Information Security Threats to Network Based Information Systems

2009 ◽  
pp. 691-696
Author(s):  
Sumeet Gupta
Keyword(s):  
Information Security ◽  
Credit Card ◽  
New World ◽  
Denial Of Service ◽  
The Internet ◽  
Security Threats ◽  
Root Cause ◽  
Internet Users ◽  
Malicious Codes ◽  
Online Experience

While Internet has opened a whole new world of opportunity for interaction and business by removing many trade barriers, it has also opened up new possibilities and means of criminal acts altogether unheard of in the off-line world. Why do people commit crimes online? Perhaps, some of them attempt to gain unauthorised access to other’s money. Some people have fun doing so and there are others who do it to take revenge or to harm others. While the motivation of conducting criminal acts may be the same as in the off-line world, the manner of such criminal acts is unique to the Internet. The vulnerability of the information transmitted over Internet is the root cause of the sprawling of criminal acts over Internet. Both users and vendors become vulnerable to criminal acts that undermine security due to easy accessibility of Internet and easy exploitation of security loopholes in the Internet. These criminal acts can adversely affect Internet users, particularly online vendors and customers. Therefore, it is important that Internet users not only become conversant of such criminal acts but also take suitable measures to counter and avoid becoming victims of these criminal acts. In this article we examine some of the major information security threats to Internet users with particular emphasis on electronic commerce and propose plausible solutions for a safer online experience. The information security threats can be categorised into threats to the users, threats to the vendors, and threats to both users and vendors. Electronic embezzlement, sniffing and spoofing, and denial-of-service attacks are examples of threat to the vendor. Credit card frauds and malicious codes are examples of threats to the users. Cybervandalism and phishing are examples of threats to both users and vendors.

Internet Crime

Cyber Crime ◽  
2013 ◽  
pp. 1-13
Author(s):  
Tejaswini Herath ◽  
H. Raghav Rao ◽  
Shambhu Upadhyaya
Keyword(s):  
Information Security ◽  
Denial Of Service ◽  
Computer Training ◽  
The Internet ◽  
Internet Crime ◽  
Security Issues ◽  
Internet Users ◽  
Computing Skills ◽  
Use Of The Internet ◽  
And Gender

It is estimated that over 1 billion people now have access to the Internet. This unprecedented access and use of Internet by individuals around the world, however, is accompanied by malicious and mischievous activities online. With the traditional crimes such as fraud, identity theft, and harassment now being committed with the use of the Internet, and networked home computers being exploited to carry out attacks such as denial of service, spamming, phishing and virus/worm propagation, it has become important to investigate security and privacy issues as they pertain to individual Internet users. To date very little is known about what characteristics of internet users affect their computing and on-line behaviors as they relate to security online. While some attention has been paid to understand the security issues affecting corporations, research investigating security issues as they relate to home users is still in infancy. Drawing from disciplines such as criminology, sociology, consumer fraud, and information security, this study seeks to find the role of computing skills and computer training, social influence, and gender on person’s vulnerability to Internet crimes. Our findings are significant and shed light in this important area of Internet crime contributing to the information security literature.

Internet Crime

2009 ◽  
pp. 433-445
Author(s):  
Tejaswini Herath
Keyword(s):  
Information Security ◽  
Denial Of Service ◽  
Computer Training ◽  
The Internet ◽  
Internet Crime ◽  
Security Issues ◽  
Internet Users ◽  
Computing Skills ◽  
Use Of The Internet ◽  
And Gender

It is estimated that over 1 billion people now have access to the Internet. This unprecedented access and use of Internet by individuals around the world, however, is accompanied by malicious and mischievous activities online. With the traditional crimes such as fraud, identity theft, and harassment now being committed with the use of the Internet, and networked home computers being exploited to carry out attacks such as denial of service, spamming, phishing and virus/worm propagation, it has become important to investigate security and privacy issues as they pertain to individual Internet users. To date very little is known about what characteristics of internet users affect their computing and on-line behaviors as they relate to security online. While some attention has been paid to understand the security issues affecting corporations, research investigating security issues as they relate to home users is still in infancy. Drawing from disciplines such as criminology, sociology, consumer fraud, and information security, this study seeks to find the role of computing skills and computer training, social influence, and gender on person’s vulnerability to Internet crimes. Our findings are significant and shed light in this important area of Internet crime contributing to the information security literature.

HomeTec Software for Security Aspects of Smart Home Devices Based on IoT

2021 ◽  
pp. 5-16
Author(s):  
Parth Rustagi ◽  
◽  
◽  
◽  
◽  
...  
Keyword(s):  
Smart Home ◽  
Denial Of Service ◽  
Security Protocols ◽  
The Internet ◽  
Security Threats ◽  
Deep Dive ◽  
Cost Cutting ◽  
Full Control ◽  
Iot Devices ◽  
Service Data

As useful as it gets to connect devices to the internet to make life easier and more comfortable, it also opens the gates to various cyber threats. The connection of Smart Home devices to the internet makes them vulnerable to malicious hackers that infiltrate the system. Hackers can penetrate these systems and have full control over devices. This can lead to denial of service, data leakage, invasion of privacy, etc. Thus security is a major aspect of Smart home devices. However, many companies manufacturing these Smart Home devices have little to no security protocols in their devices. In the process of making the IoT devices cheaper, various cost-cutting is done on the security protocols in IoT devices. In some way, many manufactures of the devices don’t even consider this as a factor to build upon. This leaves the devices vulnerable to attacks. Various authorities have worked upon to standardize the security aspects for the IoT and listed out guidelines for manufactures to follow, but many fail to abide by them. This paper introduces and talks about the various threats, various Security threats to Smart Home devices. It takes a deep dive into the solutions for the discussed threats. It also discusses their prevention. Lastly, it discusses various preventive measures and good practices to be incorporated to protect devices from any future attacks.

Network Worms

2011 ◽  
pp. 2783-2788
Author(s):  
Thomas M. Chen ◽  
Greg W. Tally
Keyword(s):  
Denial Of Service ◽  
Human Action ◽  
Network Services ◽  
The Internet ◽  
Distributed Denial Of Service ◽  
Functional Perspective ◽  
Internet Users ◽  
Confidential Data ◽  
Self Replication ◽  
E Mail

Internet users are currently plagued by an assortment of malicious software (malware). The Internet provides not only connectivity for network services such as e-mail and Web browsing, but also an environment for the spread of malware between computers. Users can be affected even if their computers are not vulnerable to malware. For example, fast-spreading worms can cause widespread congestion that will bring down network services. Worms and viruses are both common types of self-replicating malware but differ in their method of replication (Grimes, 2001; Harley, Slade, & Gattiker, 2001; Szor, 2005). A computer virus depends on hijacking control of another (host) program to attach a copy of its virus code to more files or programs. When the newly infected program is executed, the virus code is also executed. In contrast, a worm is a standalone program that does not depend on other programs (Nazario, 2004). It replicates by searching for vulnerable targets through the network, and attempts to transfer a copy of itself. Worms are dependent on the network environment to spread. Over the years, the Internet has become a fertile environment for worms to thrive. The constant exposure of computer users to worm threats from the Internet is a major concern. Another concern is the possible rate of infection. Because worms are automated programs, they can spread without any human action. The fastest time needed to infect a majority of Internet users is a matter of speculation, but some worry that a new worm outbreak could spread through the Internet much faster than defenses could detect and block it. The most reliable defenses are based on attack signatures. If a new worm does not have an existing signature, it could have some time to spread unhindered and complete its damage before a signature can be devised for it. Perhaps a greater concern about worms is their role as vehicles for delivery of other malware in their payload. Once a worm has compromised a host victim, it can execute any payload. Historical examples of worms have included: • Trojan horses: Software with a hidden malicious function, for example, to steal confidential data or open a backdoor; • Droppers: Designed to facilitate downloading of other malware; • Bots: Software to listen covertly for and execute remote commands, for example, to send spam or carry out a distributed denial of service (DDoS) attack. These types of malware are not able to spread by themselves, and therefore take advantage of the self-replication characteristic of worms to spread. This article presents a review of the historical development of worms, and an overview of worm anatomy from a functional perspective.

scholarly journals An Effective Method for Predicting Malware Family

2020 ◽  
Vol 9 (4) ◽  
pp. 1230-1233
Keyword(s):  
Machine Learning ◽  
Malware Detection ◽  
Malicious Code ◽  
The Internet ◽  
Security Threats ◽  
Learning Approaches ◽  
Computer Viruses ◽  
Software Products ◽  
Internet Users ◽  
Rapid Spread

Today, many of devices are connected to internet through networks. Malware (such as computer viruses, trojans, ransomware, and bots) has becoming a critical concern and evolving security threats to the internet users nowadays. To make legitimate users safe from these attacks, many anti-malware software products has been developed. Which provide the major defensive methods against those malwares. Due to rapid spread and easiness of generating malicious code, the number of new malware samples has dramatically increased. There need to take an immediate action against these increase in malware samples which would result in an intelligent method for malware detection. Machine learning approaches are one of the efficient choices to deal with the problem which helps to distinguish malware from benign ones. In this paper we are considering xception model for malware detection. This experiment results shows the efficiency of our proposed method, which gives 98% accuracy with malimg dataset. This paper helps network security area for their efficient works.

scholarly journals Internet Eavesdropping: Information Security Challenge in the Cyberspace

2017 ◽  
Vol 3 (3) ◽  
pp. 243
Author(s):  
Rudy Agus Gemilang Gultom
Keyword(s):  
Information Security ◽  
The Internet ◽  
Confidential Information ◽  
Internet Users ◽  
Security Challenge ◽  
Negative Impacts

In the era of information globalization the activity of information tapping over the Internet is one of the negative impacts of the interconnectivity between the Internet users and the ease of the process of exchanging data on the Internet. The disclosure of classified sensitive or confidential information or the loss of important documents is the result of information that is not well protected. Therefore, Internet users need to know more information about eavesdropping via the Internet to improve information security.

scholarly journals Internet Fraud as a Threat to Personal Information Security

2019 ◽  
pp. 25-28
Author(s):  
Marija Maslova ◽  
Kristina Ryzhaja
Keyword(s):  
Information Security ◽  
Human Activity ◽  
Personal Information ◽  
The Internet ◽  
Software Protection ◽  
Online Fraud ◽  
Internet Fraud ◽  
Internet Users ◽  
Internet Sales ◽  
Almost All

The paper analyzes the statistics of implementing known information threats, considers new types of Internet fraud and develops recommendations for protecting against unauthorized actions of Internet scammers. Internet fraud has long gone beyond mailing and has become widespread. Fraudsters operate in almost all spheres of human activity, and with the advent of various means of communication their activities have acquired new trends. The most common methods of online fraud are the following: fake shops with Internet sales, phishing, fundraising for charity, dating sites, viral content. The paper shows that the considered methods of Internet fraud are connected not so much with the Internet as directly with the user. Internet users should not only be aware of possible types and schemes of fraud, but also take care of software protection methods such as antivirus and timely updating all applications, browsers and systems. Only being up to date, constantly learning and being interested in both new threats and methods of their protection users can protect themselves and their loved ones from losses.

scholarly journals Detection of DDoS Attacks in Software Defined Networking Using Entropy

2021 ◽  
Vol 12 (1) ◽  
pp. 370
Author(s):  
Cong Fan ◽  
Nitheesh Murugan Kaliyamurthy ◽  
Shi Chen ◽  
He Jiang ◽  
Yiwen Zhou ◽  
...  
Keyword(s):  
Detection Method ◽  
Denial Of Service ◽  
Software Defined Networking ◽  
Attack Detection ◽  
Detection Methods ◽  
Network Architectures ◽  
Security Threats ◽  
Ddos Attacks ◽  
Internet Users ◽  
Detection Effect

Software Defined Networking (SDN) is one of the most commonly used network architectures in recent years. With the substantial increase in the number of Internet users, network security threats appear more frequently, which brings more concerns to SDN. Distributed denial of Service (DDoS) attacks are one of the most dangerous and frequent attacks in software defined networks. The traditional attack detection method using entropy has some defects such as slow attack detection and poor detection effect. In order to solve this problem, this paper proposed a method of fusion entropy, which detects attacks by measuring the randomness of network events. This method has the advantages of fast attack detection speed and obvious decrease in entropy value. The complementarity of information entropy and log energy entropy is effectively utilized. The experimental results show that the entropy value of the attack scenarios 91.25% lower than normal scenarios, which has greater advantages and significance compared with other attack detection methods.

scholarly journals A Review on Malware Analysis by using an Approach of Machine Learning Techniques

IJOSTHE ◽  
2019 ◽  
Vol 3 (5) ◽  
pp. 5
Author(s):  
Aayushi Priya ◽  
Kajol Singh ◽  
Rajeev Tiwari
Keyword(s):  
Machine Learning ◽  
Malware Detection ◽  
Economic Benefits ◽  
Machine Learning Techniques ◽  
The Internet ◽  
Security Threats ◽  
Malware Analysis ◽  
Internet Age ◽  
Internet Users ◽  
Learning Techniques

In the Internet age, malware (such as viruses, trojans, ransomware, and bots) has posed serious andevolving security threats to Internet users. To protect legitimate users from these threats, anti-malware softwareproducts from different companies, including Comodo, Kaspersky, Kingsoft, and Symantec, provide the majordefense against malware. Unfortunately, driven by the economic benefits, the number of new malware sampleshas explosively increased: anti-malware vendors are now confronted with millions of potential malware samplesper year. In order to keep on combating the increase in malware samples, there is an urgent need to developintelligent methods for effective and efficient malware detection from the real and large daily sample collection.One of the most common approaches in literature is using machine learning techniques, to automatically learnmodels and patterns behind such complexity, and to develop technologies to keep pace with malware evolution.This survey aims at providing an overview on the way machine learning has been used so far in the context ofmalware analysis in Windows environments. This paper gives an survey on the features related to malware filesor documents and what machine learning techniques they employ (i.e., what algorithm is used to process the inputand produce the output). Different issues and challenges are also discussed.

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