victim network. And since the network does not keep track of the number of requests going out and responses coming in, the attacker can flood the network with these unwanted DNS responses. Along with DNS, other protocols are also exploited to perform DDoS. Usage of Network Time Protocol (NTP) is to synchronize clocks on systems. Its monlist command replies with 600 entries of previous traffic records. This response is enormous compared to the request. This functionality is used by the attacker in DDoS. Since these attacks can cause colossal congestion, it is crucial to prevent or mitigate these types of attacks. It is obligatory to discover a way to drop the spoofed packets while entering the network to mitigate this type of attack. Intelligent cybersecurity systems are designed for the detection of these attacks. An Intelligent system has AI and ML algorithms to achieve its function. This paper discusses such intelligent method to detect the attack server from legitimate traffic. This method uses an algorithm that gets activated by excess traffic in the network. The excess traffic is determined by the speed or rate of the requests and responses and their ratio. The algorithm extracts the IP addresses of servers and detects which server is sending more packets than requested or which are not requested. This server can be later blocked using a firewall or Access Control List (ACL). [ABSTRACT FROM AUTHOR]