Biblio

"Security first" is the most concerned issue of Linux administrators. Security refers to the integrity of data. The authentication security and integrity of data are higher than the privacy security of data. Firewall is used to realize the function of access control under Linux. It is divided into hardware or software firewall. No matter in which network, the firewall must work at the edge of the network. Our task is to define how the firewall works. This is the firewall's policies and rules, so that it can detect the IP and data in and out of the network. At present, there are three or four layers of firewalls on the market, which are called network layer firewalls, and seven layers of firewalls, which are actually the gateway of the agent layer. But for the seven layer firewall, no matter what your source port or target port, source address or target address is, it will check all your things. Therefore, the seven layer firewall is more secure, but it brings lower efficiency. Therefore, the usual firewall schemes on the market are a combination of the two. And because we all need to access from the port controlled by the firewall, the work efficiency of the firewall has become the most important control of how much data users can access. This paper introduces two types of firewalls iptables and TCP\_Wrappers. What are the differences between the use policies, rules and structures of the two firewalls? This is the problem to be discussed in this paper.

Network intrusion detection technology has been a popular application technology for current network security, but the existing network intrusion detection technology in the application process, there are problems such as low detection efficiency, low detection accuracy and other poor detection performance. To solve the above problems, a new treatment combining artificial intelligence with network intrusion detection is proposed. Artificial intelligence-based network intrusion detection technology refers to the application of artificial intelligence techniques, such as: neural networks, neural algorithms, etc., to network intrusion detection, and the application of these artificial intelligence techniques makes the automatic detection of network intrusion detection models possible.

This paper proposes a new strategy, named resident strategy, for defending IoT networks from repeated infection of malicious botnets in the Botnet Defense System (BDS). The resident strategy aims to make a small-scale white-hat botnet resident in the network respond immediately to invading malicious botnets. The BDS controls the resident white-hat botnet with two parameters: upper and lower number of its bots. The lower limit prevents the white-hat botnet from disappearing, while the upper limit prevents it from filling up the network. The BDS with the strategy was modeled with agent-oriented Petri nets and was evaluated through the simulation. The result showed that the proposed strategy was able to deal with repeatedly invading malicious botnets with about half the scale of the conventional white-hat botnet.

Cloud provides access to shared pool of resources like storage, networking, and processing. Distributed denial of service attacks are dangerous for Cloud services because they mainly target the availability of resources. It is important to detect and prevent a DDoS attack for the continuity of Cloud services. In this review, we analyze the different mechanisms of detection and prevention of the DDoS attacks in Clouds. We identify the major DDoS attacks in Clouds and compare the frequently-used strategies to detect, prevent, and mitigate those attacks that will help the future researchers in this area.

Traditional magnetic mirrors are appealing because of their comparably simple geometry which lends itself to cost-effective construction. However, magnetic mirrors suffer from several inherent problems that make them poor choices for confining and heating plasmas. The chief concerns are the loss-cone instability which continuously saps hot particles from the trap and the interchange instability which effectively transports hot plasma from the core of the trap to the edges where it is lost to the walls. Centrifugal confinement schemes address these concerns with the addition of supersonic poloidal rotation which can effectively shut off the loss-cone. In addition, velocity shear in the flow may mitigate or even turn off the interchange instability if high enough rotation speeds can be achieved. Previous experiments have verified the efficacy of centrifugal confinement but have been unable to achieve sufficient rotation velocities to entirely shut down the interchange modes. [1] The rotation velocity in these experiments was limited by the Critical-Ionization-Velocity (CIV) instability. [3] We plan an experiment to verify that the CIV is the limiting factor in supersonic plasma centrifuges and to explore strategies for avoiding the CIV limit and achieving sufficient rotation speeds to enable stable plasma confinement.

In this paper, a novel method is proposed to assess the power system resilience considering the impacts of hurricanes. Firstly, the transmission line outage model correlated to wind speed is developed. Then, Probability Load Flow (PLF) considering the random outage of lines and the variation of loads is designed, and Latin Hypercube Sampling (LHS) is used to improve the efficiency of Monte Carlo Simulation (MCS) in solving PLF. Moreover, risk indices, including line overloading, node voltage exceeding limit, load shedding and system collapse, are established to assess the resilience of power systems during hurricanes. The method is tested with a modified IEEE 14-bus system, and simulation results indicate the effectiveness of the proposed approach.

This publication deals with the robust attitude stabilization of a quadrotor subject to stealthy actuator attacks. Based first on the nonlinear model of the system, the sector non-linearity approach will be applied in order to deduce a polytopic Takagi-sugeno model. In parallel, a polytopic fuzzy T-S modeling of the data-deception malicious attacks (time-varying parameters) is presented. After some mathematical development, it will be shown that our original nonlinear system subject to stealthy actuator attacks can be represented as an uncertain polytopic T-S system. Based on this latest model, basic concepts for attitude stabilization will be used to implement the control law. The stabilization conditions will be given in terms of Linear Matrix Inequalities (LMIs) deduced from a classical Lyapunov approach. In order to highlight the efficiency of the proposed approach, simulation results will be given.

The internet has grown increasingly important in everyone's everyday lives due to the availability of numerous web services such as email, cloud storage, video streaming, music streaming, and search engines. On the other hand, attacks by computer programmes such as bots are a common hazard to these internet services. Captcha is a computer program that helps a server-side company determine whether or not a real user is requesting access. Captcha is a security feature that prevents unauthorised access to a user's account by protecting restricted areas from automated programmes, bots, or hackers. Many websites utilise Captcha to prevent spam and other hazardous assaults when visitors log in. However, in recent years, the complexity of Captcha solving has become difficult for humans too, making it less user friendly. To solve this, we propose creating a Captcha that is both simple and engaging for people while also robust enough to protect sensitive data from bots and hackers on the internet. The suggested captcha scheme employs animated artifacts, rotation, and variable fonts as resistance techniques. The proposed captcha technique proves successful against OCR bots with less than 15% accuracy while being easier to solve for human users with more than 98% accuracy.

Watermarking is one of the most common data hiding techniques for multimedia elements. Broadcasting, copy control, copyright protection and authentication are the most frequently used application areas of the watermarking. Secret data can be embedded into the cover image with changing the values of the pixels in spatial domain watermarking. In addition to this method, cover image can be converted into one of the transformation such as Discrete Wavelet Transformation (DWT), Discrete Cousin Transformation (DCT) and Discrete Fourier Transformation (DFT). Later on watermark can be embedded high frequencies of transformation coefficients. In this work, cover image transformed one, two and three level DWT decompositions. Binary watermark is hided into the low and high frequencies in each decomposition. Experimental results show that watermarked image is robust, secure and resist against several geometric attacks especially JPEG compression, Gaussian noise and histogram equalization. Peak Signal-to-Noise Ratio (PSNR) and Similarity Ratio (SR) values show very optimal results when we compare the other frequency and spatial domain algorithms.

Emails are widely used as a form of communication and sharing files in an organization. However, email is widely used by cybercriminals to spread malware and carrying out cyber-attacks. We implemented an open-source email gateway in conjunction with a security sandbox for securing emails against malicious attachments. The email gateway scans all incoming and outgoing emails and stops emails containing suspicious files. An automated python script would then send the suspected email to the sandboxing element through sandbox API for further analysis, while the script is used also for the prevention of duplicate results. Moreover, the mail server administrator receives notifications from the email gateway about suspicious attachments. If detected attachment is a true positive based on the sandbox analysis result, email is deleted, otherwise, the email is delivered to the recipient. The paper describes in an empirical way the steps followed during the implementation, results, and conclusions of our research.

The widespread adoption of eCommerce, iBanking, and eGovernment institutions has resulted in an exponential rise in the use of web applications. Due to a large number of users, web applications have become a prime target of cybercriminals who want to steal Personally Identifiable Information (PII) and disrupt business activities. Hence, there is a dire need to audit the websites and ensure information security. In this regard, several web vulnerability scanners are employed for vulnerability assessment of web applications but attacks are still increasing day by day. Therefore, a considerable amount of research has been carried out to measure the effectiveness and limitations of the publicly available web scanners. It is identified that most of the publicly available scanners possess weaknesses and do not generate desired results. In this paper, the evaluation of publicly available web vulnerability scanners is performed against the top ten OWASP11OWASP® The Open Web Application Security Project (OWASP) is an online community that produces comprehensive articles, documentation, methodologies, and tools in the arena of web and mobile security. vulnerabilities and their performance is measured on the precision of their results. Based on these results, we proposed an Integrated Multi-Agent Blackbox Security Assessment Tool (SAT) for the security assessment of web applications. Research has proved that the vulnerabilities assessment results of the SAT are more extensive and accurate.

This paper introduces a new type of attack on isolated, air-gapped workstations. Although air-gap computers have no wireless connectivity, we show that attackers can use the SATA cable as a wireless antenna to transfer radio signals at the 6 GHz frequency band. The Serial ATA (SATA) is a bus interface widely used in modern computers and connects the host bus to mass storage devices such as hard disk drives, optical drives, and solid-state drives. The prevalence of the SATA interface makes this attack highly available to attackers in a wide range of computer systems and IT environments. We discuss related work on this topic and provide technical background. We show the design of the transmitter and receiver and present the implementation of these components. We also demonstrate the attack on different computers and provide the evaluation. The results show that attackers can use the SATA cable to transfer a brief amount of sensitive information from highly secured, air-gap computers wirelessly to a nearby receiver. Furthermore, we show that the attack can operate from user mode, is effective even from inside a Virtual Machine (VM), and can successfully work with other running workloads in the background. Finally, we discuss defense and mitigation techniques for this new air-gap attack.

One way to detect and assess software vulnerabilities is by extracting security-related information from commit messages. Automating the detection and assessment of vulnerabilities upon security commit messages is still challenging due to the lack of structured and clear messages. We created a convention, called SECOM, for security commit messages that structure and include bits of security-related information that are essential for detecting and assessing vulnerabilities for both humans and tools. The full convention and details are available here: https://tqrg.github.io/secom/.

IoT technology is finding new applications every day and everywhere in our daily lives. With that, come new use cases with new challenges in terms of device and data security. One of such challenges arises from the fact that many IoT devices/nodes are no longer being deployed on owners' premises, but rather on public or private property other than the owner's. With potential physical access to the IoT node, adversaries can launch many attacks that circumvent conventional protection methods. In this paper, we propose Secure SoC (SecSoC), a secure system-on-chip architecture that mitigates such attacks. This include logical memory dump attacks, bus snooping attacks, and compromised operating systems. SecSoC relies on two main mechanisms, (1) providing security extensions to the compute engine that runs the user application without changing its instruction set, (2) adding a security management unit (SMU) that provide HW security primitives for encryption, hashing, random number generators, and secrets store (keys, certificates, etc.). SecSoC ensures that no secret or sensitive data can leave the SoC IC in plaintext. SecSoC is being implemented in Bluespec System V erilog. The experimental results will reveal the area, power, and cycle time overhead of these security extensions. Overall performance (total execution time) will also be evaluated using IoT benchmarks.

Nowadays, improving the reliability and security of the transmitted data has gained more attention with the increase in emerging power-limited and lightweight communication devices. Also, the transmission needs to meet specific latency requirements. Combining data encryption and encoding in one physical layer block has been exploited to study the effect on security and latency over traditional sequential data transmission. Some of the current works target secure error-correcting codes that may be candidates for post-quantum computing. However, modifying the popularly used channel coding techniques to guarantee secrecy and maintain the same error performance and complexity at the decoder is challenging since the structure of the channel coding blocks is altered which results in less optimal decoding performance. Also, the redundancy nature of the error-correcting codes complicates the encryption method. In this paper, we briefly review the proposed security schemes on Turbo codes. Then, we propose a secure turbo code design and compare it with the relevant security schemes in the literature. We show that the proposed method is more secure without adding complexity.

Data streaming over a wireless network such as Wireless Sensor Networks, where wireless terminals (like PDAs, mobile phones, palmtops) access in data conferencing system, new challenges will be brought about. goal for this paper is to propose a high-speed lightweight encryption (HSLE) for low computational capability controller of WSN, HSLE scheme which reduces latency overhead by modifying existing approaches in order to encrypting data using a probabilistic encryption of data blocks. Proposed work is also useful when we communicate our confidential data on WSN or IoT it should be secure, we just have to save an encrypted data on cloud servers. proposed work is a new key-based algorithm and uses HSLE encryption instead for high end AES. Proposed methods cause significant speed enhancement for data encryption with similar security, in addition, it is best suited in order to communication between hand-held devices such as mobile phones, palmtops etc. algorithm may be used between sites where processing capacity and battery power are limited and efficient encryption is main necessity. This work is implemented on MATLAB and a wireless sensor network of maximum 100 nodes developed for testing the proposed network node encryption system, the time delay observed for the communication in 100 nodes WSN is less in compare with the other available works.

Healthcare has become one of the most important aspects of people’s lives, resulting in a surge in medical big data. Healthcare providers are increasingly using Internet of Things (IoT)-based wearable technologies to speed up diagnosis and treatment. In recent years, Through the Internet, billions of sensors, gadgets, and vehicles have been connected. One such example is for the treatment and care of patients, technology—remote patient monitoring—is already commonplace. However, these technologies also offer serious privacy and data security problems. Data transactions are transferred and logged. These medical data security and privacy issues might ensue from a pause in therapy, putting the patient’s life in jeopardy. We planned a framework to manage and analyse healthcare large data in a safe manner based on blockchain. Our model’s enhanced privacy and security characteristics are based on data sanitization and restoration techniques. The framework shown here make data and transactions more secure.

The emergence of CPSs leads to modernization of critical infrastructures and improving flexibility and efficiency from one point of view. However, from another point of view, this modernization has subjected them to cyber threats. This paper provides a modeling approach for evaluating the security of CPSs. The main idea behind the presented model is to study the attacker and the system behaviors in the penetration and attack phases with exploiting some defensive countermeasures such as redundant components and attack detection strategies. By using the proposed approach, we can investigate how redundancy factor of sensors, controllers and actuators and intrusion detection systems can improve the system security and delay the system security failure.

The era of technology has seen many rising inventions and with that rise, comes the need to secure our systems. In this paper we have discussed how the old generation of people are falling behind at being updated in tandem with technology, and losing track of the knowledge required to process the same. In addition this factor leads to leakage of critical personal information. This paper throws light upon the steps taken in order to exploit the pre-existing operating system, Windows 7, Ultimate, using a ubiquitous framework used by everyone, i.e. Metasploit. It involves installation of a backdoor on the victim machine, from a remote setup, mostly Kali Linux operating machine. This backdoor allows the attackers to create executable files and deploy them in the windows system to gain access on the machine, remotely. After gaining access, manipulation of sensitive data becomes easy. Access to the admin rights of any system is a red alert because it means that some outsider has intense access to personal information of a human being and since data about someone explains a lot of things about them. It basically is exposing and human hate that. It depraves one of their personal identity. Therefore security is not something that should be taken lightly. It is supposed to be dealt with utmost care.

All-or-nothing transforms (AONT) were proposed by Rivest as a message preprocessing technique for encrypting data to protect against brute-force attacks, and have many applications in cryptography and information security. Later the unconditionally secure AONT and their combinatorial characterization were introduced by Stinson. Informally, a combinatorial AONT is an array with the unbiased requirements and its security properties in general depend on the prior probability distribution on the inputs s-tuples. Recently, it was shown by Esfahani and Stinson that a combinatorial AONT has perfect security provided that all the inputs s-tuples are equiprobable, and has weak security provided that all the inputs s-tuples are with non-zero probability. This paper aims to explore on the gap between perfect security and weak security for combinatorial (t, s, v)-AONTs. Concretely, we consider the typical scenario that all the s inputs take values independently (but not necessarily identically) and quantify the amount of information H(\textbackslashmathcalX\textbackslashmid \textbackslashmathcalY) about any t inputs \textbackslashmathcalX that is not revealed by any s−t outputs \textbackslashmathcalY. In particular, we establish the general lower and upper bounds on H(\textbackslashmathcalX\textbackslashmid \textbackslashmathcalY) for combinatorial AONTs using information-theoretic techniques, and also show that the derived bounds can be attained in certain cases.

Personal data privacy is a great concern by governments across the world as citizens generate huge amount of data continuously and industries using this for betterment of user centric services. There must be a reasonable balance between data privacy and utility of data. Differential privacy is a promise by data collector to the customer’s personal privacy. Centralised Differential Privacy (CDP) is performing output perturbation of user’s data by applying required privacy budget. This promises the inclusion or exclusion of individual’s data in data set not going to create significant change for a statistical query output and it offers -Differential privacy guarantee. CDP is holding a strong belief on trusted data collector and applying global sensitivity of the data. Local Differential Privacy (LDP) helps user to locally perturb his data and there by guaranteeing privacy even with untrusted data collector. Many differential privacy algorithms handles parameters like privacy budget, sensitivity and data utility in different ways and mostly trying to keep trade-off between privacy and utility of data. This paper evaluates differential privacy algorithms in regard to the privacy support it offers according to the sensitivity of the data. Generalized application of privacy budget is found ineffective in comparison to the sensitivity based usage of privacy budget.

Sentiment Analysis (SA) is an approach for detecting subjective information such as thoughts, outlooks, reactions, and emotional state. The majority of previous SA work treats it as a text-classification problem that requires labelled input to train the model. However, obtaining a tagged dataset is difficult. We will have to do it by hand the majority of the time. Another concern is that the absence of sufficient cross-domain portability creates challenging situation to reuse same-labelled data across applications. As a result, we will have to manually classify data for each domain. This research work applies sentiment analysis to evaluate the entire vaccine twitter dataset. The work involves the lexicon analysis using NLP libraries like neattext, textblob and multi class classification using BERT. This word evaluates and compares the results of the machine learning algorithms.

Network attacks are always a nightmare for the network administrators as it eats away a huge wavelength and disturbs the normal working of many critical services in the network. Network behavior based profiling and detection is considered to be an accepted method; but the modeling data and method is always a big concern. The network event-based profiling is getting acceptance as they are sequential in nature and the sequence depicts the behavior of the system. This sequential network events can be analyzed using different techniques to create a profile for anomaly detection. In this paper we examine the possibility of two techniques for sequential event analysis using Modified GSP and IPAM algorithm. We evaluate the performance of these algorithms on the CSE-CIC-IDS 2018 data set to benchmark the performance. This experiment is different from other anomaly-based detection which evaluates the features of the dataset to detect the abnormalities. The performance of the algorithms on the dataset is then confirmed by the pattern evolving from the analysis and the indications it provides for early detection of network attacks.

Container security has received much research attention recently. Previous work has proposed to apply various machine learning techniques to detect security attacks in containerized applications. On one hand, supervised machine learning schemes require sufficient labelled training data to achieve good attack detection accuracy. On the other hand, unsupervised machine learning methods are more practical by avoiding training data labelling requirements, but they often suffer from high false alarm rates. In this paper, we present SHIL, a self-supervised hybrid learning solution, which combines unsupervised and supervised learning methods to achieve high accuracy without requiring any manual data labelling. We have implemented a prototype of SHIL and conducted experiments over 41 real world security attacks in 28 commonly used server applications. Our experimental results show that SHIL can reduce false alarms by 39-91% compared to existing supervised or unsupervised machine learning schemes while achieving a higher or similar detection rate.

In this paper, a data-driven security detection approach is proposed in a simple manner. The detector is designed to deal with false data injection attacks suffered by industrial cyber-physical systems with unknown model information. First, the attacks are modeled from the perspective of the generalized plant mismatch, rather than the operating data being tampered. Second, some subsystems are selected to reduce the design complexity of the detector, and based on them, an output estimator with iterative form is presented in a theoretical way. Then, a security detector is constructed based on the proposed estimator and its cost function. Finally, the effectiveness of the proposed approach is verified by simulations of a Western States Coordinated Council 9-bus power system.