Prevention of security breaches completely using the existing technologies is unrealistic. As a result, intrusion detection an important component in network security. However, many current systems (IDSs) are rule-based systems, which have limitations to detect novel intrusions. Moreover, encoding rules time-consuming and highly depends on knowledge known Therefore, we propose new systematic frameworks that apply data mining algorithm called random forests misuse, anomaly,...

Information-centric networking (ICN) is a new communication paradigm that focuses on content retrieval from network regardless of the storage location or physical representation this content. In ICN, securing itself much more important than infrastructure endpoints. To achieve security goals in paradigm, it crucial to have comprehensive understanding ICN attacks, their classification, and proposed solutions. paper, we provide survey attacks unique architectures other generic an impact ICN....

Anomaly detection is a critical issue in Network Intrusion Detection Systems (NIDSs). Most anomaly based NIDSs employ supervised algorithms, whose performances highly depend on attack-free training data. However, this kind of data difficult to obtain real world network environment. Moreover, with changing environment or services, patterns normal traffic will be changed. This leads high false positive rate NIDSs. Unsupervised outlier can overcome the drawbacks detection. Therefore, we apply...

Intrusion detection is important in network security. Most current intrusion systems (NIDSs) employ either misuse or anomaly detection. However, cannot detect unknown intrusions, and usually has high false positive rate. To overcome the limitations of both techniques, we incorporate into NIDS. In this paper, present our framework hybrid system. The system combines components which random forests algorithm applied. We discuss advantages also report experimental results over KDD'99 dataset....

The Internet of Things, abbreviated as IoT, is a new networking paradigm composed wireless and wired networks, geographically distributed interconnected by "secured" backbone, essentially, the Internet. It connects billions heterogeneous devices, called using different communication technologies provides end-users, all over world, with variety smart applications. IoT constitutes evolution for in terms diversity, size, also invites cybercriminals who exploit infrastructures to conduct large...

With the rapid expansion of Internet in recent years, computer systems are facing increased number security threats. Despite numerous technological innovations for information assurance, it is still very difficult to protect systems. Therefore, unwanted intrusions take place when actual software running. Different soft computing based approaches have been proposed detect network attacks. This paper presents a genetic algorithm (GA) approach intrusion detection, and implementation approach....

Cloud computing is a unique technique for outsourcing and aggregating computational hardware needs. By abstracting the underlying machines cloud able to share resources among multiple mutually distrusting clients. While there are numerous practical benefits this system, kind of resource sharing enables new forms information leakage such as side-channels. In paper, we investigate usage CPU-cache based side-channels in how they compare traditional side-channel attacks. We go on demonstrate...

Abstract Machine learning has become the standard solution to problems in many areas, such as image recognition, natural language processing, and spam detection. In area of network intrusion detection, machine techniques have also been successfully used detect anomalies traffic. However, there is less tolerance detection domain terms errors, especially false positives. this paper, we define strict acceptance criteria, show that only very few ensemble classifiers are able meet them detecting...

The widespread proliferation of Internet connections has made current computer networks more vulnerable to intrusions than before. In network intrusions, there may be multiple computing nodes that are attacked by intruders. evidences have gathered from all such nodes. An intruder move between in the conceal origin attack, or misuse some compromised hosts launch attack on other To detect intrusion activities spread over whole network, we present a new detection system (IDS) called distributed...

Machine learning-based anomaly detection approaches have attracted increasing attention in the network intrusion community because of their intrinsic capabilities discovering novel attacks. However, most today's anomaly-based IDSs generate high false positive rates and miss many attacks a deficiency ability to discriminate from legitimate behaviors. In this paper, we propose an method using Combined Strangeness Isolation measure K-Nearest Neighbors (CSI-KNN) algorithm. The algorithm analyzes...

The requirements for spontaneous interactions in open and dynamic systems create security issues necessitate the incorporation of trust management into each software entity to make decisions. Trust encompasses various quality attributes (e.g., security, competence, honesty) helps making appropriate In this paper, we present CAT, an interaction-based Context-Aware model by considering services as contexts. We identify a number properties including context risk awareness address those proposed...

Cross Site Scripting (XSS) is one of the worst vulnerabilities that allow malicious attacks such as cookie thefts and Web page defacements. Testing an implementation against XSS (XSSVs) can avoid these consequences. Obtaining adequate test data set essential for testing XSSVs. An contains effective cases reveal Unfortunately, traditional techniques XSSVs do not address issue testing. In this work, we apply idea mutation-based technique to generate sets Our work addresses related...

Cross Site Request Forgery (CSRF) allows an attacker to perform unauthorized activities without the knowledge of a user. An attack request takes advantage fact that browser appends valid session information for each request. As result, is first place look symptoms and take appropriate actions. Current browser-based detection methods are based on cross-origin policies allow white listed third party websites requests trusted website. These approaches not effective if specified incorrectly....

As Cloud services become more common place, recent work have uncovered vulnerabilities unique to systems. Specifically, the paradigm promotes a risk of information leakage across virtual machine isolation via side-channels. In this paper, we investigate current state side-channel involving CPU cache, and identify shortcomings traditional defenses in environment. We explore why solutions non-Cloud cache-based side-channels cease environments, develop mitigation technique applicable for...

The Internet of Vehicles (IoV) is an emerging computing paradigm that delivers intelligent transportation services. In IoV system, the legitimacy, reliability, and accuracy circulating data have a direct impact on decisions operations, eventually, public safety economy. this paper, we design decentralized secure collaboration scheme protects vehicles in environment against attacks integrity. First, trustworthiness computed based their experience acquired from interactions using Bayesian...

As security has always been an afterthought of innovation, the IoT (Internet Things), in general, and authentication, particular, become a serious research challenge. Although many authentication protocols have proposed literature during past decade, most them do not fulfill performance requirements. Furthermore, only very small number these can be used Thing-to-Thing (T2T) architectures, where Things autonomously authenticate each other without involving any human intervention. In this...

With the continuous miniaturization of electronic devices and recent advancements in wireless communication technologies, Unmanned Aerial Vehicles (UAVs), general, Small (SUAVs, a.k.a., drones), particular, are becoming progressively used by civilian sector within context a variety applications, bringing great convenience to public. However, due their resource-constrained nature, risky environmental application, way communication, drones not immune from cyberthreats. As consequence, security...

Object detection algorithms suffer from a perceptual vulnerability where they cannot differentiate between counterfeit and real objects. In this paper, we investigate the in advanced driver assistance systems (ADAS) when faced with physical digital spoofing attacks. To address vulnerability, propose method named DSADA (Detecting Spoofing Attacks Driver Assistance) to mitigate creation misclassification attacks against object utilizing LiDAR point clouds objects’ spatial shapes. receives...

Cross site scripting (XSS) vulnerabilities are widespread in web-based programs. Server side detection of suspected contents can mitigate XSS exploitations early. Unfortunately, existing serve approaches impose modification server and client environments. In this paper, we develop an automated framework to detect attacks at the based on notion boundary injection policy generation. Boundaries mark content generation locations script code. We derive expected benign features dynamic that...