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Data Skewing

Data skewing is when certain values or subsets of data occur much more frequently than others in a dataset. This can lead to biased results and longer processing times. Identifying and addressing data skewing is crucial for reliable data analysis.

Data Skewing

An Overview of Data Skewing 

Data skewing attack is all about manipulating or distorting data so that a corporation makes decisions that would benefit the attacker. Usually, skewing attacks use one of two methods: they either alter the training details of an AI algorithm, or they can use an automated conversational search engine (i.e., chat bots) to distort website information, like Google Analytics or Adobe Analytics to construct the perception that people are engaging with something more than they actually are.

Data Poisoning Attacks 

To make significant corporate choices, many organizations turn to artificial intelligence algorithms. Many security systems utilize machine learning analysis to assess whether an occurrence or an artifact is malicious. Attacks that use "data poisoning" provide fictitious data points that the algorithm gradually uses to bias its judgments.

For instance, there have been several significant attempts to poison Google's Gmail spam filter. Attackers sent millions of emails with the express purpose of confusing the classifier and altering its definition of spam. This made it possible for attackers to transmit harmful emails covertly.

Data poisoning can potentially be a particularly severe threat vector since it can destabilize any AI-based security system. For instance, many enterprises employ systems called User and Event Behavioural Analytics (UEBA) for examining protection events and identifying doubtful or in-ordinary actions. These systems might be duped by data poisoning into believing that a malicious action is actually harmless.

Web Analytics Skewed 

A web analytics for skewing of data attack frequently includes the subsequent activities:  

  • Hackers utilize artificial intelligence to generate HTTP appeals that boost the traffic to particular web pages. Usually, they are e-commerce product pages that deal with important transactions. 
  • The website proprietors determine an excessive interest in that article when the web analytic tools record several visits.
  • The skewing bot may occasionally try to carry out conversions, including completing applications or making transactions. It calls for an increasingly sophisticated program structure comparable to skimming chatbots.

The website operator can decide to advertise the item with greater prominence or make it a part of marketing campaigns because of fabricated analytical information. Considering that the hackers are product associates advertised on the intended pages, they stand to gain from the owner's decision.

What Are The Consequences Of Skewing?

The automated categorization of safety incidents, the positive or negative outcomes of site designs, marketing, and price determination are just a few examples of how information is utilized for crucial corporate choices. If the details are inaccurate, decisions will also be inaccurate and harmful to company owners.

Examples of poor business choices influenced by skewing:

  • Erroneously categorizing a hostile activity as innocent—for instance, misclassifying a spam email or a recurrent login attempt—
  • Making the incorrect design decision during an A/B test might result in significant financial losses, for instance, in large eCommerce organizations.
  • Making a mistaken automated judgment, such as giving a person an erroneous credit rating. 
  • Charging lower prices for paid clicks advertisements from major marketing agencies, such as contemplating an ad's performance score incorrectly.
  • Overpaying an associate or a partner for website visits or funnel activities

Symptoms Of Skewness

Investigate any of the irregularities as mentioned below in the volume of traffic on your website or in the application to check for activities related to skewing the data: 

  • Abnormal surges in traffic
  • Unusual user increase in some categories
  • Disproportionately high sessions or page counts
  • Higher than typical bounce rate
  • Unusual user actions inside a program
  • Unusual use of a product or website feature that hurts security or finances

Skewing Attacks Prevention - With My Own Hands

Use the recommendations below to prevent skewing of data on websites:

  • Block obsolete visitors or websites

Whilst sophisticated hackers can employ new user identities and sites in their URL addresses, several "script kids" use automated programs functioning on obsolete web browsers. With no risk of upsetting many genuine users, you can strictly obstruct these irrelevant browsers or utilize a robust CAPTCHA procedure.

  • Get a list of recognized domains and proxy services used for illicit activities and restrict the confirmed problematic domains and proxy sites from them. Disabling accessibility concerning these sites could prevent skew attacks from cybercriminals against your site, API-based and mobile-based applications. Remember that attackers may employ higher-level anonymity strategies, including residential proxies.
  • Protect bot-prone access points by considering all the possible Internet connections that bots can make to your systems in addition to your website. Protect every endpoint with a public-facing interface, including mobile apps and APIs. Share the information with all endpoints when you come across a bot and block it.
  • Analyze the sources of traffic—regularly examine analytics or model training data, dive deep into the information, and search for segments with distinctive characteristics. If you locate one, look into it more to see if it contains data produced by a bot.
  • Monitor usage surges. If the number of visitors to your app or site abruptly increases, go deeper to see which feature was impacted. If the whole surge is attributed to a single network, user group, or piece of functionality, it is likely the result of a skewing assault.

Once the skewing attempts are recognized, take the subsequent actions to ward off the attacks: 

  • Apply web statistics to filter out bad sources
  • Use web analytics to block problematic IP addresses
  • Examine the security barrier logs to find doubtful automated traffic associated with the odd insight analysis and set up your antivirus software to stop it.

Advanced Defense 

The following methods offer a thorough defense against malicious skewing bots.

  1. Fingerprint analysis of devices

Hackers work on a large magnitude from a single computer as they employ bots to carry out skewing assaults. It entails switching browsers, deleting cookies, or hiding your IP address. Fortunately, attackers can still be identified using digital fingerprint technology. You can recognize server settings and websites that stay unchanged during an assault utilizing digital fingerprint technology. It lets you spot instances when the same person connects repeatedly; now, you can prohibit their access to your site.

  1. Reputation assessment

Cyber Attacks frequently come from identical IP addresses or similar ones, or they behave in predetermined ways. Such traits may be gathered when a bot is found and used to improve future defenses. To automatically prevent hackers from accessing your website, for instance, you can employ datasets that include information and characteristics about identified malware

  1. Website access verification

To escape being noticed, chatbots employ many different accounts while imitating a particular web address. Access verification is a great way to determine whether users and browsers are what they seem to be to spot misbehavior. Such a technique, for instance, helps confirm that requests are placed as intended or that JavaScript agents are consistent.

  1. Analyzing behavior with artificial intelligence

Actual visitors to websites frequently exhibit consistent behaviors. Automation tools can also exhibit expected patterns, although such patterns frequently diverge from actual viewers. To analyze such variations, you can use behavior evaluation to check the visitor flow and their actions against your real-time behavior of initial accounts. You may check if an account is a human or a bot where the engagement doesn't match.

  1. Enhanced difficulties

You may send suspicious visitors successive trials to swiftly and effectively detect hacker activities. Such problems are virtually inconceivable for programmed accounts, so only real accounts must complete them.

Wallarm Will Protect Against Bots

With little disturbance to legitimate user activity, Wallarm's bot protection solution offers extensive security safeguards to guard against data poisoning attempts and determine malware bots. Additionally, Wallarm provides multi-factor authentication and API security and blocks vulnerability exploits so that only authorized traffic can access your API endpoint.

Wallarm offers multi-layered protection and bot defense to guarantee that websites and apps are always available, reachable, and secure. This includes account protection against harmful attempts against user accounts, DDoS protection to prevent any DDoS attack, a CDN to improve website performance and lower bandwidth costs, a WAF for authorized traffic and prevent bad traffic, and RASP from keeping applications safe from known and zero-day attacks.



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February 26, 2024
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